Harold Jarche
seeking perpetual
beta A GUIDEBOOK
FO R T H E N E T WO R K E R A
A decade of seeking, sense-making, and sharing knowledge on the Web; examining how society, business, and education are fundamentally changing.
Harold Jarche > seeking perpetual beta
This eBook is copy-protection–free because I trust you to share it as you would a physical book and I do not want to limit your right to share. Your friends may want to buy their own copies if they like it. For multiple copies, or site licenses, group discounts are available. > Sackville, New Brunswick, Canada, April, 2014.
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Contents
Introduction
4
1 THE NETWORK ERA The Changing Nature of Work
6
Complication: The Industrial Disease
8
A Networked Market Knows More
12
Job is a Four-letter Word
14
Knowledge Artisans
16
Working Socially
18
Figure 1 The Connected Enterprise
21
Tapping the Creative Surplus
22
2 WORK IS LEARNING & LEARNING IS THE WORK PKM and the Seek > Sense > Share Framework
24
Figure 2 PKM = Seek > Sense > Share
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PKM and Competitive Intelligence
30
PKM and Innovation
32
Managing Organizational Knowledge
34
Training and Complex Work
38
Narrating Our Work
41
Collaborate to Solve Complex Problems
44
3 LEADING & MANAGING IN NETWORKS Network Thinking Figure 3 Trust Emerges Through Openness and Transparency
47 47
The Connected Enterprise
50
The Knowledge Sharing Paradox
52
Managing Automation
54
Flip the Office
56
Connected Leadership
57
Figure 4 Connected Leadership
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4 THE GLOBAL VILLAGE Figure 5 Organizing Characteristics
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Figure 6 TIMN (David Ronfeldt)
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Figure 7 Tetrad of a Networked Society
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Colophon
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Introduction I had purchased my own web domain in 2003 but it was not until 2004 that I integrated a blog with my website at jarche.com. Ten years ago it was still difficult to manage your own website if you did not have good technical skills, which I did not. For example, I took my first, and only, computer programming course in 1978. It was on FORTRAN and I remember very little other than carrying stacks of punch cards and never getting a single program to run. I did not touch a computer again until 1993, when I had to submit my course assignments on a floppy disk. Shortly after that, I saw the Web on a computer in Montreal that showed a website in Germany. Suddenly things clicked. The Internet was a way to connect to other people. In 1994 I started a Master’s degree and my thesis was on learning in the information technology workplace. During my studies I read in depth the work of Marshall McLuhan, famous for aphorisms like “the medium is the message”, and I was inspired by the laws of media, developed in conjunction with his son Eric, which still inform my work.
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In February 2004, blogs were one of the few ways that an individual could self-publish to the web. We still called them weblogs back then. They had been around for quite a while, but it was not until 2006 that they became mainstream. My early blog friends helped me a lot in getting to understand the medium. I remember getting technical support from James Farmer (AU) and Scott Leslie (CA) .
I was inspired by the prolific work of Jay Cross (US) and Jane Hart (UK) ,
early bloggers in my field, who later became my colleagues. Many of these early blogging connections remain friends and colleagues, like Rob Paterson (CA) , Jon Husband (CA) , Luis Suarez (ES) , Bill Fitzgerald (US) , Nancy White (US) , and Jacques Cool (CA) . There are many others, but these were some of my earliest connections. I would also like to thank Richard Martin (UK) for his copy editing and keen eye on the final manuscript. All errors remain mine. Finally, I have to thank Christopher Mackay (CA) for hosting my site for the past 10 years and designing this publication. Chris is one of the few people in our small town who actually understands what I do for a living. The following essays are abridged and updated posts as well as combinations of posts made over the course of a decade. When I started my blog, I had three categories: learning; work; and technology. Today there are many others, as my professional interests have expanded and changed. My perspective on work and learning has been one of perpetual Beta, which also could be called strong beliefs, loosely held. Alpha is a mindset of pumping out flavour of the month drivel. Beta is more than Alpha, as you have to affirm principles and actually commit to something, while remaining open to change. I have been observing the signs and indicators of the shift to the network era for the past decade. These articles have stood the test of time, and have been refined and discussed many times in order to be suitable for Beta.
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1 THE NETWORK ERA The Changing Nature of Work The fundamental nature of work is changing as we transition into the network era. Creative work is beginning to dominate industrial work as we shift to a postjob economy. The major driver of this change is the automation of routine work, especially through software, but increasingly with robots. Valued work is in handling exceptions, dealing with complex problems, and doing customized tasks. The products of this work are often intangible and not physical. As a result, our industrial work structures need to change. Organizations have to become more networked, not just with information technology, but in how workers create, use, and share knowledge. The workplace of the network era requires a different type of leadership; one that emerges from the network as required. Effective leadership in networks is negotiated and temporary, according to need. Giving up control will be a major challenge for anyone used to the old ways of managing. An important part of leadership will be to ensure that knowledge is shared throughout the network. Learning is a critical part of working in a creative economy. Being able to continuously learn, and share that new knowledge, will be as important as showing up on time was in the industrial economy. Continuous learning will also disrupt established hierarchies as no longer will a management position imply greater knowledge or skills. Command and control will be replaced by influence and respect, in order to retain creative talent. Management in networks means influencing possibilities rather than striving for predictability. We will have to accept
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that no one has definitive answers anymore, but we can use the intelligence of our networks to make sense together. The shift to the network era will not be easy for many people and most organizations. Common assumptions about how work gets done will have to be discarded. Established ways of earning education credentials will be abandoned for more flexible and meaningful methods. Connections between disciplines and professions are growing and artificial boundaries will continue to crack. Systemic changes to business and education will happen. There will be disruption on a societal level, but we can create new work and learning models to help us deal with this next phase in human civilization. The statistician George Box wrote that, “essentially all models are wrong, but some are useful”. We will never know unless we try them out.
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Complication: The Industrial Disease We are so interconnected today that many cannot imagine otherwise. Almost every person is connected to worldwide communication networks. News travels at the speed of a Tweet. Meanwhile, inside the enterprise, reaction times and feedback loops have to get faster to deal with markets that can create multi-billion dollar valuations seemingly overnight. But are they getting faster? Expectations for digital competencies for workers keep increasing, without much of a clue from management what these really are. Today’s workplace demands emergent practices just to keep up, but there is little time or thought provided to develop these. In most cases our current models for managing people and supporting their knowledge-sharing are ineffective. Knowledge workers today need to connect with others to co-solve problems but the best tools to do this are often outside the enterprise. For instance, social media can enable the development of emergent practices through ongoing conversations. Sharing tacit knowledge in this way is becoming an essential component of knowledge work. But too often the tools needed are not available, or internal policies cripple knowledge-sharing, especially if contract or external workers are involved. The modern enterprise is its own worst enemy. In the network era, learning and working are tightly interconnected. Connected knowledge workers need more than directives; they need ongoing, real-time, constantly-changing, collaborative, support. This should be a major management responsibility but it is often ignored. To create professional knowledge-sharing connections requires a level of trust that has to be developed over time. Trust cannot be turned on as desired, no matter what the company directives state. The default action is often to turn to Jarche.com > 2004–2014
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the closest colleagues for advice, but they may not be the most knowledgeable on the subject. Company policies that try to limit information sharing, in case it may be inaccurate, further sabotage organizational learning. Social bonds keep us together and connections between people drive innovation. However, management can routinely ignore social learning because it is not visible. Our complicated industrial organizations are quite good at keeping their structural problems hidden. Most companies started with relatively simple structures; a few people gathering together around an idea. For small companies, decision-making, task assignments and direct interaction with clients are rather straightforward. With growth, the simplicity ends. Organizational growth is usually viewed as a positive development, but it comes at a cost. As organizations grow, the original simplicity gets harder to maintain. Some management experts consider the ideal size of an organization to be around 150 people. This is based on Robin Dunbar’s research and is supported by the consistent size of military units through history. Beyond this size, knowing everybody in person becomes impossible. Above 150 people, additional layers of power and delegation begin to develop and companies enter the realm of complication. Most of today’s larger companies have a complicated structure. It takes a lot of analysis to understand all the pieces. Over time, even more processes and departments are put in place. To ensure reliable operations and risk mitigation, the core competencies of decision-making and innovation are centralized, creating a structural knowledge-sharing bottleneck. New layers of control and supervision continue to appear, and knowledge sharing is so formalized it becomes useless for decision-making.
