Business-centric e-governance Bo Sundgren 2013-09-15
Here we shall look at e-society and e-governance from the perspective of businesses, including nonprofit organisations.
What is a Business? •
The term “business” should be interpreted in a broad sense, including – –
commercial businesses, aiming for profits for their owners non-profit organisations, often based on membership, with goals like: •
• •
defending and promoting certain values, shared by the members, e.g. ethical values and religions, peace, freedom of speech, equality and non-discrimination, environmental sustainability, animals’ rights; so-called voice organisations charity and concrete actions in support of people in need, vulnerable groups, or other worthy causes, e.g. the Red Cross, Doctors Without Boarders material benefits and health and safety for the members, e.g. unions, cooperatives
•
Both commercial businesses and non-profit organisations have people and/or organisations whom they are supposed to service, called customers, clients, members, or something else, the raison d’être (reason for being).
•
In addition to customers, clients, members, etc, businesses also have other stakeholders, e.g. owners and employees, whose interests they must also satisfy in order to make the organisation function well.
•
All businesses, even non-profits, have to economise with scarce resources.
•
All legal businesses have rights, but they have also duties to society: to follow the law, pay taxes, treat customers, clients, employees, and other stakeholders with respect, etc.
The role and functioning of businesses in e-society The main role of a businesses, including non-profit organisations, is to provide good and affordable products and services, often in combination. In an e-society the businesses will use computer-based technologies and information systems, and digital data, in different ways, for example:
1
in the planning, production, and marketing of their products and services as an integral part of the products and services themselves
Actually many of the products in an e-society will be information products and associated services, for example products and services produced by the media industry, and knowledge produced by research organisations. The customers of businesses may be citizens, (other) businesses, and government agencies, and we talk about the following types of businesses:
“B to C”: business to citizen “B to B”: business to business “B to A”: business to administration
In order to be successful, businesses are depending on government institutions providing good public services, good infrastructures, and a relevant, efficient, and uncorrupt legal framework. Businesses and non-profit organisations should themselves have chances to get their voices heard, in a democratic way, in the development and implementation of laws and norms, for example through consultation processes and participation in decision-making processes – together with other stakeholders.
The rights and duties of businesses in e-society In a democratic, knowledge-based market economy, businesses and non-profit organisations should have good opportunities to fulfil their legitimate purposes and roles, such as providing good, costeffective, and affordable products and services to citizens, other businesses and organisations, and administrative agencies, while adhering to democratically agreed laws and norms. Furthermore, they should themselves have chances to get their voices heard, in a democratic way, in the development and implementation of these laws and norms, for example through consultation processes and participation in decision-making processes – together with other stakeholders. Furthermore, businesses and non-profit organisations should – like citizens – be treated in a fair, secure, and efficient way
when dealing with their customers, suppliers, and other business partners and stakeholders
when fulfilling different duties (e.g. paying taxes), and even when being the subject of justified repressive actions (e.g. when having committed a crime)
Businesses do not only have rights. They also have duties towards their business counterparts (customers, suppliers, and other stakeholders) and towards society as a whole, represented by government authorities and administrative agencies. Rights In short, a business organisation, commercial or non-profit, in a modern, democratic society, characterised by good governance, should expect a number of things that may be classified into the following categories:
2
Businesses getting their voices heard: businesses getting their voices heard, e.g. through freedom of speech, freedom of in formation and freedom of knowledge, and by being offered fair opportunities to participate actively and constructively in public decision processes.
Freedom to exploit new business opportunities, enabled by new technologies and the new dimensions of freedom of information (including open data) and freedom of knowledge (including open access to scientific knowledge, open research, open innovation, and open source software), supported by good governance in e-society.
Businesses getting good services, especially public services provided by government agencies and by companies and organisations funded by government agencies, that is, by tax-payers’ money. In their role as customers, businesses should also expect to get good products and services, in a safe way, from their business counterparts.
Business activities being served and supported by well functioning infrastructures: information infrastructures, technical infrastructures, etc; hard and soft infrastructures.
Businesses being served and supported by fair and well functioning legal frameworks: laws, regulations, administrative procedures ensuring businesses o freedom of speech, freedom of information, and freedom of knowledge o free competition on relevant markets without any other limitations than those given by laws and public agreements, and without interference by corruptive actors o good services from administrations on all levels, when needed o to be treated in a fair, secure, and efficient way when fulfilling different duties (e.g. paying taxes), and even when being the subject of justified repressive actions (e.g. when having committed a crime) o to be treated in a fair, secure, and efficient way in business transactions and other relationships with their customers, suppliers, and other business partners and stakeholders
Duties Like citizens, businesses do not only have rights vis-à-vis society, they also have duties. A primary duty, inherent in the role of businesses, is of course to provide good products and services, including e-services. Businesses have duties towards their business counterparts (customers, suppliers, and other stakeholders) and towards society as a whole, represented by government authorities and administrative agencies. Some examples of duties:
To produce products and services with good quality in an efficient way To respect laws and good governance, including non-corruption To comply with administrative regulations, efficiently and with good quality Respect the rights of others, including freedom of speech, freedom of information, and freedom of knowledge To treat customers and other stakeholders with respect and service-mindedly To make use of relevant methods and tools for ensuring customer satisfaction 3
Good governance in a good society requires all actors to comply with laws and regulations that have been established in good democratic order. Furthermore, all actors should comply with the laws and regulation in an efficient way and with good quality. To fulfil duties in an efficient way should be obvious for a business that has to be efficient in all possible ways in order to survive on a competitive market. Nevertheless, it may be needed to be said, since otherwise the business may get the impression that the duties are more difficult and resource-consuming to fulfil than they actually are, and complain about this. It may not be equally self-evident for a business to fulfil its duties with good quality. For example, if a business is required to provide data to official statistics or even to its own trade or industry organisation, it may be tempting to save time and money by doing this in a careless way. This may in turn cause bad decisions by the organisation and agencies using the data. It may also seem to be self-evident that businesses should treat their customers with respect and in a service-minded way may. Nevertheless there are businesses that do not live up to this requirement, maybe because they do not fully understand how important it may be for the survival and success of their business. The second part of this duty is to make use of relevant methods and tools for ensuring customer satisfaction. Modern information technology, including the Internet and Internet-based methods and tools, like social communities, have drastically improved the possibilities for businesses to pursue customer satisfaction and other customer-related goals in a constructive, efficient, and affordable way. For example, most Internet-based e-commerce businesses routinely ask their customers for feedback concerning all parts of the sales process, from marketing and order to delivery and payment. New challenges and opportunities for businesses in e-society E-society is associated with some revolutionary changes because of the massive introduction of disruptive technologies. One of the implications of this is that businesses have to do some radical and innovative rethinking on important topics. Some examples of issues that require innovative rethinking by e-service providers:
Business models for the information economy Entrepreneurship Public procurement Business Intelligence and Big Data Social media from a business perspective The need for one-stop solutions (an organisational problem) The need to adapt to user equipment and user software
The challenges and opportunities associated with these issues will be treated in a later chapter of this document.
Businesses getting their voices heard Businesses get their voices heard through: 4
freedom of speech freedom of information freedom of knowledge public consultations active and constructive participation in public decision processes
In a democratic, knowledge-based society with freedom of speech and with a lot of economic freedom, businesses and non-profit organisations should have good opportunities to take initiatives, create innovations, and perform their daily activities, while adhering to democratically agreed laws and norms. Furthermore, they should themselves be able to influence and develop these laws and norms in a democratic way, through public consultations, and through participative decision analysis and decision-making processes.
Read more Read more about freedom of speech, freedom of information, and freedom of knowledge in Sundgren (2013b). Read about e-participation and participative decision-making in Sundgren (2013b). For a more extensive treatment of the subject of e-participation and participative analysis and decision-making, the reader is referred to the education module “Participative decision analysis”, developed by Aron Larsson and belonging to the course “E-society – evolution or revolution”. The course is available via the DSV learning platform iLearn2 or via the course website https://sites.google.com/site/esocietycourse2013/; here is the link directly to the course module on “Participative decision analysis”: https://sites.google.com/site/esocietycourse2013/module-3. These sources focus on e-participation for citizens, but much of the education material is equally relevant for e-participation for businesses (and other stakeholder), for example how businesses could participate in analyses and decision-making concerning important issues on different levels of society: local, regional, central.
Freedom to exploit new business opportunities The basic human rights of freedom of knowledge and information may be developed into a powerful platform for new e-services and new business opportunities when empowered by modern information technology, including the Internet. The following topics and phenomena, enabled by modern information technologies in e-society, are particularly relevant and significant for businesses wanting to take advantage of the emerging new dimensions of freedom of information and freeedom of knowledge:
The EU directive concerning Public Sector Information Open data Open access to scientific knowledge Net-based learning and education Open data in science 5
Open research Open innovation Open source software
Read more These topics are treated further in Sundgren (2013b, c, e, f).
Exercise The reader is asked to suggest some business opportunities that you can see for companies and organisations that want to exploit the new dimensions of freedom of information and freedom of knowledge.
Businesses providing good services In order to provide good services in an e-society, businesses must meet the demands from citizens and other customers who need these services, as discussed in Sundgren, B. (2013c). Citizen-centric egovernance. Providing good services includes:
Providing good services to citizens, possibly on behalf of administrative agencies, for example as subcontractors Providing good services to other businesses, commercial as well as non-profits Providing good services to public organs and administrations
Regardless of whether citizen-centric services are provided by public or private actors, there is a need for reliable infrastructures in order to ensure the proper functioning, good quality, and safety of the services provided. The infrastructures may be technical, information system oriented, legal, and organisational. The infrastructures need to be managed in an efficient and non-corrupt way, and this is ultimately the responsibility of the government and its principles, systems, and practices of governance.
What is an e-service? It is difficult to provide an exact definition of the concept of an e-service. However, an important feature of e-services is the use of technology, including the Internet, to facilitate the production and delivery of such services. E-services have four main components:
service providers service receivers channels of service delivery (technology supported) one or more (physical) products and/or services, often in combination
For example, as regards private e-services, businesses and non-profit organisations are the service providers and citizens as well as businesses and public administrations are the service receivers. The 6
channel of service delivery is the third requirement of e-service. Internet is the main channel of eservice delivery while other classic channels (e.g. telephone, call center, public kiosk, mobile phone, television) are also considered. The domain of e-services has become an established branch of e-government and is recognised by both practitioners and researchers as being of strategic importance in the modernisation of the public sector. E-services can be provided by private actors (commercial as well as non-profit) as well as by governments (on different levels), or by government agencies. Public e-services may also be operated by private actors, to whom governments and government agencies have outsourced or outcontracted such operations. Some of the e-service needs are so important and complex that they have given rise to new research disciplines, for example:
e-learning e-health e-commerce and e-business
One type of e-services is e-commerce. E-commerce, is the buying and selling of goods and/or services electronically. It also includes additional forms of commerce performed over the Internet, such as the transfer of funds. Electronic commerce includes consumer-based business (B to C) and transactions between businesses (B to B). It has no time or space barriers. For example, a consumer in one country is instantly able to complete a transaction with a business in another country. E-service providers can typically create an online interface to allow customers to order products and/or services at any time, using one or more convenient payment methods. The same interface can be used for providing customer service functions. If a customer needs to return or exchange a product, dispute a charge or work out a problem with the order, he or she can log on to do so. A company representative can evaluate the information that the customer submits and decide how to proceed if the transaction cannot be handled automatically. Customer services can also refer to the practice of providing people with a positive, helpful experience before, during, or after buying something. It also can refer to a department within a company that focuses on these processes. Employees can engage with individuals face-to-face, by phone or through written communications. Many businesses spend a great deal of time getting feedback and training their employees for this purpose, because it makes a client more likely to become loyal. Companies that specialise in e-services can provide a basic software package for an agency or company to use. The user can customise the package to meet specific needs with things such as inserting a logo or adding new fields for different activities. It also is possible to request a custom software package for a very specific purpose that cannot be met using generic software. Government agencies, for instance, might have concerns about the privacy of information and might need a more robust program with excellent security. References: 7
Wikipedia: http://en.wikipedia.org/wiki/E-Services wiseGEEK: http://www.wisegeek.com/what-are-e-services.htm wiseGEEK: http://www.wisegeek.com/what-is-electronic-commerce.htm wiseGEEK: http://www.wisegeek.com/what-is-customer-service.htm Sundgren (2013c). Citizen-centric e-governance. See also special chapters in Sundgren (2013f).
Requirements to be satisfied by e-service providers E-service receivers (citizens, businesses, and public administrations) demand well functioning eservices from both public and private e-service providers, wherever and whenever e-services are relevant. It is important that the services are seen from the perspectives of the service receivers, which do not necessarily coincide with the perspectives of those responsible for producing and delivering the services, regardless of whether they are public or private organisations. Three examples of problems that require innovative thinking by e-service providers are:
The need for one-stop solutions (an organisational problem) The need to adapt to user equipment and user software How to get overviews of o society o information about society o available services, including e-services o qualities and costs of available services and e-services
One-stop solutions The problem A typical quality of e-services demanded by e-service receivers is that the services should be delivered according to the so-called one-stop principle. If you as a service receiver have a specific problem or need, the whole problem or need should be met at one place (for example one website) by one service provider, who takes the responsibility for serving the service receiver from start to end. If the problem or need is complex, it may require the involvement of a number of different public and/or private organisations, or departments within organisations, but ideally this should not be visible to the customer/client: the necessary co-operation and co-ordination between the service providers should take place “behind the scene”. The service receiver should be met by one service provider, via one interface, taking full responsibility, and should not be sent from one organisation or department to another for different parts or aspects of the total problem or need. This problem typically arises when the service-providers (for example businesses or government agencies) are hierarchically organised by so-called stovepipes. The stovepipe organisation may be seen as rational from the service-providers’ perspectives, since it supports specialisation on different types of tasks. However, the stovepipe structure may not at all correspond to the natural structure of the problems and needs of the service receivers who are the customers and clients of the services. There is a structural clash that needs to be resolved, and it should be resolved by the service providers, not by the service customers. 8
For example, if a customer has a problem with a product or a service purchased from a company, he or she should not have to determine what kind of problem it is, whether it is a technical or administrative problem, for example, or whether the problem has occurred because of some mistake by some other actor that has been involved in the production or delivery of the product or service. The company with which the customer has been in contact when buying the product or service should take care of the problem vis-à-vis the customer, and then take any necessary contacts with other actors involved “behind the scene”. Another example: if you and your family have a problem and need help from society, this problem may have many different aspects (unemployment, lack of education, poverty, illness, housing), and it is not constructive or optimal to send the client to different agencies for these different aspects, when it is the family’s whole life situation that needs to be tackled in a well coordinated way.
On the other hand, assuming that the customer’s need can be met via a single interface, in a onestop solution, it could very well be both rational and efficient for the work behind the scene to be organised as a well co-ordinated co-operation between a number of actors, both public and private. For example, a public actor could engage private actors as subcontractors. How to come to grips with the problem There are a number of ways to come to grips with the “one-stop service” problem, for example:
Modelling services from request to response by means of life-cycles Using web portals as entry points to services Using a service-oriented architecture (SOA) for design and implementation of e-services
Modelling services by means of life-cycles from request to response A service may be modelled by means of a life cycle flow diagram, also called life history flow diagram, starting with a user request, going through a more or less complex sequences, selections, and iterations of subtasks, until the final response to the request has been delivered to the user. The structure of a life cycle flow is formally equivalent with the structure of a well-structured computer program, consisting of the three basic structures:
Sequence: First A, then B Selection: Either A, or B, or … depending on the condition X Iteration: Repeat A until condition Y is fulfilled
References: Wikipedia: http://en.wikipedia.org/wiki/Structured_programming Böhm, C. and Jacopini, G. (1966). Flow diagrams, Turing machines and languages with only two formation rules, Comm. ACM, 9(5):366-371. Jackson, M.A. (1975). Principles of Program Design, Academic Press, London. Dahl, O.J., Dijkstra, E.W. Hoare, C.A.R. (1972). Structured Programming, Academic Press, London. 9
Dijkstra, E.W. (1968). "Go To Statement Considered Harmful". Communications of the ACM (PDF) 11 (3): 147–148. doi:10.1145/362929.362947. Using web portals as entry points to services References: wiseGEEK: http://www.wisegeek.com/what-is-a-portal.htm Wikipedia: http://en.wikipedia.org/wiki/Web_portal Web portals are useful instruments for creating entry-points to e-services, and, if designed properly, they may focus on the needs of the users, for example citizens of businesses in e-society. The scope of a web portal may vary a lot. It may be the entry-point to a particular e-service, provided by a particular agency or company, it may be the entry-point to a wide collection of e-services, provided by an organisation, or it may be an entry-point a lot of e-services that are relevant for a particular kind of user with a particular kind of problem or need. In the latter situation, there may be services and “sub-services” from a wide range of agencies and businesses co-operating behind the scene. A web-portal may be used to provide solutions to the problems mentioned earlier:
The need for one-stop solutions (an organisational problem) The need to adapt to user equipment and user software
In order to solve the first problem, overcoming the structural clash between the user’s problem and the stove-pipe organisation of the service provider(s), the web portal service, which is visible to the user, may send messages to other services, provided by the same organisation or other organisations, asking them to do certain things, and send a message back to the requesting service, when it has done what it was asked to do. (This is an application of a service-oriented architecture, SOA.) The sub-services, may again send service requests to other sub-services, etc. When the web portal service has finally got responses from all sub-services that it has used, it may give a response to the service request from the user, hopefully providing a complete solution to the user’s problem or need. The process just described may be quite complex, involving several organisations (agencies and/or businesses), and several departments within each organisation. An important technical problem in this context is to manage what happens, if the processing of a particular user request should be broken at some stage, either voluntarily by the user, or because some sub-service was denied, for example a credit card payment, or because of some kind of technical error. The whole user request must then be rolled back, so that the statuses of all systems and subsystems are reset to what they were before the user request was initiated. In order to solve the second problem, adapting the service to any kind of user equipment and/or software, the web portal and the services that can be initiated from the web portal are made available to all kinds of technical environments in user devices. The topic of web portals is treated more extensively in a separate document: Sundgren (2013f).