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Without two-way knowledge-sharing, workers get disconnected from the company. For example, the company’s vision will be established at the board level, but individual workers will be far removed from it. A company vision statement that says people are its greatest asset will not be respected by workers who fear the next down-sizing event designed to increase stock value. As companies get even bigger, internal growth and innovation reach a tipping point, and companies rely on mergers and acquisitions to maintain the illusion of growth. By transferring jobs to subsidiaries, contractors and subcontractors, these large firms do not even create new jobs any more. The reliance on these workers creates more control protocols as management trusts them less than full-time employees, thus choking off meaningful knowledge-sharing. However, the acquisition and sharing of new knowledge remains a critical factor for innovation. To compensate for its complicated processes, the large enterprise may put significant effort into compliance training for workers, and leadership training for executives. The former is often useless and the latter can be a scam. Today’s complicated organizations are now facing increasingly complex business environments that require agility in simultaneously learning and working. Typical strategies of optimizing existing business processes or cost reductions only marginally improve the organization’s effectiveness. Faster markets challenge the organization’s ability to react to customer demand. Decision-making becomes paralyzed by process-based operations and chains of command and control. Organizations need to understand complexity instead of adding more complication. This lack of understanding is a major barrier to becoming a truly connected
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enterprise in the network era. To succeed in complex environments, the organization should focus on four basic pillars: 1. Knowledge 2. Trust 3. Credibility 4. a Focus on Results These are the principles of the wirearchy management framework, developed by Jon Husband. First consider that innovation comes from a diversity of ideas and networks, but only if knowledge is freely shared. Trust emerges over time through transparency and authenticity, practiced by people working out loud. Credibility is earned through collective intelligence, developed through an active questioning of all assumptions, including our own. Finally, a focus on results is enabled through both collaboration and cooperation, and is further enhanced by subsidiarity — the promotion of the furthest possible distribution of all authority. These four simple principles can help address the real industrial disease: complication. The pillars are the foundation for management practices in the network era and are directly linked to managing open networks and practicing connected leadership. In the network era, everything is connected: leadership, management, learning & getting work done.
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A Networked Market Knows More If you have not read The Cluetrain, you should at least peruse some of its 95 theses at cluetrain.com. The initial thesis of The Cluetrain Manifesto is that markets are conversations, but I think that theses 10 through 12 describe the change in relationships brought on by the Internet. #10. As a result, markets are getting smarter, more informed, more organized. Participation in a networked market changes people fundamentally. #11. People in networked markets have figured out that they get far better information and support from one another than from vendors. So much for corporate rhetoric about adding value to commoditized products. #12. There are no secrets. The networked market knows more than companies do about their own products. And whether the news is good or bad, they tell everyone. The big challenge will be equipping individuals with their own empowering tools. These tools are hardware, software, and most importantly, skills and attitudes. Taking control of our learning is a challenge for individuals used to working inside hierarchies that demand conformity and compliance. But the deck is still stacked against networked individuals. So if you read The Cluetrain back in 1999, or have since quoted it, then it’s time to think about how to implement it. I have no doubt that major systemic change is necessary to deal with the wicked problems that face society today. Critical components that need to change are how we work and how we learn in organizations. That change has to start with people. Individuals need to build their own interdependent personal learning systems.
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This is not a leadership or a management responsibility. This is a people issue. Each one of us should start seeking knowledge, building upon it, and sharing it, all in public. In this way we can develop an aggressively intelligent and engaged citizenry. For the first time in history we have the means to learn together without any institutional or organizational intermediaries. We don’t need schools, or even corporate MOOC ’s (massively open online courses). It is not easy, but it is possible to create a global group of co-learners around almost any problem or subject today. What’s holding us back? I think we are holding ourselves back. If participation in a networked market changes people fundamentally, then it’s time to make some fundamental changes through active participation. Here is an example of re-thinking market relationships. Doc Searls, co-author of The Cluetrain Manifesto, is working with the Vendor Relationship Management Project, which is “based on the belief that free customers are more valuable than captive ones — to themselves, to vendors, and to the larger economy. To be free —” • Customers must enter relationships with vendors as independent actors. • Customers must be the points of integration for their own data. • Customers must have control of data they generate and gather. This means they must be able to share data selectively and voluntarily. • Customers must be able to assert their own terms of engagement. • Customers must be free to express their demands and intentions outside of any one company’s control. Similar changes can and should be made in education and employment. • Free learners are more valuable than captive ones. • Free employees are more valuable than captive ones.
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Job is a Four-letter Word The concept of the job is inadequate for a creative economy. New workplace design principles are needed for the network era. Several years ago I took a term position at a university as the knowledge transfer officer, responsible for the commercialization of research. The work included managing communications on research issues; finding partnership opportunities with industry; and helping faculty with the patents, intellectual property protection and technology disclosures. But, like most people, I was more than my job description. I thought my expertise in organizational development, knowledge management and educational technologies would be areas of interest for a university. However, I could not get involved in these areas because that was not my job. The organizational common wisdom was that I was not faculty, therefore I could not be involved in teaching. I did not work in computing services therefore I could not touch IT . I was not in HR so I could not help with organizational development. Stick to your knitting, was the implied message of departmental responsibilities and hierarchies. If I saw an opportunity outside my job description there were few things I could do about it. I could initiate some collegial conversations, if I had the opportunity, but I would not be invited to the table. I had accepted this contract already knowing the university and what I would be able to do. But what happens to a person’s entrepreneurial and creative spirit after they repeatedly see that they can’t do anything with it? If you’re told often enough that it’s not your job, you will start saying, sorry, but that’s not my job. In this case, my entrepreneurial spirit quickly eroded and I lost interest in my work. I think that the construct of the job, with its defined skills, effort, responsibilities and working conditions, is a key limiting organizational factor for a creative economy. The Taylorist assumptions of division of labour and packaging of tasks Jarche.com > 2004–2014
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are just plain wrong (Principles of Scientific Management, F.W. Taylor, 1911). As Jon Husband explains: Any of us familiar with medium to large sized organizations can begin to see, I believe, that the fundamental Taylorist assumption that knowledge is structured vertically and put to use in siloed pyramidic structures and cascaded down to the execution level must be straining at the seams in the increasingly highlyconnected social networks in which many people work today. The core assumption of the job, that can be “filled” [just like the minds of students], is what needs to change. The job structure presumes common skills and the mechanistic view that workers can be replaced without disruption. But who could replace Socrates, Picasso, Einstein or Virginia Woolf or ____? As complex work requires more creativity, confining our complex individual creativity within the bounds of a mere job description is debilitating. Structured jobs can suck individual creativity and create an organizational framework that discourages entrepreneurial zeal. It’s time for a serious redesign of how we structure work.
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Knowledge Artisans An artisan is a skilled manual worker in a particular craft, using specialized processes, tools and machinery. Artisans were the dominant producers of goods before the industrial era. Knowledge artisans of the post-industrial era are beginning to retrieve old world care and attention to detail, but they are using the latest tools and processes in an interconnected economy. Look at a web start-up company and you will see it is filled with knowledge artisans, using their own tools and connecting to outside social networks to get work done. They can be programmers, marketers, salespeople. They’re distinguishing characteristic is seeking and sharing information to complete tasks. Next generation knowledge artisans are amplified versions of their pre-industrial counterparts. Equipped with and augmented by technology, they rely on their networks and skills to solve complex problems and test new ideas. Small groups of highly productive knowledge artisans are capable of producing goods and services that used to take much larger teams and resources. In addition to redefining how work is done, knowledge artisans are creating new organizational structures and business models, such as virtual companies, crowd-sourced product development and alternative currencies. Knowledge artisans not only design the work, but they can also do the work. It is not passed down an assembly line. Many integrate marketing, sales and customer service with their creations. To ensure that they stay current, they become members of various guilds, known today as communities of practice or knowledge networks. One of the earliest knowledge guilds was the open source community, which developed many of the communication tools and processes used by knowledge artisans today: distributed work; results-only work environments; blogs & wikis for sharing; agile programming; flattened hierarchies; and much more.
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Companies will employ or work with more contractual, shorter-term artisanal workers, many who bring their own learning networks. Companies must be ready to adapt to knowledge artisans with a greater emphasis on collaborating and connecting with their external online networks.
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Working Socially Saying we don’t need to understand social media is like saying we didn’t need to understand speaking, reading or writing to do our jobs before. With ubiquitous connectivity, more of our work is at a distance, either in space or time. Distributed work is becoming the norm. If we are going to support people doing this kind of work, we need to understand it. However, working in online social networks takes practice to be proficient. It is difficult to understand theoretically. For example, even though I had worked online for over a decade, I did not really understand Twitter until I started using it regularly in 2008. One fundamental difference about social media is they have a strong influence on the user, very much in a McLuhanesque medium/message/massage way. Those who come to social media for the first time are like adults learning a new language. They cannot start with the same advanced mental models and metaphors that they have in their primary language. Social media change the way we communicate and social media can change the way we think. We need to use the tools in order to understand what it’s like to be a node in a social network. There is almost nothing like it in the industrial workplace or school system to prepare us for this. Therefore we won’t know what we’re talking about until we learn the new language of online networks. The only way to learn a new language is through practice. Work today has few time or geographical boundaries. As our water coolers become virtual, social relations online will be the glue that connects us in our increasingly distributed work. Every little tweet, blog post, comment or like online shares our individuality and humanity. These actions help us be known to others in the digital surround. They help us build trust to get things done, be productive and innovate. However, we cannot benefit from professional social networks Jarche.com > 2004–2014
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unless we engage in them. This requires more than merely mastering the technology. It means being social in our work. Not using social media to connect, contribute and collaborate is like sitting in a closed office all day. To stay engaged with interconnected markets, business has to get more social. Social learning, a major activity on social media, is how we get things done in networks. Most organizational value is created by teams and networks, not individuals working alone. Organizational learning spreads through social networks. Therefore, social networks are the conduit for effective organizational performance. Blocking, or circumventing, social networks slows learning, reduces effectiveness and may in the end kill the organization. Senior managers need to understand social media in order to support learning in social networks which will enable practitioners to produce results. Does social mean highly connective? It’s much more than that. Social means human. It is an understanding that relationships and networks are complex. Our industrial management models are based on a belief that our structures are merely complicated, but more of our work is dealing with complex problems, for which there is no standardized approach. Social bonds keep us together. Much of it is about trust. If I trust you, I might ask you for advice, so trust is essential for collaboration. We lose it if we try to micro-manage knowledge work. The argument that ‘business is business and social is social’ makes little sense today. Business is social because it involves people. Business must be more social the more complex the work and the greater the need for collaboration and cooperation. We foster innovation through social interactions. The idea that a lone person working in a lab can come up with a brilliant idea is largely unfounded. Connections between people drive innovation. Jarche.com > 2004–2014
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Connecting ideas is the core of innovation, but without connecting ideas to people, there is no innovation at all. —Tim Kastelle, University of Queensland
We need to understand complex adaptive systems and develop work structures that let us focus our efforts on learning as we work in order to continuously develop next practices. The role of leadership becomes supportive rather than directive in this new knowledge-intensive and creative workplace. Artificial boundaries that limit collaboration and communication only serve to drag companies down and create opportunities for more agile competitors. Most managers would agree that an increasing amount of work and effort is in exception-handling. Social networks are an excellent framework to deal with these, as they enable people to crowd-source problem solving and speed the flow of knowledge. To understand social networks, it is best to be able to see them. Visualization, like value network analysis, enables people to see the workplace with new eyes. This in turn can lead to diverse ideas and innovative approaches. Visualizing network relationships can give the initial leverage of getting complex new ideas accepted into general management thinking. Visualization is the fulcrum to widespread understanding of social connections in business. Finally, it’s rather obvious that many HR policies imply that people cannot be trusted. Almost all IT policies say that. But it’s an interconnected world. Everything is transparent, whether we want it to be or not. Once management realizes that their company is a glass house, they will have to start working differently.
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Figure 1 The Connected Enterprise open & networked
Social Networks improve innovation from a diversity of ideas Communities of Practice solve problems & test new ideas Work Teams share complex knowledge
controlled & hierarchical
unified & collaborative
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diverse & cooperative
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Tapping the Creative Surplus The shift from consuming broadcast media to creating interactive media may be engaging a new generation in a new way. Just think of all the hours that used to be spent watching TV can now be used to generate ideas — some good and many bad — but they are being generated on an enormous scale. The myriad of explanatory videos on YouTube are an example of people sharing their knowledge on all manners of topics. This is what author Clay Shirky calls the Cognitive Surplus (2010) where people are learning how to use their free time more constructively to create rather than merely consume. As the demand and value of creative work increases, tapping into an organization’s cognitive surplus may become a critical business activity. But being creative isn’t something you can just turn on and off, as any artist can attest. This means changing how we structure work. Spending time on merely managing things can sap our energy and drive for doing creative work. Today’s workplace has to channel its creative surplus because value in the new economy, with mostly intangible goods & services, is created by workers with passion and initiative. Value creation in the 21st century is having ideas, connecting ideas, and trying new things out based on these ideas. Not only do these activities take time, they are highly social, as success often depends on who we work with. In Connected: The surprising power of our social networks and how they shape our lives (2011), sociologist Brian Uzzi, describes how creative teams in musical productions function: “Production company networks with a mix of weak and strong ties allowed easy communication but also fostered greater creativity because of the ideas of new members of the group and the synergies they created.” Creativity requires
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sufficient input from the outside, not cloistered minds focused on a single mission. Maybe we need to look at productivity differently. Instead of asking, what have you done for the company this week, we should be asking what ideas have you had and what have you done to test them out? In addition, where have you gone to get new ideas, and who have you connected with? The company has to look at its own diversity of strong and weak ties as an asset to be cared for. Diversity of opinions and ideas gives any organization more resilience to deal with change and more potential for innovation. A company’s networked creative surplus can be enabled by first turning off the broadcast noise of the 20th century enterprise. Then it needs to promote internal and external diversity. Channeling our enormous untapped talent is essential in the network era. Ignoring the creative surplus is like leaving money on the table.