10
Using a service-oriented architecture for design and implementation of e-services With the rapidly growing importance of the Internet and web-based information systems, the client/server architecture is becoming replaced by service-oriented architectures (SOA), based on well-defined, standardised services, which can be used in a standardised way, via standardised messages and communication protocols, by other services. Service-oriented architectures are based on the following design principles; Erl (2005): •
Loose coupling – Services maintain a relationship that minimises dependencies and only requires that they retain an awareness of each other.
•
Service contract – Services adhere to a communications agreement, as defined collectively by one or more service descriptions and related documents.
•
Autonomy – Services have control over the logic they encapsulate.
•
Abstraction – Beyond what is described in the service contract, services hide logic from the outside world.
•
Reusability – Logic is divided into services with the intention of promoting reuse.
•
Composability – Collections of services can be coordinated and assembled to form composite services.
•
Statelessness – Services minimise retaining information specific to an activity.
•
Discoverability – Services are designed to be outwardly descriptive so that they can be found and assessed via available mechanisms.
More briefly and concretely expressed, a service is a piece of reusable software, smaller or bigger, which performs a well-defined function, described in a standardised way. The service can be requested by other pieces of software, which may themselves be services, through standardised messages. The service requestor should not have to know anything about the internal functioning of the activated service, and the latter should not have to know anything about its external environment, but only perform its function and (possibly) provide a standardised response message in return. During its execution a service may itself request the execution of other services in the same way. The figure below illustrates the SOA concept.
11
The topic of Service-Oriented Architectures is treated more in depth in a separate document: Sundgren (2013f).
Adaptation to user equipment and software Another important requirement from the e-service customers is that they should be able to use whatever equipment and software that they have chosen for Internet communication. This is a challenge for producers of e-services. Basically it can be met in two different ways:
By installing different versions of part of the e-service software on different devices, controlled by different operating systems, for example so-called “apps”.
By developing a web application that can be accessed from any device, controlled by any operating system.
The former solution is very complex and resource-consuming, and there are new devices coming along all the time. The second solution, which is sometimes called responsive (web) design is general and elegant, but it may be less efficient than the former solution.
Getting overviews of society, available services, and their qualities In a complex society it is important for everyone to get good overviews of: 12
society as a whole available information about society (for example official statistics) which services are available, including e-services the qualities and costs of different services
Here we shall briefly discuss two kinds of modelling approaches that may contribute solutions to some of these tasks:
Life cycle models Conceptually oriented data models
Life cycle models We have already introduced life cycle models above, when discussing how to model a service from request to response. Life cycle models are also excellent for modelling the life histories of different actors in society, e.g. citizens and businesses. Among other things, such life history models can be used for identifying the needs for services, including e-services, that these actors have during their life times. In an e-society, the needs for e-services can be met by both private as well as public actors, sometimes in combination or cooperation. By walking through typical (and exceptional) life histories of a citizen (or a family) or a business, or some other kind of potential e-service customer, we may identify a large number of needs of well functioning e-services for different life situations and life phases of the customer. An example of a life history for Person:
birth-related e-services for babies and parents e-services related to child care and pre-school activities e-services related to the school life of a child, from primary schools and onwards e-services related to a person’s relations to the labour market: finding a job, changing jobs, losing a job, etc e-services related to retraining and life-long learning needs e-services related to health and social well-being e-services related to retirement, pensions, and elderly care e-services related to paying taxes and performing other citizen duties e-services related to private consumption needs
The needs for e-services may be further elaborated by developing scenarios for different life events and activities. An example of a life history for a Business:
planning to start a new business registration of a company changing the legal status of the company merger with another company bankruptcy
Some of the e-service needs above are so important and complex that they have given rise to new research disciplines, for example: 13
e-learning e-health e-commerce and e-business
Conceptually oriented data models of society Life cycle models are process-oriented. Process models typically need to be combined with conceptual models or data models or conceputally oriented data models, as they are also called. Important purposes of such models are
to clarify important concepts and relations between concepts in a so-called object system, which may be society as a whole or some subset of society, for example a sector of society or an individual company or some other organisation
to model and document information contents, representation formats, other properties of data available about the object system, for example facts about individual objects in the object system, or statistically summarised data about the object system as a whole, or subsets of objects, classified in different ways
Conceptually oriented data models will be treated in a separate document: Sundgren (2013f).
Examples of e-services and their requirements A list of concrete examples of important areas for e-services in e-society is given in Sundgren (2013c), where they are discussed primarily from a citizen/customer perspective. However the same examples can be used for analyses from a business perspective. Actually there are two relevant business perspectives on e-services:
E-services seen from the perspective of a business as a customer of e-services E-services seen from the perspective of a business as producer of e-services
Exercise The reader is recommended to consider each example in the list separately – using the descriptions of the services in Sundgren (2013 c) as a basis – address the following questions: 1. Is there, or could there be, a role for a business in the production and delivery of this service? 2. Which requirements does this service put on the provider of the service, whether it is a business or not? 3. Could a business or organisation be a customer of this kind of service? If so, would the requirements from a business customer be different from the requirements of a citizen customer? How? 4. Could you think of other services areas or services than those in the list, which would be of particular relevance and importance for a business customer? Describe such services, and how they could be produced, by government agencies and/or by private companies and organistions. List of e-services Here is the list: 14
Travel E-commerce Metalivel e-services Education Children care Elderly care Health care Labour market Housing Social benefits, insurances, and financial support Transport of people and goods Telecommunication Taxation Public documents: passport, identification card, driving license
The efficiency and quality of e-services The reader is referred to the corresponding chapter in Sundgren (2013c), where the following aspects are discussed:
acceptance accessibility administrative literacy benchmarking digital divide e-readiness efficiency security stakeholders usability
Businesses getting good services This includes:
Getting good products and services from other businesses, both commercial and non-profit Getting good services from public organs and administrations
It is important that the services are seen from the customer/client organisation’s perspectives, which do not necessarily coincide with the perspectives of those responsible for producing and delivering the services, regardless of whether they are public or private organisations. For example, a business with a problem or a need would like to have the whole problem or need addressed by one instance, so-called one-stop service. If the problem or need is complex, it may require the involvement of a number of different public and/or private organisations, or departments within organisations, but ideally this should not be visible to the customer/client: the necessary co-operation and coordination between the service providers should take place “behind the scene”. The customer/client 15
should be met by one interface, taking full responsibility, and should not be sent from one instance to another. Both public and private organisations are often hierarchically organised into so-called stovepipes, and these hierarchies may not be congruent with the natural structure of the problems and needs of the citizens. Then there will be a structural clash between the service request and the serviceproviding organisations, which creates risks that the customer/client request will not be met in an optimal way, as just described. On the other hand, assuming that the customer/client’s need can be met via a single interface, in a one-stop solution, it could very well be both rational and efficient for the work behind the scene to be organised as a well co-ordinated co-operation between a number of actors, both public and private. For example, both public and private actors could engage other actors as subcontractors. As users of e-services (from other businesses and government administrations) businesses have, in principle, more or less the same requirements as citizens. Thus the reader is referred to read about citizens’ requirements on e-services in Sundgren (2013c).
Well functioning infrastructures Wikipedia: http://en.wikipedia.org/wiki/Infrastructure Both in traditional societies and in e-societies, well functioning infrastructures are of vital importance for the efficient functioning of all kinds of activities, not least business activities, including the production and delivery of good products and services. In the traditional society the infrastructures were mainly “physical”, so-called hard infrastructures, for example road and railroad networks. In modern information-based societies, hard infrastructures are still important, for example telecommunication networks, but another type of infrastructures, socalled soft infrastructures, are becoming more and more important. The soft infrastructures include:
Databases, registers, and information systems, often serving a wide range of different customers and purposes
Standards and rules and tools for efficient exchange of information between users and systems, and between systems, for example standards for identification and authentication, and standard formats and procedures for data interchange
Regardless of whether e-services are provided by public or private actors, there is a need for reliable infrastructures in order to ensure the proper functioning, good quality, and safety of the services provided. The infrastructures may be technical, information system oriented, legal, and organisational. The infrastructures need to be managed in an efficient and non-corrupt way, and this is ultimately the responsibility of the government and its principles, systems, and practices of governance. Infrastructure is basic physical and organisational structures needed for the operation of a society or enterprise, or the services and facilities necessary for an economy to function. It can be generally defined as the set of interconnected structural elements that provide framework supporting an 16
entire structure of development. It is an important term for judging a country or region's development. The term typically refers to the technical structures that support a society, such as roads, bridges, water supply, sewers, electrical grids, telecommunications, and so forth, and can be defined as "the physical components of interrelated systems providing commodities and services essential to enable, sustain, or enhance societal living conditions" Viewed functionally, infrastructure facilitates the production of goods and services, and also the distribution of finished products to markets, as well as basic social services such as schools and hospitals; for example, roads enable the transport of raw materials to a factory. In military parlance, the term refers to the buildings and permanent installations necessary for the support, redeployment, and operation of military forces. To make it simple, infrastructure is anything that is needed everyday, an everyday item. Governments and government administrations in any society have to provide relevant and well functioning infrastructures, resources that are of great importance for most, or at least many of the actors in the society, and which have to be organised and financed collectively in order to reach their full potential. Read more about infrastructures in Sundgren (2013e) and Sundgren (2013f).
Fair and well functioning legal frameworks A good society is a society based on laws and objective procedures, where everyone is treated alike, and where corruption and arbitrariness is absent. This is particularly important for ordinary citizens and small businesses, but it is also important for the efficiency of society as a whole, including powerful citizens and organisations, public and private. The rule of law is a fundament for good governance and a good society. An important aspect of the rule of law in an e-society is that the laws must have broad acceptance among all actors in society, including both citizens and businesses. The modern information society is associated with the introduction of so-called disruptive technologies, technologies that drastically change certain basic conditions for both citizens and businesses. If not properly dealt with by politicians and legislators, some issues caused by these radical changes may cause very serious distrust in the rule of law. A well-known example is the issue of so-called pirating, caused by the ease, inexpensiveness, and perfection of copying digital material such as texts, photographs, and music. These issues have to be solved in constructive and innovative ways, not by more repressive laws and procedures. Businesses may need to get constructive help and assistance from consultants and government agencies in order to be able to cope with the new challenges, for example to find new, viable business models. The legislators in any society should ensure that there is a legal framework that is felt by the citizens and businesses to be relevant and fair. The legal framework must balance conflicting goals and interests, for example goals concerning freedom, security, and efficiency. Furthermore it needs to be in harmony with international legislation.
17
In an information society there are many needs for modifications and changes in the legal frameworks and administrative procedures. Some traditional procedures are becoming inefficient and obsolete, for example procedures based on paper documents – modified procedures based entirely on electronic documents and procedures have to be developed and implemented. At the same time, it must be taken into account – for a foreseeable future – that some small businesses will still not be able to take full advantage of modern technology in their daily operations, and they are entitled to exist and get good services from administrative agencies and others, too. It is rather obvious, and not very surprising, that the disruptive changes caused by the technological developments enabled by such phenomena as computers, computer-supported information systems, and the Internet, has made it necessary to update existing laws and regulations, and even to introduce completely new legislation. Unfortunately, legislators and judicial experts in ministries, courts, and administrations have been very slow, and even reluctant to respond adequately to these needs. Maybe there is a natural ambition among legislators and judicial experts to try to avoid new legislation by trying to reinterpret existing concepts and laws, so as to cover new phenomena such as computer-supported processes, digital data and data processing, and Internet-enabled communication. However, there are numerous examples where this strategy has not been successful, and where it has taken much too long for new legal practices to establish themselves within the old legal frameworks. For example, the Swedish “principle of publicity”, “offentlighetsprincipen”, becomes rather toothless, when it remains sufficient for public agencies to make their data public by means of paper documents only, when journalists and others would need them in digital form in order to fulfil their tasks in an efficient way. Read more about legal frameworks in Sundgren (2013e).
Challenges and opportunities for businesses in e-society E-society is associated with some revolutionary changes because of the massive introduction of disruptive technologies. One of the implications of this is that businesses have to do some radical and innovative rethinking on important topics.
Needs for innovative rethinking Some examples of problems that require innovative rethinking by e-service providers:
Business models for the information economy Entrepreneurship Public procurement Business Intelligence and Big Data Social media from a business perspective The need for one-stop solutions (an organisational problem) The need to adapt to user equipment and user software
Business models for the information economy Source: 18
Sundgren, B. (2010). Business models and authors rights in the information economy. International Journal of Public Information Systems. Vol 2010:2, pp 171-194. The need for new business models in e-society New business models are needed for the production and marketing of information-based products and services. Innovative entrepreneurs, like the founders of Google, have understood this, and have been extremely successful in designing and implementing new business models. Other important actors in the same field, notably publishers and the media industry, are lagging long behind and do not yet seem to have fully understood the new conditions for information products, caused by the advances of information technology and, in particular, the Internet. They are acting defensively, e.g. by chasing "pirates", instead of exploiting the new opportunities in a constructive way.1 And they are not alone. According to a recent article in a Swedish business journal, a large number of CEO:s in major Swedish companies are still puzzled how companies like Google can be so profitable, although they provide information products and tools for free. In the beginning of this century it was popular to claim that the IT boom will lead to a "new economy". However, the information economy is not really a "new economy" in the sense that classical economic theories should have become outdated and invalid. But certainly the typical values of some important parameters have changed drastically, mainly because of the extremely low marginal costs for producing and distributing additional copies of information products. The new parameter values lead to new interpretations of economic theories and laws in a market economy. Some aspects of the new situation are actually known from more traditional areas in the economy like how to finance and charge for public goods and infrastructure (bridges, roads, railroads etc), where the investment costs are high, whereas the cost of using the infrastructure, once it is in place, may often be relatively low. Historical background The information economy is the latest phase in the advancement of a society’s economy. In the information economy, the development and use of tools based on information technology has become extremely important and contributes more and more to economic growth. Tools based on information technology, such as computers and computer software, typically amplify the power of the human mind by facilitating intellectual processes. During the preceding industrial era, the development and use of another category of tools facilitated rationalisation and automation of manual processes, producing material goods. Before that, in an economy based on agriculture and natural resources (mining, forestry, etc), manpower was the dominating production factor. Manpower is still an important production factor, but now more so in the service industry. Human brainpower has of course always been important, not least for the progress that has taken place in the development of the economies, and in the transitions from one type of economy to another. However, with the rapidly increasing availability of powerful information services, the impact and productivity of human brainpower has increased drastically, and will continue to do so for the foreseeable future. In summary, a society’s social and economical development may be structured into four phases:
1
Threatening customers and potential customers with law suits may seem odd in the first place. Moreover, there is actually little, if any, scientific evidence that the decline in sales of music CD:s is caused by illegal downloading of music from the Internet. Downloading of music from the Internet may rather stimulate the sales of CD:s as well as tickets for live concerts. See Findahl (2006) and Marshall (2004).
19
Phase 1. This phase is dominated by agriculture and exploration and exploitation of natural resources. The goods produced are food, raw materials, handmade tools, and energy.
Phase 2. During this phase manufacturing of goods, as well as tools and machines to assist in the production of food, goods, and energy, becomes more and more important, and more and more efficiently done, first by specialised craftsmen, later on a larger scale by specialised factories, using tools and machines, which are themselves manufactured by other factories. Manual labour is replaced or supported by machines, thus increasing the productivity of each worker. Also the farmers are empowered by machines, produced by the manufacturing industry, and thus the productivity increases in the agricultural sector, too.
Phase 3. During this phase, the production of food and physical products and tools have become so automated and rationalised that a relatively larger share of the economy can be devoted to the production of services. Services were needed also during earlier phases of the socio-economic development, but during those phases many services could only be demanded by relatively few rich people, and by businesses. Since farmers and workers have now become more productive and therefore earn more money, they are able to demand and pay for more services.
Phase 4. During this phase modern information technology, in the shape of computers, computer software, and communication networks, is introduced and used on a large scale in all sectors of society. While the traditional, mechanical technology amplifies the physical capabilities of man, information technology amplifies mental and intellectual capabilities. The information technology has enabled large-volume production and consumption of nonexpensive products and services, based on information. Computers are typically much faster and less errorprone than human beings in performing mental operations. The human being is still superior in tasks requiring imagination, innovation, and unplanned and sometimes unexpected initiatives, but even in performing such tasks, people may increase their efficiency by using advanced tools based on information and information technology.
Through the history, the relative importance of different sectors in the economy has changed dramatically. For example, agriculture accounts for only a few percent of the gross national product of an advanced society, and the manufacturing industry is going the same way as agriculture. There is an increasing demand for social services in modern societies. A major problem here is how to finance this demand for labour-intensive and often publicly financed services without increasing taxes to unacceptable levels. Inexpensive information technology and information services could play an important role to improve the productivity and efficiency in service production – as we have already seen in white-collar work both in the industry and in governments on different levels. The information economy – a new economy? Is the information economy a new economy? During the IT hype in the beginning of this century, it became common to talk about a “new economy”, where the traditional laws of economics did not apply any longer. Entrepreneurs and venture capitalists used the term to defend huge investments in companies which had yet everything to prove. Year after year these companies produced only losses, and for many of them that was virtually the only thing they had produced, when the bubble became apparent and exploded. Only those who sold their shares in time became rich. In reality companies belonging to the information economy, whichever they are, are governed by the same economic laws as other companies in a market economy. There is nothing mysterious about 20
information technology from an economic point of view. Nevertheless, use of information technology will make it possible to create production processes and produce products and services that have certain characteristics, values of certain parameters, if you like, which are different from those of more traditional production processes, products, and services. Here are some examples:
A traditional industrial process produces physical objects, e.g. cars. The individual objects produced may be very similar indeed – they may be seen as instances of one and the same type – but even so, each instance will require a non-negligible amount of resources to be produced: raw material, labour, machine capacity, etc, and these resources are associated with non-negligible costs per produced instance, or unit. In contrast, information products produced, disseminated, and consumed by means of information technology may be instantiated, or reproduced/copied, at almost no cost at all. Moreover, information may be consumed (used) without being at all consumed (worn out), that is, an information product may be used over and over again, while remaining completely intact.