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2 WORK IS LEARNING & LEARNING IS THE WORK PKM and the Seek > Sense > Share Framework Simple standards facilitated with a light touch, enables knowledge workers to capture, interpret and share their knowledge. Personal knowledge management is a set of processes, individually constructed, to help each of us make sense of our world and work more effectively. But what we loosely call knowledge, using terms like knowledge-sharing or knowledge capture, is just an approximation. We are not very good at articulating our knowledge, says knowledge management expert Dave Snowden: “We always know more than we can say, and we will always say more than we can write down.” Becoming knowledgeable can be thought of as bits of knowledge partially shared and experienced over time. It is laborious, hence the reason masters through the ages could only have a limited number of apprentices. But when writing, and later books, came along, we had a new technology that could more widely distribute information created by the wise, and the not so wise. Whether being mentored by a master or reading a book, knowledge does not actually get transferred, but shared observations and information can be helpful to those who have a desire to learn. Merely being well-read is not enough to be knowledgeable, as possibly first noted by Socrates. Plato wrote in Phaedrus that Socrates felt the written language would result in ‘men filled, not with wisdom, but with the conceit of wisdom, who will be a burden to their fellows’. Socrates saw a core truth in learning from
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artifacts like books. We cannot become complacent with knowledge and just store it away. It has a shelf life and needs to be used, tested, and experienced. It should be shared amongst people who understand that they are only seeing a fragment of each others’ knowledge. Because it is so difficult to represent our knowledge to others, we have to make every effort to continuously share it. Once is not enough, as most parents know. Knowledge shared in flows over time can help us create better mental pictures than a single piece of knowledge stock, like a book. Capturing knowledge, as crudely as we do, is just a first step. Personal Knowledge Management is a framework for individuals to take control of their professional development through a continuous process of seeking, sensing-making, and sharing. Seeking is finding things out and keeping up to date. Building a network of colleagues is helpful in this regard. It not only allows us to “pull” information, but also have it “pushed” to us by trusted sources. Good curators are valued members of knowledge networks. Sensing is how we personalize information and use it. Sensing includes reflection and putting into practice what we have learned. Often it requires experimentation, as we learn best by doing. Sharing includes exchanging resources, ideas, and experiences with our networks as well as collaborating with our colleagues.
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Figure 2 PKM = Seek > Sense > Share
k
of
c P ra
Te a
or
Comm un ity
Ne tw
Seek
filter
tice
m
Sense
create
Share
discern
• Filter through networks and communities of practice (CoP) • Create individually and with teams • Discern with whom and when to share The multiple pieces of information that we capture and share can increase the frequency of serendipitous connections, especially across organizations and disciplines where real innovation happens. As Steven Johnson, author of Where Good Ideas Come From says, “chance favors the connected mind”.
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Harold Jarche > seeking perpetual beta PKM
may be an individual activity but it is social as well. It is the process by which
we can connect what we learn outside the organization with what need to do inside. Research shows that work teams that need to share complex knowledge need tighter social bonds. Work teams often share a unique language or vocabulary. However, they can become myopic and may lack a diversity of opinions. Social networks, on the other hand, encourage diversity and can sow the seeds of innovation. But it is almost impossible to get work done in social networks due to their lack of structure. PKM is the active process of connecting the innovative ideas that can arise in our social networks with the deadline-driven work inside organizations. In addition to seeking, sensing and sharing, we need to become adept at filtering information as well as discerning when and with whom to share. Like any skill, these require practice and feedback. Much of this can be provided in communities of practice, a half-way space between work teams and social networks, where trusted relationships can form that enable people to share more openly. Connecting social networks, communities of practice and work teams, is an important framework for integrating learning and working in the network era. We seek new ideas from our social networks and then filter them through more focused conversations with our communities of practice, where we have trusted relationships. We make sense of these embryonic ideas by doing new things, either ourselves, or with our work teams. We later share our creations, first with our teams and perhaps later with our communities of practice or even our networks. We use our understanding of our communities and networks to discern with whom and when to share our knowledge. Narrating one’s work does not get knowledge transferred, but it provides a better medium to gain more understanding. Working out loud is a concept that is
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very easy to understand, but not quite so easy to do. Most people are too busy managing in their information age workplaces and have little spare time to try to learn how to work in the network age. The most important step in learning a new skill is the first one. This same step has to be repeated many times before it becomes a habit. I have learned that the first step of starting to work out loud, as part of personal knowledge management, has to be as simple as possible. For example, being able to share is usually not a prime reason why people start using web information capture tools like social bookmarks but it becomes more important over time. Coupled with feed readers (e.g. feedly.com) aggregation makes information flows much easier to deal with. Then you have to connect with people. So how do you get started micro-blogging on a platform like Twitter? I suggest beginning with an aim in mind, such as professional development or staying current in a specific field. The search function can help find people who post about a specific topics. To start, you should follow between 20 and 30 interesting people. Once set up, beginners should dip into their stream once or twice a day and read through any posts of interest. Over time, as they follow links, they may add or delete feeds. Within a week or two, anyone should be able to sense some patterns and then modify their streams to provide more signal and less noise. Sometimes we get all caught up in the latest social media tools. Getting started working out loud is not complicated and should not involve a steep learning curve on a complicated system. It is best to start with simple tools and frameworks. The mainstream application of knowledge management and learning management over the past few decades is mostly wrong; we over-managed information, knowledge and learning because it was easy. Our organizations remain Jarche.com > 2004–2014
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enamoured with the next wave of enterprise software systems. But the ubiquity of information outside the organization is showing the weakness of centralized enterprise systems. As organizations begin to understand the Web, the principle of small pieces loosely joined is permeating some thick industrial age walls. More workers have their own sources of information and knowledge, often on mobile devices, but they usually lack the means or internal support to connect their knowledge with others to actually get work done. Supporting PKM , especially internal sharing, can help information flow more freely. Personal knowledge management frameworks help knowledge workers capture and make sense of their knowledge. Simple standards can facilitate this sharing. Knowledge bases and traditional KM systems should focus on essential information, and what is necessary for inexperienced workers. Experienced workers should not be constrained by too much structure, but be given the flexibility to contribute how and where they think best helps the organization. We know that formal instruction accounts for less than 10% of workplace learning. The same rule of thumb should apply to knowledge management. Capture and codify the 10% that is essential, especially for new employees. Now use the same principle to get work done. Structure the essential 10% and leave the rest unstructured, but networked, so that workers can group as needed to get work done. Many organizations are too slow and hierarchical to be useful for knowledge-sharing in the network era. Organizations structured around looser hierarchies and stronger knowledge networks are much more effective for increasingly complex work.
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PKM and Competitive Intelligence Competitive Intelligence is a combination of collecting, collating, analyzing and disseminating intelligence about the market and the business environment to make strategic decisions. Several years ago I advised a client on how to develop a CI process: 1. Start by asking questions internally and seeing what kind of answers you get. Use your existing social media tools to do this. 2. As a distributed team, each person can be responsible for a specific information source that is monitored regularly. This should be narrated and posted for all to see and comment. 3. Ask a weekly question and see who can get some information that may be able to answer part or all of it. 4. In the feedback to these questions people may ask you to re-frame the questions. Continue to learn and refine this process for your unique context. Better questions will make for better Competitive Intelligence. Keep this process visible. 5. You may not need to hire anyone else to collate the data, but if you do, keep your team (who have industry knowledge) involved. 6. Don’t just hand Competitive Intelligence over to a junior staff member. Competitive Intelligence should be part of the conversational flow in the company. Marketing, sales, developers and management should be actively involved.
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7. The process of asking questions, seeing if there are answers and in turn asking questions about the questions can hone the team’s ability to gather competitive intelligence. 8. If you decide to purchase access to information sources, only buy one at a time. Use that source as much as you can (squeeze it dry) until you realize you should eliminate it or augment it with another purchased source. Competitive Intelligence, like knowledge management, needs people to be continuously involved and engaged; it is really just a focused type of knowledge management. Therefore, people with good personal knowledge management skills should also be better contributors to Competitive Intelligence.
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PKM and Innovation Scott Anthony, in researching his book, The Little Black Book of Innovation (2011), found four skills that most successful innovators exhibit. 1. Questioning: Asking probing questions that impose or remove constraints. Example: What if we were legally prohibited from selling to our current customer? 2. Networking: Interacting with people from different backgrounds who provide access to new ways of thinking. 3. Observing: Watching the world around them for surprising stimuli. 4. Experimenting: Consciously complicating their lives by trying new things or going to new places. One way to practice these skills would be to promote personal knowledge management in the workplace. The Seek > Sense > Share framework aligns with these innovation skills. Seeking includes observation through effective filters and diverse sources of information. Sense-making starts with questioning our observations and includes experimenting, or probing (Probe-Sense-Respond). Sharing through our networks helps to develop better feedback loops. In an organization where everyone is practising PKM , the chances for more connections increases. Innovation is not so much about having ideas, as making more and better connections. Innovation is inextricably linked to both networks and learning. We can’t be innovative unless we integrate learning into our work. It sounds easy, but it’s a major
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cultural change. Why? Because it questions our basic Taylorist assumptions about work, such as: • A job can be described as a series of competencies that can be filled by the best qualified person. • Somebody in a classroom, separate from the work environment, can teach you all you need to know. • The higher you are on the organization chart, the more you know (one of the underlying premises of job competency models). PKM
is a framework that enables the re-integration of learning and work and can
help to increase our potential for innovation. It’s time to design workplaces for individuals, and their Personal KM , instead of getting everyone to conform to a sub-optimal structure that maximizes capital but not labour. Knowledge is the new capital, but it resides in each person’s head. To address complex problems, businesses have to rely more on individual tacit knowledge, and this type of knowledge is never easy to convey to others. It takes time and especially trust to make multiple attempts at clarification. Accepting PKM
as a flowing series of half-baked ideas can encourage innovation and reduce
the feeling that our exposed knowledge has to be executive presentation perfect. Workplaces that enable learning in a trusted space can expose more tacit knowledge. We can foster innovation by accepting that our collective understanding is in a state of perpetual Beta. This is how we can create a culture of innovation.
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Managing Organizational Knowledge Organizational knowledge is a mixture of explicit and implicit knowledge sharing. It can be as explicit as Harvard Business School’s Institutional Memory site, or as implicit as the feeling one gets from a well-known local legend. A lot depends on what the organization wants to preserve. Is it how-to knowledge, like a trade secret formula, or is it certain practices and norms that define the culture? Or is it both? Each institution has to define this for itself. Implicit knowledge is difficult to share and is usually complex. We know that this type of knowledge cannot easily be codified. However, this is often what gives institutions competitive advantage. Finding ways to collect and share implicit and explicit knowledge is important for organizational knowledge. Stories can be an effective medium for these exchanges. For example, the Ritz-Carlton provides an excellent example by publishing Stories that Stay with You. These stories do not have to be exceptional to be effective, just human. Simple anecdotes may be better on a large scale, rather than sweeping epics. Complex work, which is growing in importance in networked organizations, requires more sharing of implicit knowledge and this presents certain challenges. Explicit knowledge is easier to codify and more suitable for enterprise-wide initiatives. Implicit knowledge requires personal interpretation and engagement to make sense of it. Understanding how best to commit resources for knowledge-sharing should be in some kind of a decision-making framework that is easy for anyone to understand. Organizational knowledge can be strengthened with a firm foundation of personal knowledge management (Seek > Sense > Share). While seeking and sense-making are mostly individual activities and people should be allowed to
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use what’s best for them, the organization can overtly support knowledge sharing. One suggestion is to create more opportunities for people to have coffee together. Though it’s not the coffee that’s important, the act of gathering, combined with an environment that encourages capturing and sharing knowledge artifacts, serves to build organizational knowledge. Event memories can be captured as knowledge artifacts, but each is limited by what it can convey, depending on its nature and the knowledge of the recipient. Decision memories usually have a certain importance for organizations — to understand why decisions were, or were not, taken. Institutional decision memories can describe how & why an organization chose one course of action over another. Knowledge management (KM) can provide a structure to capture institutional memories, but it requires more than a single approach. Over time, memories can be codified and institutionalized. This is enterprise KM , leveraging the power of enterprise software platforms to store decision, process, and event memories. Process and event memories, like project outputs, are relatively easy to capture and codify. But decision memories are often hampered by our tendency to justify decisions after they have been made, and even create elaborate, and often fictional, stories around them. For this reason, it is important to capture decisions as they are being made, not after the fact. Explaining why other decisions were not made, should also be normal practice. For example, I was working with a client that made decisions on which chemical compound to develop out of a possibility of thousands. There was a significant cost to initially create any compound, so not all possibilities could be attempted. Decisions were made by a committee on which compound to pursue. However, the decisions on why the other compounds were not developed were never recorded. Several years later, the situation had changed due to improvements in
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technology and new research findings, and now some of the rejected compounds may have had potential for development. Unfortunately, no records were available to search the rejected compound database and find ones that met the new criteria. Sometimes our decisions not to do something are just as important as our selected course of action, from the perspective of the future. But we never know this in advance. Recording and sharing our knowledge on a regular basis is what group KM practice is about, as it focuses on providing ways for teams and projects to try new methods safely. Examples include curation, communities of practice, and mentoring. For complex work, group KM is critical, as most of the knowledge required is implicit. According to the Cynefin framework, developed by Dave Snowden and Cynthia Kurtz, in the Complex domain “the relationship between cause and effect can only be perceived in retrospect, but not in advance, the approach is to Probe — Sense — Respond (P–S–R) and we can develop emergent practices”. Teams working in the complex domain have to make probes on a regular basis in order to understand the changing environment. It then becomes essential to develop ways to capture and share the decisions made with each one. Good institutional memory requires strong personal knowledge management among a majority of the workforce. PKM is an ongoing process of filtering information from our networks; creating knowledge individually and with our teams, and then discerning with whom and when to share the artifacts of our knowledge. As educational researcher Roger Schank states, “Comprehension is mapping your stories onto mine.” PKM helps to put our maps out there for others to see. Knowledge management is nothing without people engaged in the process. Viola Spolin, creator of the Theater Games actor training system, says that, “Information is a weak form of communication.” But it can be improved, as actor
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trainer Gary Schwartz notes, “Story becomes important in the ordering of all this information.” Stories are the glue, holding information together in some semblance of order, for our brains to process into knowledge.
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Training and Complex Work The novelist William Gibson said, “The future is already here — it’s just not evenly distributed.” The near future will look like the near past, with more complex social and technological connections inside and outside organizations. The rapid pace of change is unlikely to abate in the near future. One thing is obvious, however: Learning is becoming more collaborative. In just the past year, we have seen several advancements, introductions and evolutions in the world of learning. Silicon Valley and Ivy League schools are opening up their courses for free online. Massively Open Online Courses (MOOCs) , as they’re called, are initiatives hoping to disrupt higher education. Learning management systems have become talent management or social collaboration systems as they try to increase their relevance beyond training. Last year I worked with a client that had reduced its corporate university staff by over half and outsourced all course development. Recently, McGill University management professor Karl Moore, in Forbes magazine, asked, “Is the traditional corporate university dead?” From this, it’s clear — traditional training structures, based on institutions, programs, courses and classes, are changing. Probably the biggest change we are seeing in online training is that the content delivery model is being replaced by more social and collaborative frameworks. This is due to almost universal Internet connectivity, especially with mobile devices, as well as a growing familiarity with online social networks such as Facebook and LinkedIn. What follows is a list of near-term trends that should be taken into consideration by learning professionals during the next year.