A traditional service process is heavily dependent on human labour. Unlike physical products, a traditional service cannot be stored; it must be produced and consumed at the same time; example: a receptionist answering a question from a client. In contrast, a web-based self-service system can be used by many users simultaneously, without the presence of a human producer of every instance of the service – other than the self-serving consumer of the service herself.
Lee (2001) argues that electronic commerce is more than just another way to sustain or enhance existing practices. “Rather”, he claims, “e-commerce is a paradigm shift. It is a “disruptive” innovation that is radically changing the traditional way of doing business. The industry is moving so fast because it operates under totally different principles and work rules in the digital economy.” Lee proposes an analytical framework for assisting e-commerce planners and strategic managers in assessing the critical success factors when formulating e-commerce business models and strategies. The framework suggests five essential steps for e-commerce success: redefine the competitive advantage; rethink business strategy; re-examine traditional business and revenue models, reengineer the corporation and Web site; and re-invent customer service. New frameworks and guidelines for developing business models adapted to the specific needs of an information economy may certainly be very helpful both for researchers and practitioners. At the same time, such new frameworks and guidelines do not necessarily have to contradict classic economic theories that have evolved over a long time, and which have survived many changes in society, technological and others. Thus theories and models like those presented in Samuelson (1948), Samuelson (2009), Dupuit (1844), Prest and Turvey (1965), and Kotler (1967), may still be valid, by and large. One of the laws of classic economics tells us that, under perfect market conditions (perfect competition, profit-maximising sellers, buyers with full information, etc), the price of a good will be equal to the marginal cost of producing another instance (unit) of the good. See, for example, Clifton (1977), Lee (1998), and Mas-Colell, Whinston, and Green (1995). In the examples above, from the information economy, the marginal cost of producing another instance of the good (the information product, the web-based self-service) is very close to zero. Thus, even if the producer is profit-maximising, the price should be very close to zero, too. This situation is very common in the information economy, but very unusual in the traditional economy based on traditional production of goods and services. 21
Obviously the conditions just described create certain problems for companies that want to be profitable in the information economy. Probably the most important problem arises from the fact that even if the marginal cost of producing another instance of a good is very close to zero, the cost of producing the first instance, or rather the original or the (proto)type, the generator of all instances, is often quite high, as high as it would be for a prototype, or generator, of a traditional physical product or service. In the traditional economy, these costs may be treated as investments, which are distributed over a large number of produced instances, in such a way that the effect on the price of each unit of the product or service becomes very small, relatively speaking. But when the marginal cost is close to zero, even a small share of the total investment cost will have a considerable percentage effect on the price per unit, and the producer will not be able to maximise profits by applying a traditional scheme for distributing the investment costs over the instances expected to be produced and sold. The traditional investment cost allocation scheme will lead to (a) less than optimal sales, and less than optimal profits for the producer, and (b) higher than optimal prices, fewer buys, and lower than optimal total satisfaction among the potential consumers of the good. The dilemma just described is not completely unknown in the traditional economy. A similar situation often occurs for infrastructural goods like roads, railroads, bridges, networks for telecommunication, electricity distribution, etc. Here again the dilemma is that charging the customers more than the marginal cost of using the infrastructure will lead to underutilisation of the infrastructure, and a loss for the collective of customers (and producers), and for society as a whole. When the infrastructure is already in place, the cost of using it is often relatively low, and charging the customers extra every time they are using the infrastructure, in order to recover the investment, will inevitably decrease the usage of the infrastructure, and may actually even decrease the total revenues for the owner of the infrastructure, thus giving a negative rather than a positive contribution to the coverage of the investment costs. Different solutions have been tried to solve the dilemma concerning traditional infrastructures. A common solution is to finance investments in infrastructure over the government budget. The users of the infrastructure will then pay for the infrastructure collectively, in their role as taxpayers; at the same time this financing regime will not deter any individual from using the infrastructure, once it is in place. This will lead to close-to-optimal usage of the infrastructure, assuming that the marginal cost of using it is zero or very low. If this is not the case, the infrastructure users should pay the marginal cost of using the infrastructure every time they use it. Another method of financing infrastructures is to form so-called Public-Private Partnerships (PPP). This method may reduce needs for the government to borrow money, and it may have advantages from the point of view of risk management, but it does not seem to solve the basic problem of preventing underutilisation of infrastructures because of too high prices for using them once they have been created. For example, the Arlanda Express railway to Arlanda Airport outside Stockholm is the result of a PPP-project, but the price of the train tickets is so high that most private persons prefer to take a bus, their own cars, or even a taxi to the airport, which creates more air pollution than necessary, a so-called external diseconomy. Information (and knowledge) exhibits the characteristics of a public good or a collective utility: nonrivalry and non-excludability. See Samuelson (1954). Non-rivalry means that consumption of the good by one individual does not reduce availability of the good for consumption by others. Nonexcludability means that nobody can be effectively excluded from using the good. From a holistic point of view (and as pointed out above) some ways of financing the production of a public good may lead to underconsumption of the good, once it has been produced and is available 22
for everyone. More generally, production and consumption of public goods are associated with socalled externalities. An externality occurs when an economic activity causes costs or benefits to parties who are not directly involved in the activity. See Pigou (1920) and Baumol (1972). Production, dissemination, and marketing Here we shall present a number of illustrative examples of production, dissemination, and marketing of intellectual goods and information-based products and services. Music: live and recorded The music industry was one of the first industries to discover (or rather not to discover) the new parameters and the new realities of the information economy as compared with the economy they had got used to. Thanks to their power over the composers and artists, and the monopoly created by authors’ rights, music publishers could continue to charge their customers high prices for recorded music, although market prices for reproduction and dissemination of electronic products approached zero thanks to the developments of information technology. When the market forces anyhow started to work through especially young people’s sharing of electronic products via the Internet, the music publishers responded by defensive and even repressive actions, making maximum use of taxpayers’ money through the legal system, augmented by private police forces. A more constructive response could have been innovative initiatives, turning the technical advances to their own advantage, rather than seeing them as threats to be defeated. The situation became absurd; it must be unique in history that an industry becomes the worst enemy of its own customers, at least on such a large scale. Music sharing and downloading via the Internet flourished, strengthened by the fact that the music industry voluntarily refrained from entering this potentially huge and profitable market. Even composers and artists revolted and made their work available free of charge on the Internet, getting free, self-amplifying publicity in return, making themselves attractive for profitable live concerts and other engagements; they sometimes even increased their sales of music recorded on traditional media like CDs. It should be noted that the revolting composers and artists were the same as those whose authors’ rights the hypocritical music publishers pretended to protect. It is true that they made everything to protect and defend authors’ rights – but they did this, not for the sake of the authors, but for their own comfort and wellbeing through excessive profits that they did not deserve, and actually never got, because of the sharp downturn in the sales of their traditional products. Another argument, often put forward by music publishers to defend the high prices for their digitally produced and reproduced products, is that it is very costly to market and promote music, especially music made by relatively unknown creators and performers. Here again the music publishers only demonstrate that they ignore or oppose alternative marketing methods enabled by modern information technology. We will return to this issue in our discussion of new business models. This is not to say that all music publishers were evil and greedy. Some of them may only have been stupid and ignorant. Some music publishers explicitly defined information technology as being outside their core business; thus they failed to recruit talented and innovative information technology experts, who could have helped them to see the possibilities in the new environment, not only threats. Instead the spent money on non-productive recruitments of lawyers and private Internet detectives. Literature: books and journals
23
Publishers of literature have behaved in much the same way as publishers of music, which may be natural, since both music and literature are intellectual products with well established technologies for reproduction, dissemination, and marketing. The new information technology has not been equally threatening to publishers of literature as it has been to music publishers. Printed books and journals still have certain advantages from a customer’s point of view, which are not so apparent for traditional physical media used in the music industry (vinyl records, magnetic tapes, and compact discs). Even if the publishers of literature have not been so dramatically challenged by new technology and new forms of reproduction and dissemination, they have, like their colleagues in the music industry, missed many opportunities of exploiting the new technology in a positive way, rather than applying defensive and repressive measures. For a customer of literature, especially non-fiction literature, it is not always easy to choose between a traditional medium (e.g. a printed book or a journal) and an electronic medium (e.g. an Internet website or an electronic document downloaded from the Internet). Many of us still prefer printed books and documents in order to get an overview and to browse. On the other hand, electronic media are easier to carry, search, and combine with other sources; for example, few books, if any, have tables of contents and indexes that may compete with the free-text search capabilities automatically available for electronic documents. For scientists and social researchers it gives prestige and academic qualification to get articles published in well regarded printed journals. On the other hand, this somewhat archaic publishing procedure usually takes long time, often several years, and in the end the published article becomes less available to professional colleagues and other potential readers than an article made available free of charge via the Internet. An interesting feature of scientific journals is that most of the expertise necessary for the production of the journal is provided free of charge by the academic experts: authors, referees, and even the scientific editors; only the technical editors and the staff of the publishing company are paid. At the same time the customers of the journals, the readers, are often the same as the authors and scientific editors, but as customers they have to pay. It should also be noted that articles submitted to an electronic journal, made available free of charge on the Internet, could easily be subject to the same rigorous reviewing procedures as articles submitted to a traditional journal, printed and disseminated by a traditional publisher. Official statistics Official statistics are statistics about different aspects of a society (economic, social, environmental, etc), typically produced, compiled, and published by national statistical agencies or international organisations like the United Nations, OECD, the World Bank, the International Monetary Fund, Eurostat, etc. The production of official statistics is typically financed by taxpayers via government budgets. Statistical surveys of this nature typically require scarce expertise for the design work, and expensive data collection operations for the production. However, once the resulting statistical results are available, they will be useful and valuable for a wide range of users in society: policy-makers, public and private analysts and decision-makers, researchers, students, etc, not forgetting the public at large. Nevertheless, noone of these users alone would probably have the resources or incitement to produce the statistics, unless they were collectively financed; collective financing via the government budget is a rational solution in this case. 24
It should be noted that what has just been said about design and production of official statistics does not necessarily apply to reproduction (printing) and dissemination of the produced statistics. As long as traditional information technology was used (printing etc), each copy produced and disseminated involved a non-negligible extra cost, which seemed fair to recover from the actual user of that copy. Thus statistical publications were typically sold and distributed for a fee, rather than given away for free. Ideally the price of the printed copies should be set to cover the costs of reproduction and distribution, nothing more, since all preceding steps in the process had already been paid for by the taxpayers via the government budget. Nowadays statistical agencies have many technical modes and channels to choose from for making their statistical outputs available to their customers, and the customers can choose between many alternatives for retrieving and accessing the statistics. Naturally, methods based on modern information technology, like computerised databases made available via the Internet, gain in popularity all the time, since they are flexible, user-friendly, and efficient. Printed publications are still in demand, especially analytically oriented publications, containing much more advanced contents than mere figures and short explanations. With the new information technology available, the costs for reproduction and dissemination of statistics in electronic form have gone down to almost zero. Nevertheless many statistical agencies continued to charge their customers for the electronic outputs in much the same way as they had always done for the printed publications, forgetting or deliberately hiding the fact that the values of the cost parameters in the electronically based reproduction and dissemination process were quite different from the corresponding parameter values applicable in a traditional printing and distribution process. Some agencies had got used to seeing their marketing and sales departments as revenue-making businesses, and because of bad accounting practices they sometimes even believed that these businesses were making profits, which they almost never did (rather losses), and if they had made profits, that would have been harmful, since it would have meant that the publications had been wrongly priced, and the too high prices would have led to an underconsumption of valuable statistics, and an overtaxation of taxpayers/users of statistics. By now most national statistical agencies and most international organisations (with some notable exceptions like the OECD) have changed their pricing policies in such a way that electronic information products are made available to everyone free of charge in standardised forms, whereas printed products are still being charged for. When looking at the situation, many agencies discovered that the cost of charging was typically by far the most significant cost in a modern, electronically based dissemination process, which made it ridiculous to charge in the first place. Some agencies may also undertake extra tasks to be paid for by the customer, e.g. making analyses and presentations tailored to special needs, but often such needs are left to be met by private actors on competitive markets. Having introduced the new pricing policies, statistical agencies have noted an explosion in the use of official statistics, most likely to the benefit of all parties concerned: private businesses, public administrations, researchers, interested citizens – economic as well as social and democratic interests; well informed citizens and politicians should hopefully lead to a better society in all respects and for all concerned. Those few agencies and organisations which still charge for their electronic information products have a few typical arguments. One of them is that they may lose revenues from printed publications if these become less in demand because of the free availability of electronic products. First of all, this may not be true at all. The increased visibility of official statistics as such, thanks to the free availability of the electronic products, will also increase the exposure of the printed publications to audiences that did not know that these publications existed, and who may sometimes find it useful 25
to buy a printed publication for certain purposes, rather than relying entirely on electronic outputs – traditional printed publications still have certain advantages. Secondly, even if the sales of printed publications went down, the decrease in revenues should be balanced by a corresponding decrease in costs – otherwise the printed publications have been overpriced, in contradiction with the laws of a well functioning market economy. Geographic data: coordinates and maps The area of geographic data and information systems (GIS) is an area where, in some countries, the pricing policies of governments and government agencies have lead to a striking underutilisation of information resources which are strategic for economic growth and private welfare. It has also often led to an inefficient duplication of work, when both private and public actors have found that they cannot afford to use the geographic data provided by the government agency responsible, and instead have to do their own data collection, or use less accurate data from other sources. Conclusion from the examples A very important conclusion from the examples stated above is that producers and customers of intellectual products and information products and services in the information economy are in serious need of new business models, making it possible to form profitable and viable businesses, while at the same time allowing the customers to reap the benefits of the new opportunities offered by modern information technology, without having to pay more than necessary for these benefits. In the following two sections we shall discuss what a business model is, and what kind of business models could be suitable for actors in the information economy. What is a business model? The term “business model” has different meanings in the literature – some broader, some more narrow in scope. In a narrow sense, a business model is a model for how to earn money from a business, or, expressed in a slightly more elaborated way, how to design the business so as to generate enough money to make the business sustainable in the long run. In a broader sense, a business model is a model of the business as a whole, a model of all important aspects of a business, e.g.
value aspects: vision, goals, strategies, customers, products, etc process aspects: how the business is organised in order to produce value for the customers in a profitable way (or within a budget) information aspects: what information the processes need, and how basic concepts used in the business are defined and related to each other
Business models that combine different perspectives may be very useful for analyses of businesses and preparation of changes. See Sundgren, Tolis, and Steneskog (2004). In order to start a business and, even more importantly, to stay in business, we need to be able to answer questions such as: 1. 2. 3. 4. 5.
In which business are we? Which are the important concepts in our business? Who are our customers, and what kind of value do we create for these customers? Which is the vision of our business, and which are our strategies and goals? How can we earn money to make our business viable and profitable? How can we design, organise, and execute our business processes so as to achieve our goals, and create value for our customers? 26
If we can answer these questions satisfactorily, we may have a feasible business model. We may have to iterate between the questions above a number of times, modifying different aspects of the business model, before the whole model is consistent and, hopefully, optimal. Which business are we in, and how do we define it? The answer to this question may not always be obvious. We may benefit from reconsidering which business we actually are in. Let me give two examples. Example 1. Up to the 1930’s there were companies making good business by distributing ice to retailers of meat and other heat-sensitive products. Then came the refrigerators, and the ice distributors went out of business. They regarded themselves as being in the ice business. Had they redefined themselves as being in the distribution business, they might have survived, because they had gained excellence in managing distribution networks in such a way that they could reach many shops in a short time. Example 2. American Airlines developed early a very good computer-based flight and seat reservation system that was adopted by the travelling industry as a whole. It became a necessity for airlines to appear on the first screen of the American Airlines system. After some time American Airlines earned much more from the information system than from flying airplanes, in which business they actually made losses. Guess what they did. It is interesting to note that in these examples, and many others, the companies concerned could benefit by taking a broader look at their business, including aspects belonging to the information economy. Both distribution networks and flight reservation systems are information systems. In the first example it was probably a paper-based information system, or only an ad hoc system relying on people’s experience. In the second example it was certainly a computer-supported information system. The examples also show that the information economy may not be separate from the traditional economy of (material) goods and services. Information goods and services may very well be an integrated part of a more traditional business. However, even in such cases the business as a whole may benefit a lot from recognising the information aspect of the business explicitly and in its own right. One may compare with the earlier transition of companies producing and selling physical products (like cars) into companies producing and selling packages of physical products and accompanying services; today you buy a car together with a package of guarantees, insurances, and other services, and both you as a buyer, and the car manufacturer as the seller, consider all parts of the package as important. In addition to businesses where information is regarded as an important tool or complement to material products and services, there is a growing number of businesses where information is in focus, both as the product and as a tool for producing and communicating the product. In fact such businesses have existed for a long time in the media industry: books, newspapers, radio, TV, music, film, etc. Tragically the media industry has come to associate themselves so much with the material tools and traditional distribution channels that they lost focus on their core business, to provide contents to their customers, and even neglected and opposed the rapidly emerging and very efficient new tools and channels based on modern information technology. Most of the companies in the media industry still do not seem to understand how to adapt in a positive and constructive way to the opportunities offered by the information economy based on modern technology. Instead of exploiting the opportunities, listening to their customers, rationalising their business processes, and 27
pricing their products in accordance with the laws of a free, capitalistic economy, they call for protection and harmful regulations of free competition, prosecute their customers, and give up large shares of their markets to innovative companies outside the traditional media industry, many of which are actually very serious and successful. When we discuss questions such as “which business we are in”, and all the important aspects of this business, as listed above, we need to be careful with definitions of the concepts and terms we are using. We must be sure that we all understand ourselves what we are talking about, and furthermore, we must be sure that we understand each other. Who are our customers, and what do they expect from us? It is absolutely essential in all kinds of businesses to know, who are your customers, how you reach them, and what they really expect from you – not what you think they expect from you. In the information economy you may have to reconsider these questions quite often, because modern technologies offer new opportunities all the time, and your customers will certainly expect you to take advantage of these technologies, improving the information products themselves, improving the communication channels, improving the price/performance ratios, etc. And do you know who your final customers really are? Sometimes it is the customers’ customers you should focus on. In some branches intermediaries may disappear or become less important. For example, book readers and potential bookreaders may not visit bookstores or libraries any longer – they expect to be able to find and download books (and many other types of media products) from the Internet, in a way that is convenient from their perspective, and at a reasonable price. A good thing with the information economy is that it is very easy to get a lot of useful feedback from the customers, e.g. by studying their behaviour, when they move around on an Internet website, by systematically analysing their purchasing patterns, by explicitly asking them for their comments, by making it easy for them to file complaints, by handling such complaints as a top priority, etc. If the product you provide is an information product, it may be relatively easy to modify it, so you may not have to be so anxious if the first version of the product is not so successful as you had hoped after investigating the potential market. It is not easy for a potential customer to describe the characteristics of an “ideal” product, and to quantify how eager she would be to actually purchase this product at different prices. But after you have launched an information product via the Internet, you will get feedback very quickly, and then you should be prepared to respond as quickly to the feedback by modifying the product and the services around it, if necessary. Business models for the information economy Now we shall turn to a more concrete discussion about how to create viable business models for companies in the information economy. According to Zimmermann (2000), in order to create business models for the digital economy, it is necessary to analyse the context from a company or industry perspective. Zimmermann states four basic questions, which have to be asked:
Structures: What is the future structure of a certain industry? Processes: What will the value creation processes look like ? Products: What are the basic customer’s needs and the respective product/service elements in order to serve them? Infrastructure: Which services are necessary for a specific marketplace serving for a distinct business community?