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We should consider that, for all intents and purposes, the industrial era, including the information age, is over. We have entered the network era, and work will never be the same. What were considered good, dependable jobs in the 20th century are now getting either automated or outsourced. Automated tellers have replaced thousands of bank clerks, but even more advanced jobs are getting automated as we connect the world with computers. The New York Times reported in March of 2011 that armies of expensive lawyers, who once did discovery work, have been replaced by software programs that do the work at a fraction of the cost. This applies to computer chip designers, loan officers, tax accountants and others. It’s not just automation. Any work that can be outsourced is going to the place of cheapest labor, wherever in the world that may be. The Internet enables hyper-competition, destroying geographical barriers for anything that can be digitized. This includes any information and visual products, from creative writing, to photography and video, to radiological images. For knowledge workers, there is diminishing value in standardized work, as it will be either automated or outsourced over time. That leaves higher task-variety, non-standardized work, which is complex, creative or both. How does complex work differ from complicated work, the mainstay of many workplaces for the past half-century? In complex work there are no best practices or even good practices, just emergent practices that have to be developed as the work gets done. Consider that in the network era workplace, neither training nor education will be able to completely prepare workers for doing complex work. Higher task variety means a growing use, and demand for, informal learning opportunities and a greater use of implicit knowledge, which is difficult to share with others.
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In complex environments, the relationship between cause and effect can only be perceived in retrospect, not in advance. It’s like raising children. This is the situation more workers find themselves in today. In these complex environments, a Probe-Sense-Respond approach is required, and this is something that training and education programs, designed in advance and directed by management, cannot address. While people still need to be trained and educated, that alone will not prepare them for a networked workplace that requires more informal learning. They will need to learn while they are working, in a social, collaborative environment. One challenge for the training department is that the Probe-Sense-Respond framework throws the linear course development model, which advocates design in advance, out the window. The increasing complexity of our workplaces means we have to accept the limitations of training and education as we have practiced them. We need to help people be more creative and solve complex problems, which are skills often outside of the training program scope. Training departments need to add more thought and resources to enable people to learn socially, share cooperatively, and work collaboratively.
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Narrating Our Work Networked learning is changing the training world. Many learners now own their knowledge-sharing networks. What does it mean to own a knowledge-sharing network? Today, content capture and creation tools let people tell their own stories and weave these together to share in their networks. It’s called narrating your work and has been done by coders and programmers for decades as they learn out loud. What started as forums and wikis quickly evolved into more robust networks and communities. Programmers who share their work process and solutions in public are building a resource for other programmers looking to do the same type of work. This makes the whole programming environment smarter. Organizations can do the same. The public narration of what we do, attempt and learn on a daily basis not only helps us help others, but also puts us in a position to get help from peers. When your co-workers know what you’re working on and what problems you run into, they can offer their experience. Still, these days, few people work in the same room as all their co-workers, so they rely on the Internet to offer them a common space to find and offer work narration. Narration helps everyone get smarter. John Stepper, managing director at Deutsche Bank, says that everyone should work and learn out loud. If you’re confused about what to write, Stepper suggests posting about what you’re working on every day, who you’re meeting with, the research you’re doing, the articles you find relevant, lessons you learned and mistakes you made. These insights are valuable to people trying to train others how to do similar things. He also recommends creating short posts that are easy-to-skim, making this kind of narration practical for both the author and the audience.
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Narration is turning one’s tacit knowledge — what you know — into explicit knowledge — what you can share. Developing good narration skills takes time and practice. Just adding finished reports to a knowledge base does not help others understand how that report was developed. This is where online activity streams and micro-blogging, like Yammer, have helped organizational learning. People can see the flow of work in small bits of conversation that, over time, become patterns. Narration of work is the first step in integrating learning into the workflow. Online learning can be looked at as either stock or flow. Stock is organized for reference and does not change frequently. Courses are stock. Flow is timely and engaging. Narration of work in social networks is flow. With access to more learning flow, via social technologies, highly networked workers can have a much broader, deeper and richer learning experience than any workplace learning professional could ever design in advance. A worker today can ask questions to a worldwide support network on a platform like Twitter and get an answer in minutes. Deeper questions can be addressed on a service like Quora, where responses get voted on by the community. Many experts worldwide are now narrating their work and making it freely available on the Internet. A new form of distributed cognitive apprenticeship is now available, and knowledge workers are taking advantage of this. Training departments should put a greater emphasis on learning flow. Stories are an excellent example of learning flow. For millennia, we have learned through
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stories. This is how gamers and hackers, the digital pioneers, have learned how to learn without curriculum, courses or instructors: They share their stories. They know there is no user manual. They embrace the flow. Ensuring knowledge flow entails the capture and creation of digital artifacts. Try to share as much as possible. Make sharing the default action by offering entrance into social networks to everyone. [e.g. feed readers, social bookmarks, blogs, photos, videos, social networks, activity streams]. Keep everything open and transparent [do not create walled gardens] as the key to useful information is being able to find it. Support easy-to-make connections; between people, and with digital resources.
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Collaborate to Solve Complex Problems Communities of practice are groups of people who share a passion for something that they know how to do and who interact regularly to learn how to do it better. —Etienne Wenger
Communities of practice should be thought of as networks, not cohesive groups. In a network, joint activities are cooperative and non-directive. No one is completely in charge. Communities and networks exemplify complexity, with fuzzy boundaries, shifting cultures and semi-autonomous members. Networked communities are good structures for dealing with complexity, where emerging practices can be tested and loose social ties can help facilitate faster learning feedback loops without hierarchical constraints. Effective communities of practice can help solve problems, retain talent and develop new strategies. They are not bound by reporting lines, so knowledge can flow freely. Supporting online communities of practice is a lot like dancing, there’s constant give and take. Consider a community a dance space, where some people are skilled and others less so, while in fleeting but pervasive contact with partners of varying abilities. It’s a constantly negotiated space, dependent on who shows up, who plays and who dances. Thriving in this community depends on getting introduced to the right people; some to dance with and others to talk to. This is the job of the community manager, a new and growing role for training and development.
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Here are some guidelines for community managers, based on several years of observing and being engaged in online communities. • Communities often don’t grow the way they are planned. Design communities for change, with flexible boundaries and structures. • Communities don’t want to be managed — they want to be nurtured. Community managers must lead with a gentle hand. • Building community means giving up control. There is a constant dynamic tension in communities over control versus member empowerment. • Building community is not about collecting as many people as possible. Community managers should focus on improving the quality of conversations and knowledge-sharing, not the quantity. • Make all learning initiatives collaborative Training professionals used to have it relatively easy. They only had to run courses and send people off to work. Online courses replicated the classroom. But online communities are not like classrooms. Now that we are all connected by networks, more of our work is dependent on others — and so is our learning. The future of online training is in improving collaboration. Basically, most workers are only paid to do one thing — solve problems. But it is getting much more difficult to do this on our own, as author Robert Kelley at Carnegie Mellon University showed in research for his book, How to be a Star at Work (1999). In interviewing knowledge workers, Kelley found that most people just don’t have all the knowledge in their heads to do their work any more, and in some cases it was less than 10%. Workers need to collaborate and share their knowledge. This is where learning professionals can help, by improving online collaboration and knowledge-sharing.
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Shifting from an online content delivery to a collaboration focus enables the training department to concentrate on work performance — not learning, and not knowledge. “How can we help you work?” should be the mantra of all training departments. Helping people work together is the mission. The primary function of learning professionals should be connecting and communicating, based on three core processes: 1. Facilitating collaborative work and learning amongst workers, especially as peers. 2. Sensing patterns and helping to develop better shared-workplace learning practices. 3. Working with management to fund and develop appropriate new tools and collaboration processes.