Here we shall add two issues to be discussed: 28
New goal structures – beyond profit maximisation New marketing strategies
See also Selz (1999) and Timmers (1998), referred to by Zimmermann (2000). New ways of structuring businesses and processes When analysing the structure of a business and its processes, one may discover that the structures that used to be natural and efficient are no longer obviously best in the information economy, with the new possibilities offered by information and communication technology, especially the Internet. We will look at a couple of examples. E-commerce Consider a traditional mail-order business. It has a number of main processes, for example:
marketing (advertising etc) customer-oriented order process (by surface mail and/or telephone) the delivery of goods ordered from a warehouse warehouse management the supplier-oriented order and delivery process invoicing and payment collection
The mail-order company may use subcontractor for certain subprocesses, but in general the processes in a traditional mail-order business are rather tightly integrated, and kept under close control by one and the same company, the mail-order business itself. If a traditional mail-order company transforms itself into e-commerce, it may consider to structure its business in a different way. For example, it may loosen the couplings between the above-mentioned processes a bit, and even outsource or sell some of the processes to independent companies, replacing the tight integration between the processes with a loosely coupled system of processes, managed by different companies interacting in some kind of partnerships with one another. An e-commerce company may define its core business to be the directly customer-oriented and highly interactive processes of marketing and order-taking. It may focus entirely on these processes and leave the other processes to business partners, intervening in these processes only if a customer experiences some problem with them, for example, if the delivery or payment process fails for some reason. The goods may actually be delivered from different warehouses around the world, the payments may be collected via bank cards, etc. Thanks to the speed, low costs, and ubiquity of information systems, the physical systems of the business (the warehouses etc) may be organised in a more complex way, so as to minimise the costs of storage and transportation. It does not really matter any longer where in the world the customers are, and where the e-business interacting with the customer has its physical headquarters – if anywhere. A discussion of some aspects of this kind of business restructuring can be found in Gaudeul and Jullien (2007). When analysing and reconsidering the processes of a business, it may be useful to consider the rich literature on business modelling and business process reengineering, e.g. Hommes (2004), Sundgren, Tolis and Steneskog (2004), Malhotra (1998), Davenport (1993). Authoring and publishing An authoring and publishing business contains some typical processes:
29
One or more authors (writers, composers, artists, knowledge workers, etc) create a piece of art or knowledge Intermediaries (publishers etc) evaluate, publish, and market the works of the authors, and collect revenues, some of which are given back to the authors
Over time, it seems that the owners of the intermediary processes (publishers, agents, etc) have more and more become the main players in authoring and publishing businesses, whereas the authors have become subcontractors to the intermediaries, rather than the other way around, as would seem to be more natural and fair. After all, without the authors, there would be nothing to publish and sell, whereas the authors could possibly do without the intermediaries. Can they? With the rapid penetration of the Internet as an inexpensive, efficient, and interactive channel of communication, it has suddenly become possible for authors to find their audiences and customers directly, without intermediaries, and for potential audiences and customers to find the works of the authors in a very efficient and inexpensive way. There is good reason for both the authors, on their part, and the intermediaries, on theirs, to reconsider their respective businesses. It is no longer evident that the two businesses should be so intimately linked to each other, as they have been in the past, and it is definitely not evident that the authors should be subcontractors of the publishers, rather than the other way around. The authors may very well find that they can do fine without the traditional intermediaries. Creative as they usually are, they have already found a lot of new, Internet-based tools to market their products, and meet their audiences and customers. They discover that they produce, or may produce, a whole portfolio of related products, which may very well support each other, and do this in new ways, with the help of the new technology. For example, a musician may see his digital works as advertisements for live concerts, more than the other way around, and a scientific writer may see his books as just one communication form of the knowledge he produces – other forms being lectures, courses, consultancies, etc. New goal structures – beyond profit maximisation The last example above, the scientific writer or researcher, leads us to the next issue that becomes very interesting in the information economy, the issue of the goals and objective of a business. A researcher very seldom expects to make a profit from publishing books and articles. In fact, articles submitted to scientific journals are never paid for; neither is the tedious and highly qualified peerreviewing that researchers are expected to do as a part of their scientific careers. On the other hand, the publishers of traditional scientific journals will certainly not publish, unless they will make a profit from the publishing, and without blushing they will sell their products to the same authors (possibly through their universities) who have provided them with their articles free of charge. Even if an author of a scientific book will get some royalty, it will usually correspond to a very low hourly compensation for the author’s creative work. Obviously, researcher have other goals than profit maximisation when they document and publish their research results. They need to document their results in order to merit themselves for academic positions, and apart from this, they are usually genuinely interested that as many other researchers as possible should note and appreciate what they have achieved. Thus the researcher attains selffulfilment and, sometimes, fame and glory. For the publisher, on the other hand, a researcher’s success is only valuable if it leads to profits for the publisher, which is a low priority goal for the researcher. In fact, the researcher may become 30
much faster and much more widely read, acknowledged, quoted, and recognised as a researcher, if she publishes herself through open access journals and open archives, available free of charge via the Internet. We will return to this below. Thus there are obvious goal conflicts between authors and publishers. In the traditional economy, the authors and the publishers did not have much choice than coexisting in the same business, with tightly integrated processes. In the information economy, and with todays penetration of the Internet, the authors have many alternatives to the traditional dependence on publishers, and the publishers have to review their business in creative ways in order to find new roles for themselves, including new offerings that really add customer value to the products of the authors, and to do this in ways that the authors cannot easily or efficiently do themselves. New marketing strategies It is not a new idea to market a product by giving it away for free. Anderson (2008) tells how King C. Gillette after trying an endless number of marketing gimmicks without success, finally found a successful strategy for boosting the sales of his innovative safety razor with disposable thin metal blades: “Razors were bundled with everything from Wrigley's gum to packets of coffee, tea, spices, and marshmallows. The freebies helped to sell those products, but the tactic helped Gillette even more. By giving away the razors, which were useless by themselves, he was creating demand for disposable blades. A few billion blades later, this business model is now the foundation of entire industries: Give away the cell phone, sell the monthly plan; make the videogame console cheap and sell expensive games; install fancy coffeemakers in offices at no charge so you can sell managers expensive coffee sachets.” However, before recent developments in the information economy, practically everything "free" was really just the result of a so-called cross-subsidy: you get one thing free if you buy another, or you get a product free only if you pay for a service. In the modern information economy a different situation has emerged, creating conditions for new marketing strategies. The new strategies are not based on cross-subsidies — the shifting of costs from one product to another — but on the fact that the costs of products themselves, the information products, are falling fast and coming very close to zero. In an economy where the cost of a product is not negligible, you may give away products, or give heavy discounts on them, only if you sell many more at full price, or use cross-subsidies as described above. In contrast, in the information economy, where the cost of some products are really very close to zero, you only have to sell very few products at a non-zero price, in order to be able to give away most products, maybe 99% of them, for free. The situation is reversed in comparison with the situation in a traditional economy, where you have to sell much more than 1% at a non-zero price. Earning money from information businesses Many traditional businesses in the media industry have learnt the hard way that it is not so easy to earn money from information products in a world based on modern information technology, at least not in comparison with how it used to be, when not only the creators of successful products (literature, music, etc) could get decently paid for their efforts by royalties generated by the sales of physical products used for distributing their work, but where a large number of other business people and others (for example heirs) somehow associated with their work could make a good living on overhead charges included in the prices of the material products then needed to carry the immaterial work of authors and artists. 31
The main reason why this old system for compensating and overcompensating some people and companies in the media industry could survive so long, was that the marginal cost of producing extra copies of the material carriers of the immaterial work (like printed books and – to a lesser extent – CD and DVD records) were really so high that a certain overhead percentage could rather easily be added to the price without distorting the market economy mechanisms completely. But when no material carriers are needed, and when the marginal cost for downloading extra copies of the immaterial work are very close to zero, for both the producer and the consumer, the situation becomes completely different. Even the very introduction of any kind of charging mechanism at all, even electronic, introduces a very high percentage increase in the overhead costs. It will often simply cost too much to charge, at least it will cost so much that it severely distorts the normal forces of a market economy – people will abstain from such products, or they will find satisfactory substitutions, e.g. by “borrowing” or sharing electronic copies from each other via BitTorrent or equivalent systems, distributed libraries one could say. After all, borrowing via public libraries used to be legal and free. There is a need, of course, to develop business models, where authors and performers of useful and demanded information products get paid decently for their work. At the same time it does not seem reasonable that authors and performers (and their heirs) should earn money when they are not working. A successful football player has to play in order to earn money; he does not obtain royalties for his performances after he has stopped playing or even died. Information services as infrastructure services From an economic point of view it is useful to compare information services with services made available by an infrastructure. Up to now infrastructures have typically been “hard” (like roads, bridges, transmission networks). Knowledge bases and bases of immaterial works made available via the Internet may be regarded as a soft infrastructure, whereas the Internet itself is a hard infrastructure. In order to maximise the total benefits in society of an existing infrastructure, one should not charge the users of the infrastructure for more than the marginal cost of using the infrastructure, when they use it. Charging them less than the marginal cost of usage would, on the other hand, mean subsidising the usage and should only be done for very clearly defined purposes or reasons. One reason may be that the marginal cost of a single user’s use of the infrastructure is so small that the cost of charging the users individually for their marginal use would be much higher than the cost of the usage itself. The problem then is how the development costs and other costs not directly related to the usage of the infrastructure should be financed. Some possibilities are:
taxes flat fees paid by subscribers to the service at certain time intervals payments from buyers of other products and services, who indirectly benefit from others using the infrastructure, e.g. businesses whose offerings become more visible or available to potential customers using the infrastructure
The last alternative above is the alternative that has been so innovatively and successfully exploited by Google, an example that will be more carefully examined below. Already here it can be noted that
32
there are at least three parties involved in the Google business model, who have all gained very significantly from it:
Google itself (of course), making enormous profits The users of the Google search engine (getting good value for no money) The advertisers (getting very good value for less money than they pay for alternative marketing channels)
How can all three parties gain? There are two basic reasons:
Google launched an innovative and very efficient search engine, made it available free of charge, and thus attracted an enormously large audience, without even having to spend any money on marketing its own product
Google offered advertisers a new and innovative channel that was simply more efficient in terms of value for advertising money than available alternatives; from Google’s point of view the channel was so efficient that they could price it very attractively for the advertisers, while providing the search engine free of charge to the general public, and keeping a substantial net profit for themselves
Thus the business model is based on two innovations: a technical one (the search engine) and an economic one (the new advertising channel). Furthermore, the two innovations were linked to each other in a way that was in itself innovative, a systems innovation with enormous synergy effects. The innovations have been further developed, and the synergy effects have been further exploited by Google, making more and more sophisticated use of automatically generated and collected statistics about user behaviour, which are intelligently used for offering advertisers more and more attractive and efficient advertising services. Decoupling financing from usage of infrastructure Somebody has to pay for everything. This is a simple truth that needs many qualifications, especially in the field of information economy. Different business models, all generating profit for a business owner, may vary significantly as regards, for example
prices per user and usages (depending on the volume of the usage, which is again strongly affected by the price)
prices for different products/services, when several products/services are bundled as discussed earlier (note especially the strong and very complex and cleverly designed interdependences that may exist between the bundled products/services, like the Google offerings to advertisers and information searchers, respectively)
An example of the importance of decoupling financing from usage is the introduction of citizen’s certificates that many countries are now undertaking. Several business models are possible here, and have been tried in different countries – with various results. For example, in Denmark the government took full central responsibility, both financially and otherwise, with a very fast penetration and acceptance of the certificate as the result, to the benefit of the whole society. In Sweden the government first tried to find a market-based solution through the banks, which did not work very well, and a new government will now try a different approach, with more similarities with the Danish model. 33
Bundled businesses Bundled (or combined) businesses are businesses where you combine two or more offerings to two or more populations of potential customers. Both the offerings and the customer populations may be quite distinct from each other, like they are in the case of Google. Bundled businesses have become very important in the information economy, but they have existed in other forms far back in history. For example, a traditional, printed newspaper typically relies on one offering to potential readers of their editorial contents (news, analyses, etc), and quite a different offering to potential advertisers. For both offerings you have a set of parameters that you may adjust, for example the price. For readers of editorial contents, you may have one price and one service package for subscribers, and another price and other distribution channels for buyers of single copies. The different offerings are linked to each other in ways that are important to understand and exploit to the benefit of the business (and the customers). For example, the more readers a newspaper gets, the more attractive it becomes for potential advertisers, especially if the readers belong to a segment of particular interest for particular advertisers. Example 1. Some years ago the Swedish entrepreneur Jan Stenbäck shocked the market of daily newspapers by offering a newspaper called Metro free of charge at all underground entrances in Stockholm. Referring to the model I just described, what he did was just to put one of the price parameters to an extreme, zero. Metro became profitable sooner than expected, and now the concept has been copied by several followers; some have succeeded, some have failed. Example 2. Ryanair is an example of similar entrepreneurship, based on combined offerings, in another type of business. The main business is (or at least seems to be) flying people between two places at a very low price, often close to zero. Other offerings are the marketing and selling of other products and services, especially products and services associated with travelling. Example 3. Google is of course the most outstanding example of a bundled business and has already been mentioned above. The offering in focus at the start was the Internet search service based on an innovative search engine and offered to the general public free of charge. This offering was bundled with an offering to advertisers. The success of the search engine was of course a major key to the commercial success of the advertisement offering. But it should be noted that the efficiency of the new advertisement channel (in terms of costs of reaching potential buyers and making them buy) was also very high in comparison with existing channels. This efficiency leap, which makes the new advertisement offering a “win-win” offering for both Google and its advertising customers, is again based on innovative information methodology. Actually it may be claimed to be a “win-win-win” situation, because the users of the search engine did not only find the information they were looking for, but also information (and offerings of advertisers) they did not know existed, and which they rather often find interesting and useful. Thus there are many synergies involved in the bundled offerings exploited by modern information businesses. If you get these mechanisms explained, they are hopefully not so difficult to understand, at least in principle, but in fact they have confused – and are still confusing – a big majority of business people grown up and trained in more traditional branches of the economy. It is important to make a distinction between business bundling, as described above, and crosssubsidies as discussed above. Cross-subsidies, especially those which are based on formal or de facto monopolies are regarded as harmful in a market economy; see for example Irwin (1997). Read more
34
Sundgren, B. (2010). Business models and authors rights in the information economy. International Journal of Public Information Systems. Vol 2010:2, pp 171-194. Sundgren, B. (2013e). Administration-centric e-governance. The chapter on Authors’ rights and copyright legislation. The open, net-based course E-society – evolution or revolution. Module 1. Introduction to e-society.