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3 LEADING & MANAGING IN NETWORKS Network Thinking One major challenge in helping organizations improve collaboration and knowledge-sharing is getting people to see themselves as nodes in various networks, with different types of relationships between them. Network thinking can fundamentally change our view of hierarchical relationships. For example, using value network analysis, I helped a steering group see their community of practice in a new light, mapped as a network. They immediately realized that they were pushing solutions to their community, instead of listening to what was happening. Thinking in terms of networks, networks, networks lets us see with new eyes.
Figure 3 Trust Emerges Through Openness and Transparency
social networks openness
enables
transparency
knowledge sharing
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trust fosters
reinforces
diversity of ideas
innovation
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A new social contract for creative work is needed. First we must abolish the organization chart and replace it with a network diagram. Some new technology companies have done this. Then we can move away from counting hours, to a results only work environment. With distributed work, this is becoming more common. Organizations should encourage outside work that doesn’t directly interfere with paid work, as it will strengthen the network. There should be options for workers to come and go and even stay connected when they’re not employed (like Ericsson’s Stay Connected Facebook group). Thinking in terms of networks means building an ecosystem, not a monolith. As we learn in digital networks, content loses significance, while conversation becomes more important — the challenge is to continuously weave the many bits of information and knowledge that pass by us each day. Conversations help us make sense. But we need diversity in our conversations or we become insular. We cannot predict what will emerge from continuous learning, co-creating & sharing at the individual, organizational and market level but we do know it will make for more resilient organizations. A professional learning network, with its redundant connections, repetition of information and indirect communications, is a much more resilient system than any designed development program can be. Redundancy is also a good principal for supporting social learning diffusion. There is always more than one way to communicate or find something and just because something was blogged, tweeted or posted does not mean it will be understood and eventually internalized as actionable knowledge. The more complex or novel the idea, the more time it will take to be understood. Programmers say that you are only as good as your code. Credentials and certifications often act as blinders and stop us from recognizing the complexity of
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a situation. As Henry Mencken wrote, “For every complex problem there is an answer that is clear, simple, and wrong.” We should not let credentials lull us into a false sense of expertise. Working smarter starts by organizing to embrace diversity and manage complexity. Diversity is a key factor in innovation and all organizations need to improve innovation. Networks can offer greater diversity than any hierarchy can.
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The Connected Enterprise It’s all about thriving in networks that are smarter and faster than you are. It’s all about being utterly screwed if you don’t know what I’m talking about. —Hugh MacLeod
Our dominant business models are the legacy of military hierarchies. But in a networked world these are inefficient, ineffective, and stifle innovation. Not a single major business disaster in the last half-century can be blamed on too much openness. However, many can be blamed on overly controlling management practices. The problem with hierarchies is that they are only as smart as the smartest gatekeepers. Networks are smarter than the sum of their nodes. Business models that enable connected leadership are essential in a network era. Structures + Skills + Tools The innovative work structures required for increasingly complex networked economies need to be supported by skilled workers with the right tools. We know that sharing complex knowledge requires strong interpersonal relationships, with shared values, concepts, and mutual trust. But discovering innovative ideas usually comes via loose personal ties and diverse networks. Knowledge intensive organizations need to be structured for both strong and weak ties. Effective knowledge-sharing drives business value in a complex economy and this requires a workforce that is adept at sense-making. In a connected enterprise, capabilities need to be aligned with tools. A core requirement for both knowledge workers, and enterprise tools, is to share what we are learning and doing. Making work more explicit enables the organization to learn. Sharing user-generated content (knowledge artifacts) is how everyone
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can make tacit knowledge more explicit. Work is learning and learning is the work, when everyone shares. Of course this is more difficult if communications systems do not allow the easy creation and sharing of this content. Tools have to support the work. Most organizations have tools that support working together for a common objective. Coordinating tasks, conducting meetings that don’t waste time, and finding expertise are common collaborative tasks. Letting workers pick their own collaboration tools can go a long way in getting work done. Having an array of tools is also helpful. Modelling collaboration skills throughout the enterprise is even better. When people share openly, without any direct gain, knowledge networks thrive and the organization benefits. Cooperative skills include sharing openly with colleagues, communicating effectively, and networking to improve business performance. In addition, social media require new skills, beyond traditional faceto-face interchanges. Setting sharing as a default behaviour is a good start, but providing tools to enable sharing is also needed. As with collaboration, cooperative behaviours need to be modelled and encouraged. A combination of organizational structure changes, skills development and modelling, plus a suite of tools, can help to create a connected enterprise. All three are needed. Focusing on only one or two areas will likely not yield much success. This has been a problem with many social business initiatives which are too focused on the tools, like enterprise social networks (ESN) . While an ESN may cover all the required facets, workers still need to have the required skills. In addition, the structure must support these behaviours on an ongoing basis. It takes all three components.
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The Knowledge Sharing Paradox An effective suite of enterprise social tools can help organizations share knowledge, collaborate, and cooperate — connecting the work being done with the identification of new opportunities and ideas. In an age when everything is connected, it only makes sense to have platforms in place that enable faster feedback loops inside the organization in order to deal with connected customers, suppliers, partners, and competitors. It takes a networked organization, staffed by people with networked mindsets, to thrive in a networked economy. Getting work done today means finding a balance between sharing complex knowledge (collaboration) and seeking innovation in internet time (cooperation). Individual workers can develop sense-making skills, using frameworks like PKM , to continuously learn and put their learning to work. For example, they can seek new ideas from their social networks; make sense of these ideas by connecting with communities of practice; try new ideas out alone or with their work teams; and then share these ideas and practices. But there is a major issue that gets ignored by software vendors, managers, IT departments, and almost everyone except the workers themselves. People will freely share their knowledge if they remain in control of it. Knowledge is a very personal thing. Most workers do not care about organizational knowledge bases. They care about what they need to get work done. However, if we are going to build organizational knowledge from individual knowledge-sharing, we have to connect the two. The knowledge sharing paradox is that enterprise social tools constrain what they are supposed to enhance. Why would someone share everything they know on an enterprise network, knowing that on the inevitable day that they leave, their
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knowledge artifacts will remain behind? I could not imagine having this blog (my outboard brain) cut off from me. I would not put in anywhere near the effort I do now if someone else controlled my access to this blog. The elephant in the room is human nature. Enterprise knowledge sharing will never be as good as what networked individuals can do. Individuals who own their knowledge networks will invest more in them. I think this means that innovation outside of organizations will continue to evolve faster than inside. It may mean that the half-life of organizations will continue to decrease, as more nimble businesses continuously emerge to compete with incumbents. Whoever creates an organizational structure that bridges the individual-organizational knowledge sharing divide may have significant business advantages.