Entrepreneurship: Will e-entrepreneurs kill traditional entrepreneurship? Based on an article in Swedish by Kristofer Kalén (2013). Angry Birds, Instagram and Block. There is a long list of successful e-businesses where the entrepreneur behind it during a very short time has managed to establish a successful concept and at the same time make themselves a decent fortune. A classic entrepreneur is a creative person who works hard during a whole life to move their business forward all the time. Will the new, considerably faster e-road to success businesses and a lot of money have the side-effect that we shall not get any new IKEA, Volvo, or H&M in the future? Today's technology has been responsible for a huge development for virtually the whole of society. Developments have taken place globally and on all levels, not least when it comes to business activities and different types of trade. In several markets, conditions have changed completely, many times for the better, but in some cases for the worse, as seen from both consumer and business perspectives. A business person today has to be updated all the time, and have an organisation that can quickly shift and change along with demands. What has also changed radically in this rapid march towards an electronic world, an e-society, is the opportunity to be heard and seen rapidly over the whole world. Take a YouTube clip as an example. In just one day a popular video may have been seen by several million people. The band PSY with song Gagnam Style received in 2012 over a billion views within course of five months. The possibility to be able to reach out to so many people in an easy and fast way obviously generates new opportunities, and many of these are new business opportunities. YouTube is just one example of how quickly one may reach out to people in the digitised world. App Store and Android Market, Apple's and Google’s respective markets for downloading applications to their smartphone, are other examples. Here there is a daily ongoing warfare between application manufacturers for all users' attention. All want place the new "hit", at the top of the downloading lists for months, raking in huge sums of money, both from advertisements and from the amounts that users pay for the downloads. Let's zoom in on one company, a company whose application has been talked about a lot recently, and which has had the kind of success just mentioned. Not many people have heard about Rovio Entertainment Ltd, but basically everyone who has a smartphone has heard of, or even tried the game Angry Birds. Rovio is the company behind the game, the world's most downloaded iPhone application that is not free. Rovio launched the game in 2009. It became an incredible success story, and today, in 2013, analysts value the company at about 9 billion dollars. In comparison, a company like Electrolux, which has an international giant in household appliances for decades had in 2012 a market value of about 8 billion dollars. This makes you think about what it really is that explains the high market value of companies like Rovio. Do they own very expensive machines and other equipment? Do they have thousands of competent and attractive employees? Do they have a huge 35
turnover of money? Actually the answer to all these questions is “no”. Instead the biggest asset of these companies in an extremely hyped brand and a franchising business in the form of a mobile game. To get a picture of how valuable the trade mark of Angry Birds has become around the world, it can be mentioned that Disney has indicated an interest to base a whole film on Angry Birds. It does not end here. We can go ahead and peek at one of the world's largest companies, Google. The company was founded in 1998. For several years now, Google has been on the list of the world's 20 most highly valued companies. This means that the company, in about 20 years, has moved from a relatively simple idea to one of the world's largest companies. Before e-society this would have been a complete impossibility. For global companies that deal with "real products" and are now of the same magnitude as Google, a great majority have been around for at least 50 years, most of them even longer. Unlike in the previous Rovio example, Google provides of course a variety of useful services, but the fact remains that all parts of the company’s business is internet-based. Many older generation people might say that “Google – it is just a cloud.” Facebook is yet another example of the new type of companies, which “only” offer some web services, in the case of Facebook a social portal. Yet, in just a few years, Facebook has grown to an enormous organisation known over whole world. Mark Zuckerberg, a founder of Facebook, started the company in 2004, and today he is number 66 on Forbes’ list of the world's richest people. Pretty well done for a company less than ten years old. Could all these success stories of e-businesses to be a threat to more traditional entrepreneurship, resulting in production and trade of innovative physical products? Several studies have been done in recent years, investigating how entrepreneurs think and behave in different situations. Professor Sara Sarasvathy from the University of Virginia is one of those who have done research on this. Laureiro-Martinez et al. has made a completely different type of investigation but which also sometimes takes up similar questions. They argue, among other things, that entrepreneurs by nature are eager and like when things go fast. If they start a business and it does not succeed in five years, they often put the idea on the shelf and start something else instead. All opportunities that come with e-society is obviously a dream coming true if one likes when things are moving quickly. Both researchers and entrepreneurs agree that it has never been easier, with a good idea, to launch a large-scale enterprise in relatively short time, thanks to e-technology. The world is getting smaller and smaller, which in turn means that global trade will increase. By and large this is good. The danger lies in the fact that many founders of new businesses have similar personalities and think in the same way about business opportunities in e-society. This may make e-business more attractive and “traditional businesses” less attractive than before, which may pose a threat to innovative developments in businesses based on physical products and traditional trade. According to some researchers in entrepreneurship, for example Gerald Lidstone at the University of London, entrepreneurs may overlook the opportunities in businesses that are not based on, or have a major part of its business via the Internet. In addition to the factors that have already been mentioned, there is at least one other factor that is a powerful motivator for starting a business, and that is money. This has been confirmed by many studies, for example the study by Ernst&Young (2012), where they asked Swedish entrepreneurs about this. Although the factor of money not always first on the list, it was almost always mentioned as one of the most important factors. The opportunities in e-society to be heard and seen very 36
quickly across the world radically increase the chances to earn a lot of money from a good business idea. If you compare a business that after ten years is established all over the world with a business that after the same time is established in only two Swedish cities, the former business will almost certainly make more money than the former. This makes the already attractive e-business option even more attractive and appealing, even for many entrepreneurs from “the old generation”. Yet another positive factor for those who want start an e-business is the low market entry barriers, that is the small amount of capital and other resources needed start an e-business and get it running. In most cases an e-business does not require large premises or a lot of staff. On the other hand, the low entry barriers will also tempt many to start a company without having a particularly good business idea, or the necessary dedication, knowledge, experiences, and skills to operate a company in a good manner. Although traditional companies will not disappear completely within the next hundred years, we will probably see a reduction of start-ups engaged in “traditional” products and services in society. Ebusiness and e-society as a whole is definitely something that is here to stay. In addition it is also something that it is possible to earn big money from, and fast. However, there will continue to be a great demand for "traditional" products and services, and this will encourage people to start and run and innovate such businesses as well – often enabled, supported, and empowered by the Internet and other e-based technologies, methods, and procedures. In summary, we probably need do not be afraid of losing future counterparts of IKEA, Volvo and H & M.
Public procurement Openness and e-based public processes are powerful tools against corruption. Public procurement is an area where many countries have seen the potential of those tools, both as a weapon against corruption and nepotism, and as an instrument for lowering the costs in the public sector, especially when government agencies and administration use outsourcing and subcontracting instead of recruiting and managing their own staff to perform certain tasks. Public procurements are surrounded by strict laws and procedures on all levels of administration, from the international level (for example within the European Union) to national and local levels. These procedures have no doubt done a lot for decreased corruption and nepotism, not least on the local levels (municipalities), and they have also lowered the costs. But there are some problems that need to be tackled, for example:
The call for tenders and the selection criteria may focus too much on costs, partly because they are easy to measure. This has sometimes led to quality problems, for example in social care. Quality criteria are often difficult to formalise and measure.
The tendering processes are often felt to be bureaucratic and resource-consuming, especially for small businesses, who want to compete.
Because of these and other problems it has become clear that the legal frameworks and administrative procedures involved in public procurements need to be improved. In order to come to grips with the bureaucracy problems, the legal framework may have to be changed, but when it comes to secure the quality of the procured services, it is a matter for the public agencies and administrations to come up with better methods and critera for measuring and comparing quality, and to give more weight to important quality criteria in the tendering processes. 37
Despite some problems, like those just described, public procurements following strict legal frameworks and e-supported procedures are here to stay, and businesses that want to compete for public contracts have to adapt to this, streamlining their procdures for the preparation and submission of tenders. For more information about public procurement and e-procurement, see Sundgren (2013e).
Business Intelligence and Big Data References: Strain (2013), Kernochan (2013), Schiff (2010). Business Intelligence and Big Data are two related concepts. Both have to do with the analysis of data as a basis for decision-making. Data mining and Text mining are other related concepts. The analyses will often use statistical methods with the aim of getting good overviews, discovering patterns, identifying correlations between variables, etc. The results of the analyses are often presented in tables and visualised by means of graphs and animations. Here we shall focus on potential benefits that businesses may get by using Business Intelligence and Big Data. What is Business Intelligence? Business Intelligence: http://en.wikipedia.org/wiki/Business_intelligence Business intelligence (BI) is a set of theories, methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information for business purposes. BI can handle large amounts of information to help identify and develop new opportunities. Making use of new opportunities and implementing an effective strategy can provide a competitive market advantage and long-term stability. BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing (OLAP), analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics and prescriptive analytics. Though the term business intelligence is sometimes a synonym for competitive intelligence (because they both support decision making), BI uses technologies, processes, and applications to analyse mostly internal, structured data and business processes while competitive intelligence gathers, analyses and disseminates information with a topical focus on company competitors. If understood broadly, business intelligence can include the subset of competitive intelligence. For more information about technical and methodological aspects of Business Intelligence, see Sundgren (2013f). Potential benefits of Business Intelligence According to Strain (2013): 38
“Business intelligence usually refers to computer software and other tools that collect all sorts of complex business data for a company and condense it into reports. The collected data may focus on a specific department, or give an overall view of the company's status. Large corporations with huge amounts of data to process are most likely to benefit significantly from business intelligence, though smaller concerns use it, as well. Business intelligence may help a company identify its most profitable customers, trouble spots within its organization, or its return on investment for certain products. Although a companywide business intelligence system is complex, costly and time-consuming to establish, when implemented and used correctly, its benefits can be significant. Fact-Based Decisions. Once a company-wide business intelligence system is in place, management is able to see detailed, current data on all aspects of the business -- financial data, production data, customer data. They can read reports that synthesize this information in pre-determined ways, such as current return on investment reports for individual products or product lines. This information helps management make fact-based decisions, such as which products to concentrate on and which ones to discontinue. Improves Sales and Negotiations. A business intelligence system can be a valuable asset to a company's sales force because it provides access to up-to-the-minute reports that identify sales trends, product improvements or additions, current customer preferences and unexplored markets. Detailed and current data is also a valuable backup to negotiations with suppliers or other vendors. Eliminates Waste. A business intelligence system can point out areas of waste or loss that may have previously gone unnoticed in a large organization. Since a companywide business intelligence system works as a single, unified whole, it can analyze transactions between subsidiaries and departments to identify areas of overlap or inefficiency. According to the CIO website, in 2000 "with the help of [business intelligence] tools, Toyota realized it had been double-paying its shippers to the tune of $812,000." Identifies Opportunities. Business intelligence can help a company assess its own capabilities; compare its relative strengths and weaknesses against its competitors; identify trends and market conditions; and respond quickly to change -- all to gain a competitive advantage, according to the Journal of Theoretical and Applied Information Technology. It helps decision makers act swiftly and correctly in response to opportunities; helps the company identify its most profitable customers, as well as potentially profitable customers; and assess the reasons for customer dissatisfaction before it begins to cost them sales. According to Schiff (2010): “Ten Benefits of Business Intelligence Software Experts explain how business intelligence solutions can help companies be more efficient, spot areas for cost savings and identify new business opportunities. Over the last five years, a growing number of companies have invested in business intelligence software to help them centralize, better access and get a better understanding of key business metrics such as sales and to predict future performance. The economic downturn of the last few years slowed the growth of business intelligence (BI) software sales somewhat, but the sector still managed to grow during the recession, as companies 39
were eager to make the most of limited resources with a BI solution that could help them be more efficient, spot areas ripe for cost savings and identify new business opportunities. With a modest recovery underway, companies have even more need to make the most of their resources and turn mountains of data into opportunity. Business Intelligence Benefits Here are 10 ways business intelligence software can help your business: 1. Eliminate guesswork: "Running a business shouldn't be like gambling," said Ken Dixon, executive vice president of marketing at Kogent Corporation. "Far too often, executives must rely on 'best guess' and 'gut feel' decisions as they attempt to steer their companies into the future. They do this because their business data lacks any structure to allow them to make truly informed choices. Business intelligence can provide more accurate historical data, real-time updates, synthesis between departmental data stores, forecasting and trending, and even predictive 'what if?' analysis," eliminating the need to guesstimate. 2. Get faster answers to your business questions: "BI users can quickly get answers to business questions, rather than spending hours reading through volumes of printed reports," said Wende Cover, director of strategic marketing at MicroStrategy. 3. Get key business metrics reports when and where you need them: Today, many business intelligence software vendors are making it possible for users to access key business metrics, reports and dashboards on mobiles devices like their iPhone, iPad, Droid or BlackBerry, giving sales and marketing people access to critical business information on the fly. 4. Get insight into customer behavior: One of the great benefits of business intelligence software is it allows companies to gain visibility into what customers are buying (or not), giving them "the ability to turn this knowledge into additional profit" and retain valuable customers, said Mike Meikle, CEO of the Hawkthorne Group, a boutique management and information technology consulting group that advises companies on business intelligence tools. 5. Identify cross-selling and up-selling opportunities: "Business intelligence software allows firms to leverage customer data to build, refine and modify predictive models [that help] sales representatives to up-sell and cross-sell products at appropriate customer touch points," said Mohit Joshi, vice president and global head of the Sales, Banking and Capital Markets Practice at Infosys Technologies. 6. Learn how to streamline operations: "With detailed insights into business performance, organizations can easily see where they need to make changes to streamline operations," said Cover. 7. Improve efficiency: "Many companies waste significant time hunting for data from within various departmental data sources which they need to help understand what is going on in their business," said Dixon. "Then if they are lucky enough to find the information they want, they then need to convert, merge and report on if effectively, communicate opinions about it internally, discuss its accuracy, etc." Using business intelligence software, however, all the information is centralized and can be viewed in a dashboard or turned into a report, saving enormous amounts of time and eliminating inefficiencies. 40
8. Learn what your true manufacturing costs are: Business intelligence software can give users greater insight into manufacturing costs and the ability to adjust production on the fly for greater profitability, said Meikle. 9. Manage inventory better: Business intelligence software can help you "order the right amount of inventory at the right time so that customers receive their products when they need them," and your business doesn't bear the cost of stocking excess inventory, noted John Krech, the president and founder of ePhiphony. 1. See where your business has been, where it is now and where it is going: "Business Intelligence has been very successful at explaining what happened to the business over some defined period of time — for example, how many units were sold, through which store, in which geography, or by which customer segment," said Sid Probstein, CTO of Attivio. "These issues are now well understood, and so the next generation of competitive advantage comes from analyzing unstructured content to understand how and why these things happen. From simple contentbased metrics to sophisticated sentiment analysis, [business intelligence software can] provide a more complete view on customer and competitor experience and opportunities therein," and help executives plan for the future.” According to Smietana (2013): “5 Ways to Bring Self-Service BI to Your Small or Midsized Business Plenty has been written on empowering users with self-service business intelligence, but the topic is rarely viewed through the lens of small to midsized businesses grappling with limited IT resources and small budgets. Paradoxically, small and midsized businesses often have more to gain in terms of bottom-line impact of BI than larger Fortune 500 companies do. The rapid growth of visual analysis and data discovery BI tools is just the latest chapter in the evolution of business intelligence software from IT-centric platforms to self-service products, and it is a trend that has the potential to make a great impact on smaller organizations. While many small and midsized businesses scoff at the idea of implementing a BI solution, BI does not have to be big and scary. Many solutions today require no IT footprint and can be easily piloted in just one area of your organization. It just takes careful planning to introduce and implement BI properly. Let’s explore five ways you can bring self-service BI into your organization in an easy, cost-effective fashion. 1. Spreadsheets Can Show You Where BI will Be Most Successful Why is the humble spreadsheet still – by far – the most-used self-service BI tool on the planet? It’s because spreadsheets give users an extraordinary amount of control over the design and construction of reports, all from a convenient point-and-click interface. Once users gain “advanced” skills, they can use macros to automate routine processing. Pivot tables, filters, what-if analysis and a rich collection of statistical functions provide advanced users with a non-trivial amount of analytical fire power. What’s not to like? But the problems with spreadsheets are well-documented. Spreadsheets containing confidential data are often emailed around among employees, representing a potential data security breach. Spreadsheet formula syntax is not intuitive, making it difficult to find and debug errors. Macros, pivot tables and links to other spreadsheets are fragile and easily broken. Spreadsheet data can be typed 41
over and changed so it is subject to errors. In the end, basing important business decisions on spreadsheet analysis can be risky. Many BI practitioners consider spreadsheets to be “the enemy.” But if you are looking for a good place within your organization to start with BI, look for the people and departments that exhibit heavy use of spreadsheets. These are your “data champions”: employees and departments who are hungry for data analysis and visualization solutions and who are already using spreadsheets as a proxy for self-service reporting. They probably already know the source systems where the raw data exists, the schedule by which it gets updated and the format of the reports or dashboards they need to do their jobs better. They are the ideal first users of a BI solution. Business intelligence is useful for these data champions because it provides more secure and reliable business decision support. The trick is that the BI solution must be intuitive and simple to use, like a spreadsheet. If more self-service BI products were as easy to learn and use as spreadsheets, BI adoption rates would be far higher, especially in smaller organizations that lack in-house training and support staff. 2. Demystify BI with Purpose-Built Applications In any organization, there are departments with cultural and practical barriers to adopting new tools. For example, finance takes great pride in its spreadsheet ninja skills and will naturally fall back to this tool rather than deploy a new one. And financial software systems are so entrenched in the daily operation of a business that introducing new systems or replacing old ones can seem as difficult as performing open-heart surgery on a marathoner in the middle of a race. For organizations in which BI implementation seems especially daunting, deploying a purpose-built BI application can provide an easier entry into the technology because it can provide immediate benefits to one area of the business without disrupting existing systems. Once departmental users view the new tool as a productivity enhancer – rather than a threat or disruption – adoption rates tend to rise dramatically. It is wise to look for a well-thought-out interface and focused functional scope. Noted social psychologist Roy Baumeistercoined the term “decision fatigue,” which humans experience when challenged to make too many decisions in a fast-paced environment. Interestingly, people experience this condition regardless of the magnitude of a particular decision. Whether or not to drill down into a particular dashboard metric can, surprisingly, raise the same level of mental stress as making a major personal financial decision. Bottom line: The fewer decisions our overtaxed brains have to make to complete a task, the more likely we are to successfully complete our assigned task. Successful, purpose-built applications can bring the benefits of self-service BI to the end user by presenting fewer menu options, a more problem/resolution-focused interface and a familiarity of the subject matter for users. Effective self-service BI is not guaranteed from any particular tool, application or platform. When BI providers pay attention to the details of application design, it pays dividends in terms of users’ productivity increases and clearer decision-making. 3. Just Say “No” to the Data Warehouse This is an admittedly provocative topic, and I expect plenty of readers to express opinions to the contrary. But too many small and midsized organizations have denied themselves the benefits of BI because conventional wisdom says that building a data warehouse is a mandatory first step. That premise has been, and will continue to be, demonstrably false.
42
Many excellent BI tools have flexible ETL capabilities that offer an alternative to building a data warehouse. Foregoing the data warehouse can shave time, cost and complexity off the implementation, while still delivering BI results. With exponentially growing volumes of unstructured and streaming data making the data warehouse value proposition increasingly questionable, it’s time to move beyond this sacred cow. A truly versatile BI platform should be able to create BI-optimized data structures regardless of whether a data warehouse exists or not. 4. Broaden Your BI Mind Beyond BI lies information delivery. Traditional BI delivers numbers, dashboards and reports, but does not tell users what to do with this data. Information delivery expands BI’s utility by including not just data, but other content needed to convert insight into action. These can include context-relevant documents, presentations, videos and alerts. Mobile BI is an excellent example that demonstrates this new paradigm. A BI-based sales enablement tool can provide a field rep with metrics on inventory, stock-outs, promotions and incentives as well as sales scripts, sell sheets, product videos and other collateral that specifically target a particular class of customers. According to the “Wisdom of Crowds Mobile Computing/Mobile Business Intelligence Market Study,” published by Dresner Advisory Services LLC, three times as many small organizations indicated that mobile BI is a critically important function to the business compared to large organizations. Howard Dresner, lead researcher, president and founder of the Nashua, N.H.based analyst firm, said, “When you’re a small organization, you have to garner as many competitive advantages as you can.” 5. Cloud and SaaS Keep BI Easy to Support and Affordable Cloud and SaaS-based deployment options have arguably made self-service BI an affordable reality for more small and midsized organizations than any other innovation. A monthly subscription and reduced demand on internal IT resources can lower entry barriers for decision-makers who realize they need BI to remain competitive yet balk at the price of implementation. As the BI user base grows, cloud or SaaS deployments scale up, with all of the heavy lifting left to the BI vendor and its designated SaaS infrastructure provider. With a SaaS-based BI deployment, customers can access the functionality found in a vendor’s onpremise solution. The co-location facility hosting the vendor’s physical servers will employ security, backup and failover practices and allow high availability and 24x7x365 access. The servers at the colocation facility can be configured to optimize each customer’s performance and storage needs. For customers concerned about sensitive data, a SaaS-based vendor should be able to guarantee the physical location of their data. Customer requirements such as availability, throughput, concurrent users and anticipated data volumes should be explicitly addressed in the vendor’s SLA. Conclusion While challenges remain, they are continually being addressed by BI vendors. Self-service BI can quickly be implemented in small and midsized business environments, and it provides an easy entry point without the time or financial commitments required for a large-scale BI implementation. The confluence of information delivery, convenient cloud and SaaS-based deployment options and purpose-built applications have overcome significant obstacles that seemed daunting only a few 43
years ago. Best practices are equally important, though small and midsized companies use a slightly different playbook than their much larger corporate brethren that deploy enterprise BI solutions. The trends outlined here demonstrate that self-service BI is a reality for all who want the benefits it offers throughout their organizations, regardless of the organization’s size.” What is Big Data? Big Data: http://en.wikipedia.org/wiki/Big_data Big data is a collection of data sets so large and complex that it becomes difficult to process using onhand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualisation. The trend to larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to "spot business trends, determine quality of research, prevent diseases, link legal citations, combat crime, and determine real-time roadway traffic conditions.” Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process the data within a tolerable elapsed time. Big data sizes are a constantly moving target, as of 2012 ranging from a few dozen terabytes to many petabytes of data in a single data set. The target moves due to constant improvement in traditional DBMS technology as well as new databases like NoSQL and their ability to handle larger amounts of data. With this difficulty, new platforms of "big data" tools are being developed to handle various aspects of large quantities of data. Big data is difficult to work with using most relational database management systems and desktop statistics and visualisation packages, requiring instead "massively parallel software running on tens, hundreds, or even thousands of servers". What is considered "big data" varies depending on the capabilities of the organisation managing the set, and on the capabilities of the applications that are traditionally used to process and analyze the data set in its domain. "For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration.” In a 2001 research report and related lectures, META Group (now Gartner) analyst Doug Laney defined data growth challenges and opportunities as being three-dimensional, i.e.
volume (amount of data) velocity (speed of data in and out) variety (range of data types and sources)
Gartner, and now much of the industry, continue to use this "3Vs" model for describing big data. In 2012, Gartner updated its definition as follows:
"Big data are high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization."
If Gartner’s definition (the 3Vs) is still widely used, the growing maturity of the concept fosters a more sound difference between Big Data and Business Intelligence, regarding data and their use: 44
Business Intelligence uses descriptive statistics with data with high information density to measure things, detect trends etc.; Big Data uses inductive statistics with data with low information density, whose huge volume allow to infer laws (regressions…) and thus giving (with the limits of inference reasoning) to Big Data some predictive capabilities.
Scientists regularly encounter data processing limitations due to large data sets in many areas, including meteorology, genomics, connectomics, complex physics simulations, and biological and environmental research. The limitations also affect Internet search, finance and business informatics. Data sets grow in size in part because they are increasingly being gathered by ubiquitous information-sensing mobile devices, aerial sensory technologies (remote sensing), software logs, cameras, microphones, radio-frequency identification (RFID) readers, and wireless sensor networks. For more information about technical and methodological aspects of Big Data, see Sundgren (2013f). Potential benefits of Big Data According to McGuire et. al.: “Many observers, including the authors of this article, believe that Big Data is the new, new thing that will see some companies leapfrog others to become best in class. There are a few skeptics, but readers will find a compelling case and a toolkit for the smart use of Big Data in this article. Data are now woven into every sector and function in the global economy, and, like other essential factors of production such as hard assets and human capital, much of modern economic activity simply could not take place without them. The use of Big Data — large pools of data that can be brought together and analyzed to discern patterns and make better decisions — will become the basis of competition and growth for individual firms, enhancing productivity and creating significant value for the world economy by reducing waste and increasing the quality of products and services. Until now, the torrent of data flooding our world has been a phenomenon that probably only excited a few data geeks. But we are now at an inflection point. According to research from the McKinsey Global Institute (MGI) and McKinsey & Company’s Business Technology Office, the sheer volume of data generated, stored, and mined for insights has become economically relevant to businesses, government, and consumers. The history of previous trends in IT investment and innovation and its impact on competitiveness and productivity strongly suggest that Big Data can have a similar power, namely the ability to transform our lives. The same preconditions that allowed previous waves of IT-enabled innovation to power productivity, i.e., technology innovations followed by the adoption of complementary management innovations, are in place for Big Data, and we expect suppliers of Big Data technology and advanced analytic capabilities to have at least as much ongoing impact on productivity as suppliers of other kinds of technology. All companies need to take Big Data and its potential to create value seriously if they want to compete. For example, some retailers embracing big data see the potential to increase their operating margins by 60 per cent. BIG DATA: A NEW COMPETITIVE ADVANTAGE 45
The use of Big Data is becoming a crucial way for leading companies to outperform their peers. In most industries, established competitors and new entrants alike will leverage data-driven strategies to innovate, compete, and capture value. Indeed, we found early examples of such use of data in every sector we examined. In healthcare, data pioneers are analyzing the health outcomes of pharmaceuticals when they were widely prescribed, and discovering benefits and risks that were not evident during necessarily more limited clinical trials. Other early adopters of Big Data are using data from sensors embedded in products from children’s toys to industrial goods to determine how these products are actually used in the real world. Such knoiwledge then informs the creation of new service offerings and the design of future products. Big Data will help to create new growth opportunities and entirely new categories of companies, such as those that aggregate and analyse industry data. Many of these will be companies that sit in the middle of large information flows where data about products and services, buyers and suppliers, consumer preferences and intent can be captured and analysed. Forward-thinking leaders across sectors should begin aggressively to build their organisations’ Big Data capabilities. In addition to the sheer scale of Big Data, the real-time and high-frequency nature of the data are also important. For example, ‘nowcasting,’ the ability to estimate metrics such as consumer confidence, immediately, something which previously could only be done retrospectively, is becoming more extensively used, adding considerable power to prediction. Similarly, the high frequency of data allows users to test theories in near real-time and to a level never before possible. We studied five domains in depth—healthcare and retail in the United States, the public sector in Europe, and manufacturing and personal location data (the location data generated by the smart mobile devices many of us now carry) globally—and some broadly applicable ways of leveraging big data emerged. FIVE WAYS TO LEVERAGE BIG DATA 1. Big Data can unlock significant value by making information transparent. There is still a significant amount of information that is not yet captured in digital form, e.g., data that are on paper, or not made easily accessible and searchable through networks. We found that up to 25 percent of the effort in some knowledge worker workgroups consists of searching for data and then transferring them to another (sometimes virtual) location. This effort represents a significant source of inefficiency. 2. As organisations create and store more transactional data in digital form, they can collect more accurate and detailed performance information on everything from product inventories to sick days and therefore expose variability and boost performance. In fact, some leading companies are using their ability to collect and analyse big data to conduct controlled experiments to make better management decisions. 3. Big Data allows ever-narrower segmentation of customers and therefore much more precisely tailored products or services. 4. Sophisticated analytics can substantially improve decision-making, minimise risks, and unearth valuable insights that would otherwise remain hidden. 5. Big Data can be used to develop the next generation of products and services. For instance, manufacturers are using data obtained from sensors embedded in products to create innovative after-sales service offerings such as proactive maintenance to avoid failures in new products. 46
VALUE CREATED BY THE USE OF BIG DATA If the U.S. healthcare system were to use big data creatively and effectively to drive efficiency and quality, the sector could create more than $300bn in value every year. Two-thirds of that would be an 8 percent reduction in U.S. healthcare expenditure. In the developed economies of Europe, government administrators could create more than €100bn ($123bn) in operational efficiency improvements alone by using Big Data – and that’s not including employing advanced analytic tools to reduce fraud and errors and boost the collection of tax revenues. But it’s not just companies and organisations that stand to gain from the value that Big Data can create. Consumers can also reap highly significant benefits. For instance, users of services enabled by personal-location data can capture $600bn in consumer surplus. Take smart routing using real-time traffic information, which is one of the most heavily-used applications of personal-location data. As the penetration of smart phones increases, and free navigation applications are included in these devices, the use of smart routing is likely to grow. By 2020, more than 70 percent of mobile phones are expected to have a GPS capability, up from 20 percent in 2010. All told, we estimate that the potential global value of smart routing in the form of time and fuel savings will be about $500bn by 2020. This is equivalent to saving drivers 20bn hours on the road, or 10 to 15 hours every year for each traveller, and about $150bn on fuel consumption. Some of the most significant potential to generate value from Big Data will come from combining separate pools of data. The U.S. healthcare system, for instance, has four major pools of data – clinical; activity (claims) and cost; pharmaceutical and medical products R&D; and data about patient behaviour and sentiment – each of which is primarily captured and managed by a different constituency. MGI estimates that if U.S. healthcare fully used all the available techniques that can be enabled by Big Data, such as analyzing records of real-world medical treatments, their costs and health outcomes to guide physicians on which treatments provide the best outcomes at the best cost, the annual productivity of the sector could grow by an additional 0.7 per cent. But achieving this boost in productivity will require the combination of data from different sources – often from organizations that have no history of sharing data at scale. Sets of data such as patient records and clinical claims would have to be integrated. Doing so would create benefits not just for the various industry players but for patients, who would have broader, clearer access to a wider variety of healthcare information, making them more informed. Patients would be able to compare not only the prices of drugs, treatments, and physicians, but also their relative effectiveness, enabling them to choose more effective, bettertargeted medicines, potentially even customised to their personal genetic and molecular make-up. To obtain those broad benefits, healthcare consumers may have to accept a slightly different tradeoff between their privacy and the benefits that wider pooling of data would bring. Sensitivities around privacy and data security are just one hurdle that companies and governments need to overcome if the economic benefits of big data are to be realised. One of the most pressing challenges is a significant shortage of people with the skills to analyse big data. By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical training (in statistics or machine learning) and another 1.5m people with the managerial and quantitative skills to be able to frame and interpret analyses effectively enough to base decisions on them. There are also many technological issues that need to be resolved to make the most of big data. Legacy systems and incompatible standards and formats often prevent the integration of data and the application of the more sophisticated analytics that create value. Ultimately, making use of large 47
digital datasets will require the assembly of a technology stack from storage and computing through analytical and visualisation software applications. Above all, access to data needs to broaden. Increasingly, companies will need to access data from third parties, e.g., business partners or customers, and integrate them with their own. A vital competency for data-driven organizations in the future will be the ability to create compelling value propositions for others, including consumers, suppliers and potentially even competitors, to share data. If it looks unlikely that data sharing will occur despite the potential for societal benefits (a market failure), legislators may then have to step in. As long as companies and governments understand the power of Big Data to deliver higher productivity, better value for consumers, and the next wave of growth in the global economy, there should be a strong enough incentive for them to act robustly to overcome the barriers to its use. By doing so they will unleash avenues to new competitiveness among companies, higher efficiency in the public sector that will enable better services, even in constrained fiscal times, and enable firms and even whole economies to be more productive. BIG DATA IS A BIG DEAL The era of Big Data could yield new management principles. In the early days of professionalized corporate management, leaders discovered that minimum efficient scale was a key determinant of competitive success. Likewise, future competitive benefits are likely to accrue to companies that can not only capture more and better data but also use that data effectively at scale. We hope that by reflecting on such issues and the five questions that follow, executives will be better able to recognize how big data could upend assumptions behind their strategies, as well as the speed and scope of the change that’s now under way. 1. What happens in a world of radical transparency, with data widely available? As information becomes more readily accessible across sectors, it can threaten companies that have relied on proprietary data as a competitive asset. The real-estate industry, for example, trades on information asymmetries such as privileged access to transaction data and tightly held knowledge of the bid and ask behaviour of buyers. Acquiring both requires a significant expense and effort. In recent years, however, online specialists in real-estate data and analytics have started to bypass agents, permitting buyers and sellers to exchange perspectives on the value of properties and creating parallel sources for real-estate data. Cost and pricing data are becoming more accessible across a spectrum of industries. Another swipe at proprietary information is the assembly by some companies of readily available satellite imagery that, when processed and analyzed, contains clues about competitors’ physical facilities. These satellite sleuths glean insights into expansion plans or business constraints as revealed by facility capacity, shipping movements, and the like. One big challenge is the fact that the mountains of data many companies are amassing often lurk in departmental “silos,” such as R&D, engineering, manufacturing, or service operations—impeding timely exploitation. Information hoarding within business units also can be a problem: many financial institutions, for example, suffer from their own failure to share data among diverse lines of business, such as financial markets, money management, and lending. Often, this prevents these companies from forming a coherent view of individual customers or understanding links among financial markets. 48
Some manufacturers are attempting to pry open these departmental enclaves: they are integrating data from multiple systems, inviting collaboration among formerly walled-off functional units, and even seeking information from external suppliers and customers to co-create products. In advancedmanufacturing sectors such as automotive, for example, suppliers from around the world make thousands of components. More integrated data platforms now allow companies and their supply chain partners to collaborate during the design phase—a crucial determinant of final manufacturing costs. 2. If you could test all of your decisions, how would that change the way you compete? Big Data ushers in the possibility of a fundamentally different type of decision making. Using controlled experiments, companies can test hypotheses and analyze results to guide investment decisions and operational changes. In effect, experimentation can help managers distinguish causation from mere correlation, thus reducing the variability of outcomes while improving financial and product performance. Robust experimentation can take many forms. Leading online companies, for example, are continuous testers. In some cases, they allocate a set portion of their Web page views to conduct experiments that reveal the factors that drive higher user engagement or sales gains. Companies selling physical goods also use experiments to aid decisions, but Big Data can push this approach to a new level. McDonald’s, for example, has equipped some stores with devices that gather operational data as they track customer interactions, traffic in stores, and ordering patterns. Researchers can model the impact of variations in menus, restaurant designs, and training, among other things, on productivity and sales. Where such controlled experiments aren’t feasible, companies can use “natural” experiments to identify the sources of variability in performance. One government organization, for instance, collected data on multiple groups of employees doing similar work at different sites. Simply making the data available spurred lagging workers to improve their performance. 3. How would your business change if you used Big Data for widespread, real-time customization? Customer-facing companies have long used data to segment and target customers. Big Data permits a major step beyond what until recently was considered state of the art, by making real-time personalization possible. A next-generation retailer will be able to track the behavior of individual customers from Internet click streams, update their preferences, and model their likely behavior in real time. They will then be able to recognize when customers are nearing a purchase decision and nudge the transaction to completion by bundling preferred products, offered with reward program benefits. This real-time targeting, which would also leverage data from the retailer’s rewards program, will increase purchases of higher-margin products by its most valuable customers. Retailing is an obvious industry for data-driven customization because the volume and quality of data available from Internet purchases, social-network conversations, and, more recently, locationspecific smart phone interactions have mushroomed. But other sectors, too, can benefit from new applications of data, along with the growing sophistication of analytical tools for dividing customers into more revealing microsegments. 4. How can Big Data augment or even replace management?
49
Big data expands the possible domains of application for algorithms and machine-mediated analysis. At some manufacturers, for example, algorithms analyze sensor data from production lines, creating self-regulating processes that cut waste, avoid costly (and sometimes dangerous) human interventions, and ultimately lift output. In advanced, “digital” oil fields, instruments constantly read data on wellhead conditions, pipelines, and mechanical systems. That information is analyzed by clusters of computers, which feed their results to real-time operations centers that adjust oil flows to optimize production and minimize downtimes. One major oil company has cut operating and staffing costs by 10 to 25 percent, while increasing production by 5 percent. Products ranging from copiers to jet engines can now generate data streams that track their usage. Manufacturers can analyze the incoming data and, in some cases, automatically remedy software glitches or dispatch service representatives for repairs. Some enterprise computer hardware vendors are gathering and analyzing such data to schedule preemptive repairs before failures disrupt customers’ operations. The data can also be used to implement product changes that prevent future problems or to provide customer-use inputs that inform next-generation offerings. The bottom line is improved performance, better risk management, and the ability to unearth insights that would otherwise remain hidden. As the price of sensors, communications devices, and analytic software continues to fall, more and more companies will be joining this managerial revolution. 5. Could you create a new business model based on data? Big Data is spawning new categories of companies that embrace information-driven business models. Many of these businesses play intermediary roles in value chains where they find themselves generating valuable “exhaust data” produced by business transactions. One transport company, for example, recognized that in the course of doing business, it was collecting vast amounts of information on global product shipments. Sensing opportunity, it created a unit that sells the data to supplement business and economic forecasts. Another global company learned so much from analyzing its own data as part of a manufacturing turnaround that it decided to create a business to do similar work for other firms. Now the company aggregates shop-floor and supply-chain data for a number of manufacturing customers and sells software tools to improve their performance. This service business now outperforms the company’s manufacturing business.” Can Big Data help avoid the correlation trap? According to Kernochan (2013): “Can Big Data help enterprises establish causation, and thus avoid the data correlation trap? Yes, says Wayne Kernochan of Infostructure Associates. As I was at a vendor conference recently that brought this to mind, I will write on something that is less about the vendor and more about what I view as major opportunities for software technology going forward. In this case, I am referring to causality vs. correlation. Be assured, this eventually relates to business strategy. One of the first things I learned in statistics was to beware of "spurious correlation." The example given was the fact that growth in use of radios tracked nicely to the growth in population, the economy, etc. So, it was easy to conclude that selling more radios would ensure a booming economy 50
forever and a day. In fact, the two had nothing to do with each other; it was just that both of them happened to be growing pretty much monotonically at a particular period in time. The obvious way to avoid spurious correlation is to establish causation: This is or is not caused by that. Loosely speaking, it appears to me that establishing causation between groups of events/data points A and B involves two key elements:
Establishing that group of events B follows group of events A in time; and Establishing a physical link between event A and event B (e.g., your return of serve in tennis is physically linked to my serve: I’m serving to you, not to someone else.)
Establishing Causation The problem in the real world is that while statistics and analytics are awash in ways to establish correlation, there is an incredible paucity of ways to establish causation. I wandered through the byways of Wikipedia when, a while ago, I considered fulfilling my lifelong Asimov-Foundation-fueled desire to write about mathematical tools for predicting the future – and found nothing close to globally applicable. There was a major example of this in economics recently. Two economists, Reinhart and Rogoff, published a paper warning of the perils of high deficits to the future growth path of economies. To their data – whatever its merits – they applied standard regression techniques showing some sort of decrease in growth correlated with higher and higher levels of debt. But nowhere did they consider whether the data really did show that high deficits preceded slow growth in time. Moreover, comments by critics simply questioned whether high deficits preceded slow growth in time. Until very recently, no one attempted to figure out statistically what preceded what. Of course, once someone did that, it turned out that the data supported more that slow growth preceded high debt than vice versa – but this only covered the temporal aspect, not the physical link, and the statistical technique used was a very awkward comparison of regressions. The result of this, I think, is a pervasive, unconscious assumption that if we keep beating at correlations over and over, we will somehow establish causation. To me, this leads to the kind of business problem cited in a recent tweet: 80 percent of CEOs think they supply a superior customer experience, while just 8 percent of customers think so. These CEOs are taking things that have been shown to correlate with more positive customer response, and assuming they will work in the case of their own customers. I could cite many other examples in and out of business; but for businesses, this means money thrown down a rathole trying to provide a superior customer experience and failing – although certainly businesses are doing better than when the first spurious this-focus-group-likes-the-idea-soit'll-work correlations were used. I am asserting that the correlation trap is costing businesses lots of cash in wasted strategies, whether they are using Big Data or not. What Could Big Data Do? I recently tweeted that maybe "Big Data" should be called "Deep Analytical Processes" now because it is becoming apparent that any real value of Big Data beyond having more data to play with is that a change of degree is a change in kind. That is, the ability to use more data leads to another layer of understanding of its meaning – e.g., personalization of the customer rather than segmentation – and 51
that allows us to change fundamentally our processes for decision-making and action-taking in response to these insights. So for example, a company might change the call-center process to treat the call-center customer as a unique bundle of attributes instead of a category. One of these dimensions of depth that can potentially lead to a change in process is time. Now, optionally, the business can attach a sequence of interactions and changes in attributes over time to the individual customer. Not only can it know and remember what has happened in previous interactions, it can also detect how the customer has changed since the last interaction, so it can offer baby-related information to the new parent, for example. Thus, if the business is smart enough, it can eliminate many spurious correlations by seeing that they do not fit the customer sequence of actions and states. Think of the money wasted on call center redesigns that infuriated users! However, there remain three main improvements in Big Data before we can really establish causation and begin to truly escape the correlation trap:
Vendor products need to be beefed up to allow the temporal aspect of causation to be included, unobtrusively but pervasively, in analytics. There ought to be a "time-checker" that says, radio sales follow, they don’t lead, economic growth. Making sure of temporality should be a given in Big Data, not an effortful exception. Comparable attention must be paid to the physical link. The obvious place to do this is in the modeling phase. However, even in Big Data, the modeling phase does not appear to be a common step. Models need to include the concept of the physical link, and users need to use that capability by default. That’s a bit of a tall order. Statistics really needs to provide far better tools, and far greater use of them, for establishing both time and physical link. I would be happy if at least the time aspect was upgraded substantially, since development of models is still a bit of a black art. But some sort of minimal toolkit that is as useful as regression in including time, and figuring out how much that establishes causation, would be really useful.
Business Benefits of Avoiding the Correlation Trap (via Big Data) I have briefly alluded to examples of saving money by avoiding strategies based on spurious correlations. I believe, however, that avoiding the correlation trap provides a more fundamental business benefit from analytics. It seems to me that business benefits, crassly speaking, run along two lines: first, avoiding bad things such as costs and disasters, and second, achieving good things such as increased revenues and new markets. Business cases based on good things are necessarily more speculative, because before a CEO can achieve superior performance he or she has to keep the business alive – especially in these slow-revenue-growth times. Up to now, Big Data has leaned toward a good things message: Big Data use leads to new insights that improve revenues or decrease costs while increasing customer satisfaction, followed by – trust me – another such insight, followed by – trust me more – yet another such insight. However, avoiding the correlation trap is much more about avoiding bad things and much more long term. It's also about process, in the sense that your processes are now based on well-established insights where your action is better guaranteed to be a cause of a good outcome rather than being irrelevant and money-wasting or positively harmful. I like to compare this kind of strategy to effective 52
boxing. A short, better-targeted punch is more powerful and more likely to strike home than a roundhouse right in the vague direction of the opponent. Big Data, at least potentially, takes us a lot closer to that kind of strategic targeting by avoiding the correlation trap. It's not just about the latest and greatest insight. It's about not wasting money on the fad du jour, but taking full advantage of what's really going on, based not only on deep analysis but deep understanding. Fix the three problems cited above, and you're well on the way there. So for vendors, I believe the challenge is to get your products in shape to handle causation much better, as I detailed above. However, for users, there is no need to wait. You can start infusing your analytics with time-based analysis on a skunkworks or pilot-project basis right now, with a little careful piecing through the masses of detail your vendors give you. Then demand that your vendors up their game in this area. If all this comes to pass, I can dream that eventually even the statistics profession will pay attention to the real-world problems of establishing causality. If that happens, I will be happy, Isaac Asimov in his grave will be happy, and businesses might begin to appreciate statisticians more. In fact, I can envision a bumper sticker: Have you hugged your statistician today? On second thought ... naaah. That's a bit much, even for me. Businesses will just have to settle for long-term strategic benefits.” Four Things You Need To Know In The Big Data Era According to Clark (2013): “Big Data has been declared the “sexiest job of the 21st century” and it’s already reshaping corporate decisionmaking and even talent recruitment. As Phil Simon, author of Too Big to Ignore: The Business Case for Big Data, points out, “In a recent report, McKinsey estimated that the U.S. will soon face a shortage of approximately 175,000 data scientists.” Seemingly everyone wants in on Big Data, a blanket term for the massive amounts of information we generate today. (Simon notes that roughly 80 percent of that information is unstructured – such as tweets, blog posts, Facebook likes, or YouTube videos – as compared to the smaller and easier-to-manage “structured data” that populates spreadsheets.) With the impending rise of wearable technology and “The Internet of Things,” it appears the pace of data creation will only increase. Here are four things you need to know about the Era of Big Data. It’s Not Just for Large Companies. “Companies like Amazon, Apple, Facebook, Google, Twitter, and others would not be nearly as effective without Big Data,” says Simon. But it’s not exclusively the province of billion-dollar tastemakers. “In the book, I write about a few small companies that have taken advantage of Big Data. Quantcast is one of them. There’s no shortage of myths around Big Data, and one of the most pernicious is that an organization needs thousands of employees and billions in revenue to take advantage of it. Simply not true.” Data Visualization may be the Next Big Thing. You have massive amounts of data – how can you possibly comprehend it? Enter data visualization, which Simon believes is “absolutely essential for organizations…[These tools] are helping employees make sense of the never-ending stream of data hitting them faster than ever. Our brains respond much better to visuals than rows on a spreadsheet. This goes way beyond Excel charts, graphs, or even pivot tables. Companies likeTableau Software have allowed non-technical users to create very interactive and imaginative ways to visually represent information.” 53
Intuition isn’t Dead. It turns out Big Data and the certainty of numbers hasn’t killed intuition, after all. “Contrary to what some people believe,” says Simon, “intuition is as important as ever. When looking at massive, unprecedented datasets, you need some place to start. Intuition is more important than ever precisely because there’s so much data now. We are entering an era in which more and more things can be tested. Big Data has, at least not yet, replaced intuition; the latter merely complements the former. The relationship between the two is a continuum, not a binary.” It Isn’t a Panacea. “When used right,” says Simon, “Big Data can reduce uncertainty, not eliminate it. We can know more about previously unknowable things. This helps us make better predictions and better business decisions.” But it doesn’t mean we can rely solely on the numbers without injecting our knowledge, perspective, and (yes) intuition. Is your company using Big Data? How do you expect it to impact your business or industry?”
Social media from a business perspective References: ITACA (2010). Social Media: Business Benefits and Security, Governance and Assurance Perspectives. An ITACA Emerging Technology White Paper. Ross, J. M. (2009). A Corporate Guide for Social Media. Forbes Free Report. Lasica, J.D. (2013). Best practices for developing a social media policy. Society for New Communications Research. ENISA (2010). Online as soon as it happens. European Network and Information Security Agency. Ward, S. (2013). Social Media Marketing. About.com Guides. Makwana, K. (2012). Social Media – A Business Perspective. Prezi. The growing use of social media among citizens have several important implications for businesses. Positive and negative comments about a business and its products will spread rapidly through blogs and social communities like Facebook. Businesses may choose to be passive, reactive, or pro-active. Remaining passive to negative comments will obviously be dangerous for any serious business. Being reactive requires a lot of work on the part of the business in order to observe comments on the Internet, and to consider how to best respond. The best alternative seems to be for a business to become pro-active by developing a strategy for its own Internet presence, where the task of communicating with customers and the public at large becomes an integral part. “The use of social media is becoming a dominant force that has far-ranging implications for enterprises and individuals alike. While this emerging communication technology offers great opportunities to interact with customers and business partners in new and exciting ways, there are significant risks to those who adopt this technology without a clear strategy that addresses both the benefits and the risks. There are also significant risks and potential opportunity costs for those
54
who think that ignoring this revolution in communication is the appropriate way to avoid the risks it presents. The only viable approach is for each enterprise to engage all relevant stakeholders and to establish a strategy and associated policies that address the pertinent issues.” ITACA (2010). “Today, more than 90% of the adult online population is using social media. No Business can ignore social media anymore. and if it ignores, it is not only loosing an opportunity to enhance business, but its absence may cause damage to its brand and reputation. Social media offers opportunities to a business to connect and engage with its customers, build long lasting valuable relationships, generate new leads, build awareness, educate people and above all manage reputation. Online Branding Incorporating the name, logo, colour schemes and tagline in the company website or blog prominently. Using the same "identity" repeatedly on all other profile pages that the business may have on any other social media or whatever else is possible. Remain "Visible" to people and have active online presence. Keeping fans/ followers updated/ engaged to reach newer market and customers. It is essential for the business to take part in conversation in the social media, interact with the people directly and engage with them. Taking part in discussion groups/ forums on Q & A or writing about products and services on company's blog. The Social media provides a very good platform for all businesses to network and reach out to target audience, connect with them directly and generate trust by listening to what they have to say. Ideal platform for marketing, advertising, selling, public relations, publicity, direct marketing and sales promotion. Building Relationship Business can use the social media to build long lasting relationships with customers by engaging them at a level comfortable to them, answering queries, understanding their problems and helping them out. Use the social media as an effective communications tool to provide support, care and service to customers directly at their fingertips. Businesses can offer customers services or support from their own blogs or website thereby encouraging them to interact directly with the staff or customer care personal to address their grievance, if any, rather than voicing them out on a public platform. Word of Mouth A small mention in any of audience's profile goes a long way in spreading the word about business/product. "Let your customer become your marketing agents." Online Reputation Management Businesses have to keep track of what is being written about business/ product on the internet and then offset the negativity by tackling the source directly and addressing the issues or promote positive content.” Makwana (2012). What is “social media”? According to ITACA (2010): “Initiated as a consumer-oriented technology, social media is increasingly being leveraged as a powerful, low-cost tool for enterprises to drive business objectives such as enhanced customer interaction, greater brand recognition and more effective employee recruitment. While social media affords enterprises many potential benefits, information risk professionals are concerned about its inherent risks such as data leakage, malware propagation and privacy infringement. Enterprises seeking to integrate social media into their business strategy must adopt a cross-functional, strategic approach that addresses risks, impacts and mitigation steps, along with appropriate governance and assurance measures. 55
… Social media technology involves the creation and dissemination of content through social networks using the Internet. The differences between traditional and social media are defined by the level of interaction and interactivity available to the consumer. For example, a viewer can watch a news broadcast on television with no interactive feedback mechanisms, while social media tools allow consumers to comment, discuss and even distribute the news. Use of social media has created highly effective communication platforms where any user, virtually anywhere in the world, can freely create content and disseminate this information in real time to a global audience ranging in size from a handful to literally millions—in less time than it takes to read this document. There are many types of social media tools: blogs such as WordPress and TypePad, microblogs such as Twitter and Tumblr, image and video sharing sites such as Flickr and YouTube, social networking sites such as Facebook and MySpace, and professional networking sites such as LinkedIn. The common link among all forms of social media is that the content is supplied and managed by individual users who leverage the tools and platforms provided by social media sites.” According to Ross (2009): “Whether you call it Web 2.0, the social Web or any other neologism, the new network economy is about communities, collaboration, peer production and user-generated content. It is a place where business reputations are defined by customer opinions and ratings, where press is delivered by independent bloggers, and product development and insight is driven by customers. As digital natives–those who have grown up with the Internet–flood the workplace, your employees will expect to be part of the social Web and they’ll have a lot to contribute. Does this sound like business as usual? It shouldn’t. Social technologies turn many corporate policies upside down. Big corporations are scratching their heads trying to figure out how to harness the benefits of increased employee participation while mitigating the risks. Clearly there is no one-size-fits-all: If you are in financial services you have unique concerns for privacy, if you are part of the YMCA, you must be aware that having counselors “friend” teenagers is not appropriate, etc. Business benefits of social media According to ITACA (2010): “Social media has become a powerful tool for enterprises across the globe. A 2010 Burson-Marsteller study showed that, “of the Fortune Global 100 companies, 65 percent have active Twitter accounts, 54 percent have Facebook fan pages, 50 percent have YouTube video channels and 33 percent have corporate blogs.” Enterprises are using social media in many functional areas of the business and are enjoying numerous tangible benefits such as increasing brand recognition, sales, search engine optimization (SEO), web traffic, customer satisfaction, and revenue.3 In addition, rapid feedback and insight from consumers provide a mechanism for executives to assess consumer opinion and use this information to improve products, customer service and perception.
56
Enterprises have also discovered that they are able to monitor the market, their competition and their customers via social media outlets. This allows engaged enterprises to be on top of any changes that may be needed and to proactively make appropriate adjustments to strategies, products or services. The ability to search for and communicate with potential employees is another area that has seen great enhancement via sites such as LinkedIn and Plaxo. Given its ease of use and measurement and its ability to reach large populations almost instantly, social media is becoming a powerful force in the way businesses reach, attract and engage their customers, employees and other stakeholders.” Social media marketing Ward (2013): “What is social medial marketing? Social media marketing consists of the attempt to use social media to persuade consumers that one's company, products and/or services are worthwhile. Businesses using social media want to sell their products or services of course. But as blatant advertising on social media would, in most cases, alienate their intended audience or even get them kicked out of the particular social community they're trying to infiltrate, businesses need to use other methods to promote themselves. To use social media marketing effectively, businesses have to be perceived as members of the social media community, willing to interact with other members. The main problem with social media marketing from a business perspective is that it can be incredibly time-consuming. Social media marketing campaigns are not one-shot affairs; they need to be nurtured over time. While big businesses such as Dell, Microsoft and HP have been using social media marketing effectively, they have the kinds of marketing budgets that allow them to assign x number of staff to conduct and manage social media marketing campaigns, resources that a lot of small businesses don't have. Still, social media marketing is a type of marketing that many small businesses could benefit from, if only to find out more about what their customers are thinking - and saying - about their brand and their products. The main goals of social media marketing are to build a business' customer base and to develop and manage a company's reputation. More on Social Media Marketing Top 7 Reasons Why Your Small Business Should Use Twitter 5 Rules for Twitter Promotion Twitter for Entrepreneurs - Part 1: Getting Started Additional Resources Social Media Online Business Marketing Related Articles Social Media Marketing Plans - Social Media Reader Stories: How I Use Social Media Marketing 57
Social Media Tips for Ecommerce Segments Most Influenced by Social Media and Consumer Communities Social Media: What is the Role in Marketing?”
Guidelines and policies Here we present some thoughts about guidelines and policies about how to use social media in businesses, organiations, and workplaces. According to Ross (2009): “If you are an executive, keep in mind two points as you gear up your social media strategy: First, social technologies including blogs, social networks and Twitter are communication tools. That means a company’s social media approach must integrate with its existing communications channels and goals. Second, if you think these guidelines don’t apply to you, you are probably already on the endangered species list. Social Web Guiding Principles for Employers Lead by example. Rules aren’t enough. Leaders should model the behavior they would like to see their employees take. Chief executive Jonathan Schwartz of Sun Microsystems set a standard on blogging. Chief Executive Tim O’Reilly has established the bar on Twitter. A corollary to this rule: don’t delegate social media to interns or people who can’t possibly represent your culture and brand. Build your policies around job performance, not fuzzy concerns about productivity. If your employees are using Facebook at work, they are also likely checking work e-mail after dinner or at odd hours of the day. Don’t ask them to give up the former if you expect them to continue the latter. If you have good performance measurements, playing the “lost productivity” card is a canard. Encourage responsible use. Encourage employees to use social tools to engage and interact with one another and with customers. In all likelihood they are already using the social Web. The difference is that currently they are using these tools without any guidance. Company’s like Zappo’s encourage using social tools. Check out http://twitter.zappos.com/. Grant Equal Access. Don’t block your employees from any site that is already talking about your products or that you would like to see talking up your products (YouTube, Facebook, Twitter, blogs and so on.). I have had many experiences sending instructional material to clients and having them tell me that they can’t view the video or site at work. Enough said. Provide Training. The social Web is a cultural phenomenon; don’t go there without a guide. Consider providing some form of education for your employees (including discussion about what tools are available, how to use them and what are the prevailing cultural norms for use). You can use one of your own employees (a power user) or bring someone in–but get educated. Begin from a Position of Trust. While there are possible negatives involved in having employees on the social Web, most employees have common sense. Begin with a set of possibilities first (increasing awareness, improving customer 58
service, gaining customer insight and so on) then draw up a list of worst-case scenarios (bad mouthing the company, inappropriate language, leaking IP, to name a few). Modify the guiding principles for your employees below to help mitigate the risks you’ve identified. Once you embrace having your employees participate in the social Web, give them a few basic guiding principles in how they conduct themselves. You can start with these: Social Web Guiding Principles for Employees Listen before you talk. Before entering any conversation, understand the context. Who are you speaking to? Is this a forum for “trolls and griefers?” Is there a good reason for you to join the conversation? If your answer is yes, then follow these rules of engagement: Say who you are. In responding to any work-related social media activities always disclose your work relationship. Show your personality. You weren’t hired to be an automaton. Be conversational while remaining professional. If your personal life is one that you (or your employer) don’t want to mix up with your work, then consider establishing both private and public profiles, with appropriate sharing settings. Respond to ideas not to people. In the context of business, always argue over ideas not personalities. Don’t question motives but stay focused on the merit of ideas. Know your facts and cite your sources. When making claims, always refer to your sources, using hyperlinks when possible. Always give proper attribution (by linkbacks, public mentions, re-tweets and so on). Stay on the record. Everything you say can (and likely will) be used in the court of public opinion–forever. So assume you’re “on the record.” Never say anything you wouldn’t say to someone’s face and in the presence of others. Never use profanity or demeaning language. If you respond to a problem, you own it. If you become the point of contact for a customer or employee complaint, stay with it until it is resolved.” According to Lasica (2013): “From our research, six factors emerged as the highest priority in the successful development and implementation of a corporate blogging policy. These include: Culture: Foster a corporate culture of openness. Listen to and respect the opinions of employees, customers and other constituencies. Trust: Employees should be trusted to communicate and develop relationships with customers. Do not review blog posts prior to posting. Trust your employees to be good communicators and to use good judgment. 59
Training: Provide complete training about how to blog, and review legal issues with employees. Give employees the option of training rather than requiring them to participate. Transparency: Disclose connections with customers in blog posts. Reveal any commercial or personal connections. Transparency and authenticity are key. Accuracy: Check facts. Check with colleagues before publishing content that will affect them. If you write about private conversations, ask for permission before publishing. Comments: Develop and clearly communicate your organization’s comment policy. Set expectations and clearly communicate what is and what is not allowed on the blog. Allow negative and positive comments, but restrict inappropriate comments. Write to the person who commented first. Best practices for developing & implementing a social media policy The following best practices will also help organizations to successfully develop and implement corporate blogging policies and guidelines for their employees. Legacy guidelines: Use existing human resources and communications policies. Start with the employee communications agreement that is already in place in your organization as the foundation for your new policy. Provide guardrails for employees so they can safely and successfully engage in social media practices. Employees often seek help and guidance when they are considering launching a blog. Provide them the resources they want and need. Developing new guidelines: Include company bloggers in the process of developing corporate blogging policies and guidelines. Think ahead in your social media policy development. Develop policies that will extend to other new and emerging communications technologies such as podcasts and video, etc. Once published, distribute guidelines widely. Companies that have facilitated wider distribution had their guidelines shared virally. Legal Department: If you have a legal department, include them in the process but don’t let them drive the effort. Seek input from legal when developing blogging polices. Employee Communications: If you have an employee communications department, partner with them to develop these new polices. Whose views?: Clearly define if the blog reflects the employee(s)’ opinions or the company’s perspective. Allow constructive criticism: Is it permissible for your employees to provide a differing point of view from management’s position? A culture of open communication will provide the strongest foundation for the successful rollout of a social media program. Responding to comments: Set up a mechanism for responding to every comment that requires a reply. Acknowledge mistakes: Acknowledge mistakes and fix errors on your blog in a timely and open manner. Deleting confidential information: If information needs to be deleted because it is confidential and was posted in error, delete the information and state why the information has been deleted. 60
Podcasts and videos: Make sure employees understand that the mp3 files associated with podcasts are permanent and that it is not possible to remove mp3 files in the same way it is possible to take down blog content. The same permanent nature applies to video files. Social media: The policies developed for blogging and company websites apply to employees using other types of social media. Protect privacy: Consider, define and clearly communicate to employees what information is appropriate or inappropriate to disclose. Respect your audience: Respect your audience’s privacy. Respect competitors: Do not write about competitors in a negative way. Be respectful of others in your industry. Consider the impact on revenues: Consider this carefully, and remember that that if you talk about a new product, service or feature as a public company, you are required to account for the revenue in the quarter that you announced it. Disclosure: Make sure you identify your relationship with the company. Customer feedback loop: Let customers know you listened when they post feedback. Respond appropriately. Citations: Cite material included in your articles, and provide links to original sources where possible and appropriate. Don’t break confidentiality: Don’t write about confidential conversations. Communicate this policy clearly to employees: Err on the side of caution. Recommend to employees that if they believe a conversation might have been considered confidential, check with the person/people prior to publishing. Platform: Companies that choose to encourage all of their employees to blog can either provide a common blogging platform, or invite their bloggers to select the platform and domain of their choosing. Pace of adoption: Realize that adoption of social media does not have to happen all at once. It is a process.” Risks and security and privacy concerns – and how to meet them According to ITACA (2010): “Not wishing to be left behind, many enterprises are seeking to leverage social media tools. Since the tools are new to many enterprises and do not require new infrastructure, social media technologies may be introduced to the enterprise by business and marketing teams without IT involvement, a project plan or risk assessment. It is therefore important that the enterprise create a social media strategy and have a plan to address the risks that accompany the technology. 61
While the use of social media does have inherent risks that could negatively impact enterprise security, it also presents opportunities such as accelerated business growth and improved brand recognition. Therefore, simply choosing to prohibit the use of social media can also incur an opportunity cost based on forgoing these potential business benefits. As with any new initiative, enterprises should take care to consider risks vs. benefits when deciding on a social media strategy. There are several scenarios that should be considered when evaluating the impact of social media on the enterprise. Initially, the enterprise should consider the risks of using social media as a business tool to communicate with customers or constituents. Enterprises must also consider the risks of employee access to social media sites while on the corporate network. Finally, enterprises should consider that employees also use social media tools from their corporateissued mobile devices. Although mobile devices may be an organizational asset, they are often not subject to the same controls and monitoring as the enterprise’s computers. Vulnerabilities such as insecure applications may exist on an employee’s personal social media page; those vulnerabilities may cause unacceptable exposure on a corporate network. Additionally, malicious outsiders could use employee social media pages to launch targeted attacks by gathering information to execute sophisticated social engineering campaigns. A final, although perhaps more controversial, consideration is employee personal use of social media from home and personal computing devices. With the exception of the threats of infection of organizational computing assets with viruses and malware, all of the risks that exist for personal use of social media sites in the workplace also exist when employees access social media sites from home or other areas not controlled by the enterprise or its policies. Close collaboration with organizational human resources and legal departments is critical when considering an approach to this situation. Strategies for Addressing Social Media Risks Since enterprise use of social media tools usually requires no additional technology to implement, an enterprise social media presence does not always begin with a project plan and risk assessment. To effectively control social media usage by both the enterprise and employees, a documented strategy (and associated policies and procedures) should be developed with the involvement of all relevant stakeholders, including business leadership, risk management professionals, and human resource and legal representation. This holistic approach to integrating emerging technologies into the enterprise helps to ensure that risks are being considered in the context of broader business goals and objectives. While the use of social media presents an additional entry point for technology risks such as malware and viruses, these risks are elevated primarily because more employees may be using social media sites without understanding the threats that exist. Therefore, any strategy to address the risks of social media usage should first focus on user behavior through the development of policies and supporting training and awareness programs that cover: • Personal use in the workplace: – Whether it is allowed – The nondisclosure/posting of business-related content – The discussion of workplace-related topics – Inappropriate sites, content or conversations • Personal use outside the workplace: 62
– The nondisclosure/posting of business-related content – Standard disclaimers if identifying the employer – The dangers of posting too much personal information • Business use: – Whether it is allowed – The process to gain approval for use – The scope of topics or information permitted to flow through this channel – Disallowed activities (installation of applications, playing games, etc.) – The escalation process for customer issues Training should be conducted on a regular basis and should focus on the benefits and opportunities as well as on the dangers related to use of social media. Emphasis should be placed on the specific dangers and methods of social engineering, common exploits, and the threats to privacy that social media present. Training should also ensure full understanding of the rules governing acceptable use and behavior while on social media sites. Technical controls that exist for other e-commerce opportunities will benefit the enterprise when embracing a social media strategy. Technology can assist in policy enforcement as well as in blocking, preventing or identifying potential incidents. This strategic component should utilize a combination of web content filtering, which can block all access or allow limited access, and in some cases provide protection against malware downloads and end-user system antimalware, antivirus and operating system security to counter such attacks. As with most security technology strategies, a layered approach is optimal.”
Literature Anderson C. (2008). Free! Why $0.00 is the Future of Business. Wired Magazine 16.03. Axelsson, K, Melin, F, Lindgren, I, (2009). Developing public e-services for several stakeholders – a multifaceted view of the needs for an e-service. 17th European Conference on Information Systems. Bannister F. (2007). The curse of the benchmark: an assessment of the validity and value of egovernment comparisons. International Review of Administrative Sciences, 73 (2), 171-188. Baumol W.J. (1972). On Taxation and the Control of Externalities. American Economic Review 62(3), 307-322. Bartels, A. (2000). The difference between e-business and e-commerce. Computerworld, Oct 2000. Buchanan, L. (2011). How Great Entrepreneurs Think. Inc Com Magazine. Böhm, C. and Jacopini, G. (1966). Flow diagrams, Turing machines and languages with only two formation rules, Comm. ACM, 9(5):366-371. Clark, D. (2013). Four things you need to know in the Big Data era. Forbes. Clifton, J. A. (1977). Competition and the evolution of the capitalist mode of production, Cambridge Journal of Economics vol. 1, no. 2, pp. 137-151. 63
Codagnone, C. Undheim T.A (2008). Benchmarking eGovernment: tools, theory, and practice. European Journal of ePractice. Nº 4 • August 2008 Dagens Media. De 10 mest nedladdade apparna. The 10 most downloaded apps. In Swedish. Davenport T. (1993). Process Innovation: Reengineering work through information technology, Harvard Business School Press, Boston. Dahl, O.J., Dijkstra, E.W. Hoare, C.A.R. (1972). Structured Programming, Academic Press, London. Dijkstra, E.W. (1968). "Go To Statement Considered Harmful". Communications of the ACM (PDF) 11 (3): 147–148. doi:10.1145/362929.362947. Dupuit J. (1844). De la measure de l’utilité des travaux publics. Annales des ponts et chaussées, Second series, 8. ENISA (2010). Online as soon as it happens. European Network and Information Security Agency. Findahl O. (2006). Thieves or customers? File-sharing in the Digital World. In Cunningham P. and Cunningham M. (eds.), Exploiting the Knowledge Economy: Issues, Applications, Case Studies, IOS Press, Amsterdam. Entrepreneur. Exploring e-commerce. Retrieved: 2013-07-19. Erl, T. (2005) Service-Oriented Architecture – Concepts, Technology, and Design Prentice-Hall Ernst&Young (2012). Entreprenörsstudien 2012. In Swedish. ESBRI. Entreprenörskap är ett sätt att tänka. Entrepreneurship is a way of thinking. In Swedish. Retrieved: 2013-07-19. Finansportalen. Nyckeltal. In Swedish. Forbes (2013). The World’s Richest Tech Billionaires. Forbes (2011). Current Top 25 in Market Value. GAO (2002). E-Government: Proposal addresses Critical Challenges. U.S General Accounting Office, Govt of the USA. Garreffa, A. (2012). Rovio Entertainment are preparing IPO for 2013 – Analysts peg their value at 9 billion dollars. Tweaktown. Gaudeul A. and Jullien, B. (2005). E-commerce, two-sided markets and info-mediation. In Internet and Digital Economics 2007, Cambridge University Press. Gerber, M. (2012). Traits of a Truly Entrepreneurial Mindset. Inc Com Magazine. 64
Grönlund, Å., Hatakka, M. and Ask, A. (2007) Inclusion in the E-Service Society – Investigating Administrative Literacy Requirements for Using E-Services. 6th International Conference (EGOV 2007, Regensburg, Germany). Helbig, N; Gil-García, J ; Ferro, E (2009). Understanding the complexity of electronic government: Implications from the digital divide literature. Government Information Quarterly, 26(2009), 89–97. Hommes B-J. (2004). The Evaluation of Business Process Modelling Techniques. Doctoral thesis. Technische Universiteit Delft. Huang, C.J. (2003). Usability of E-Government Web Sites for People with Disabilities. In Proceedings of the 36th Hawaii International Conference on System Sciences (HICSS’03), IEEE Computer Society. Irwin T. (1997). Price Structures, Cross-Subsidies, and Competition in Infrastructure. The World Bank Group, Note No. 107. ITACA (2010). Social Media: Business Benefits and Security, Governance and Assurance Perspectives. An ITACA Emerging Technology White Paper. Jackson, M.A. (1975). Principles of Program Design, Academic Press, London. Jaeger, P.T. (2006). Assessing Section 508 compliance on federal e-government Web sites: A multimethod, user-centered evaluation of accessibility for persons with disabilities. Government Information Quarterly 23 (2006) 169–190. Kalén, K. (2013). Will e-entrepreneurs kill traditional entrepreneurship? Stockholm University. In Swedish. Kaylor, C., Deshazo, R. & Eck, D. V. (2001). Gauging e-government: A report on implementing services among American cities. Government Information Quarterly (GIQ), 18(4), 293 – 307. Kernochan, W. (2013). Can Big Data Avoid the Correlation Trap? EnterpriseAppsToday. Kotler P. (1967). Marketing Management: Analysis, Planning, Implementation and Control. Prentice Hall. Lasica, J.D. (2013). Best practices for developing a social media policy. Society for New Communications Research. Laureiro-Martinez, D., Brusoni, S., Canessa, N., Zollo, M. (2012). An Ambidextrous mind: An FMRI Study of Attention Control, Exploration-Exploitation Decisions and Performance. Bocconi University, CROMA Working Paper, 12/002. Lee, C-S. (2001). An analytical framework for evaluating e-commerce business models and strategies. Internet Research, 4(11), 349-359. Lee F.S. (1998). Post-Keynesian Price Theory. Cambridge University Press. Makwana, K. (2012). Social Media – A Business Perspective. Prezi. 65
Malhotra, Y. (1998). Business Process Redesign: An Overview. IEEE Engineering Management Review, vol. 26, no. 3. Marshall L. (2004). The effects of piracy upon the music industry: A case study of bootlegging. Media, Culture & Society, 26(2): 163-181. Mas-Colell A., Whinston M. D., and Green J.R. (1995). Microeconomic Theory. New York and Oxford: Oxford University Press. McGuire, T., Manyika, J., Chui, M. (2012). Why Big Data is the new competitive advantage. Ivey Business Journal. Pigou A.C. (1920). Economics of Welfare. Macmillan and Co. Prest A. R. & Turvey, R. (1965). Cost-Benefit Analysis: A Survey. The Economic Journal, Vol. 75, No. 300, pp. 683-735. Ross, J. M. (2009). A Corporate Guide for Social Media. Forbes Free Report. Rowley, J. (2006) An analysis of the e-service literature: towards a research agenda. Internet Research, 16 (3), 339-359 Samuelson P. A. (1948). Economics: An Introductory Analysis. McGraw-Hill; with William D. Nordhaus (since 1985), McGraw-Hill (18th ed., 2004). Samuelson P. A. (1954). The Pure Theory of Public Expenditure. Review of Economics and Statistics, 36(4), 387–389. Samuelson W. F. (2009). Managerial Economics. 6th edition, Wiley. Schiff, J. (2010). Ten Benefits of Business Intelligence Software. EnterpriseAppsToday. Selz D. (1999). Value Webs - Emerging forms of fluid and flexible organizations. Dissertation, University of St. Gallen. Shalini, R. (2009). Are Mauritians ready for e-Government services? Government Information Quarterly 26 (2009) 536–539. Smietana, F. (2013). 5 Ways to Bring Self-Service BI to Your Small or Midsized Business. Information Management. Stone, K. E. E-commerce and the Entrepreneur. Iowa State University. Strain, M. (2013). The Advantages of Business Intelligence. Chron Small Business. Sundgren B., Tolis C., and Steneskog G. (2004). Business Modelling and Solutions. 4th edition. Stockholm, Sweden: Stockholm School of Economics. Sundgren, B. (2010). Business models and authors rights in the information economy. International Journal of Public Information Systems. Vol 2010:2, pp 171-194. 66
Sundgren B. (2013a). Introduction to e-governance in e-societies. Sundgren B. (2013b). The concept of governance. Sundgren B. (2013c). Citizen-centric e-governance. Sundgren B. (2013d). Business-centric e-governance. Sundgren B. (2013e). Administration-centric e-governance. Sundgren B. (2013f). Methodological and technical perspectives on e-governance. Timmers P. (1998). Business Models for Electronic Markets. Electronic Markets, Vol. 8 No. 2, pp. 3-8. Timmers, P. (2000). Electronic Commerce - strategies & models for business-to-business trading, pp.31, John Wiley & Sons, Ltd, ISBN 0-471-72029-1. Ward, S. (2013). Social Media Marketing. About.com Guides. Wu, Philip F. (2009). User Acceptance of Emergency Alert Technology: A Case Study. Proceedings of the 6th International ISCRAM Conference – Gothenburg, Sweden Zimmerman H-D. (2000). Understanding the Digital Economy: Challenges for New Business Models. AMCIS Proceedings.
67