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Managing Automation It is fairly obvious that standardized work will keep getting automated, by software or robots. Addressing this technology-driven shift should be a high priority for everyone, from unions, to governments, and human resource professionals. As we move into a post-job economy, society needs to restructure how work gets done and how it is compensated. While this is a macro issue, there are some things that can be done within the enterprise right now. Companies that implement these changes could be in a much better position as the creative economy rises to dominate agricultural, manufacturing, and information economies. If the future of management is talent development, what does this mean on a day to day basis? One small change that could have a major impact would be to look at everyone’s work from the perspective of standardized versus customized work. Every person in the company, with the help of some data and peer feedback, should be able to determine what percentage of their time is spent on standardized work. If the percentage is over a certain threshold, say 50%, then it becomes a management task to change that person’s job and add more customized work. The company should be constantly looking at ways to automate any standardized work, in order to stay ahead of the forces of automation, the market, and the competition. Automation is pretty well inevitable but it does not have to decimate the workforce. Looking at the overall company balance between standardized and customized work should be an indicator of its potential to succeed. By visualizing the Routine (Labour) versus Customized (Talent) split, people in the company can take action and make plans before the inevitable shift. This of course means that jobs and roles have to become more flexible and open to change. But this is a post-job
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economy we are moving toward. We cannot stay tied to the concept of the job as the primary way to work. Building ways to constantly change roles will be one way to get rid of the standardized job, which has no place in a creative economy. This one small change could have a major impact on any organization. It just requires a slightly new way of looking at work, collecting good data, engaging workers in the process, and being transparent about it all. Most of all, it requires companies and managers who really care about talent development. The reality that treating workers like Talent, not replaceable and low cost Labour, can actually increase revenue is starting to make an impact, even where it is not quite so obvious — the retail sector. Getting staff to focus on customized work, or dealing with each unique customer need, pays dividends in the long term.
Jarche.com > 2004–2014
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Flip the Office Think of all the time wasted in the typical workplace just consuming — listening at meetings; reading directives, waiting for someone to make a decision; commuting; etc. Imagine what could happen if an entire organization decides to tap into its collective cognitive surplus. Why do we have physical workplaces? To get work done, one assumes. But if you ask people, especially knowledge workers, where they are most productive, it’s not likely to be at their office. They waste a lot of time at work, the main culprits being email, meetings, and constant interruptions. It makes little sense to ship millions of people to offices every day in order to be less productive than they could be. So what are offices for in the network era? They should be for collaborating, discussing, and getting to know each other better. People should not have to go to an office to work alone. Knowledge management expert Nancy Dixon says that, “Forcing people back to the workplace [to be more productive] is not the solution because too often when they are in the workplace they are either sitting in a meeting listening to endless presentations, or in a cubicle sending emails to each other. Neither of those activities is worth the cost in time or travel.” We know that many collaborative activities are best conducted face to face. The physical workplace should support and encourage meaningful conversations, between ourselves or with our clients. We have the software to handle scheduling so that most workers could have the opportunity to be productive for most of their days. It’s time to flip the office. Instead of going to work, we should be going to socialize, converse, and collaborate. Productive solo time is not for the office. Knowledge workers can be productive anywhere but at the office.
Jarche.com > 2004–2014
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Connected Leadership Leadership training usually does not work. In most cases, leadership coaching and mentoring is not that effective either. Perhaps the problem is the nature of leadership. Is it a skill that can be fairly quickly developed, or rather a craft that takes time to develop? When it comes to crafts that require much time and practice, modelling may be a better method than shaping. Education and training are shaping technologies. They reward successive approximations of the desired behaviour. Modelling, on the other hand, is the foundation of social learning. Trying to directly shape behaviour can work when the task to be done is straight-forward, time is of the essence, and the learner is ready. For complex behaviours like leadership, consisting of several skills, modelling may be best, as there is much implicit knowledge to be learned, which takes time. Education and training usually don’t provide the time for enough reflective practice. As long-time Canadian painter Stephen Scott has noted, most of what he knows about the technique of oil painting he learned on his own after leaving university. Management and leadership are similar types of abilities. If we look at how organizational training and development has functioned over the past half century, it has been mostly separate from the work being done and focused on shaping behaviours. But the valued work in the enterprise is shifting, as it increases in variety and decreases in standardization. There is strong evidence that we need to integrate learning into our work in order to deal with the increasing complexity of knowledge work. Modelling is integrative, while shaping is usually external and out of the work context. Consider also that as knowledge expands and new information is constantly added, who has the base knowledge to do the shaping anyway? In our networked
Jarche.com > 2004–2014
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world, modelling behaviours may be a better strategy than shaping on any pre-defined curriculum. With modelling, the learner is progressively supported. In connected leadership, people can be both teachers and learners. Therefore neither training programs, nor coaching are enough. Leadership by example becomes the key. Connected leadership is not the status quo and it is not based on “great man” theories. As organizations, markets, and society become networked, complexity in all human endeavours increases. There are more variables as a result of more connections. In complex adaptive systems, the relationship between cause and effect can only be known after the fact. This makes traditional planning and control obsolete. Connected organizations must learn how to deal with ambiguity and complexity. Those in positions of leadership have to find ways to nurture creativity and critical thinking. The connected workplace is all about understanding networks, modelling networked learning, and strengthening networks. In networks, anyone can show leadership, not just those appointed by management. A guiding principle for connected organizational design is for loose hierarchies and strong networks. As networked, distributed work becomes the norm, trust will emerge from environments that are open, transparent, and diverse. Strengthening professional social networks will ensure that knowledge is shared and contributes to organizational longevity. Connected organizations need to learn as fast as their environments. As a result of this improved trust in the workplace, leadership will be seen for what it is — an emergent property of a network in balance and not some special property available to only the select few. This requires leadership from everyone — an aggressively intelligent and engaged workforce, learning with each other. In
Jarche.com > 2004–2014
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the connected workplace, it is a significant disadvantage to not actively participate in social learning networks. Leadership in networks does not come from above, as there is no top. To know the culture of the workplace, one must be the culture. Marinate in it and understand it. This cannot be done while trying to control the culture. Organizational resilience is strengthened when those in leadership roles let go of control. The connected workplace requires collaboration as well as cooperation. Both collaborative behaviours (working together for a common goal) and cooperative behaviours (sharing freely without any quid pro quo) are needed, but most organizations today focus their efforts on shorter term collaboration. However, networks really thrive on cooperation, where people share without any direct benefit. Modelling cooperation is another important leadership skill in the connected workplace. Connected leaders know that people naturally like to be helpful and get recognition for their work. But humans need more than extrinsic compensation, as our behaviour on Wikipedia and online social networks proves. For the most part, people like to help others. Cooperation makes for more resilient knowledge networks. Better networks are better for business. Research shows that tacit knowledge flows best in trusted networks. Trust promotes individual autonomy and this becomes a foundation for more open social learning. Without trust, few are willing to share their knowledge. An effective knowledge network also cultivates the diversity and autonomy of each worker. Connected leaders know how to foster deeper connections which can be developed through meaningful conversations. They understand the importance of tacit knowledge in solving complex problems.
Jarche.com > 2004–2014
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The power of human social networks, like electricity, will inevitably change almost every business model. Those who are trusted as leaders will need to understand the new connected workplace. Connected leadership starts by organizing to embrace networks, manage complexity, and build trust. Managers, acting as servant leaders in a connected enterprise, should spend much of their time focused on complex situations, where the relationship between cause and effect can only be seen after the fact. Actively listening requires an engagement with networked contributors who are closely in touch with their environment. Everyone should continuously question the contexts in which the enterprise is working. Appointed servant leaders have an even greater responsibility to look at the big picture, not manage the contributors, who for the most part can manage themselves when everyone’s work is transparent. Leaders can then propose changes and build consensus around suggested responses. Connected leadership is helping the network make better decisions.
Figure 4 Connected Leadership Temporary Hierarchies + Strong Networks
networked contributors transparent diverse
Actively listen
open
Question the context Sense & review
Propose changes Build consensus Suggest responses
servant leaders Jarche.com > 2004–2014
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4 THE GLOBAL VILLAGE At the highest level, we are changing the way we organize as a society. This has only happened twice before — when we shifted from a predominantly oral & tribal society to a written & institutional one, and when Gutenberg’s press shifted us to a print & market society. The emerging form (Networks) is not a mere modifier of previous forms (Tribes, Institutions, & Markets), but a form in itself that may be able to address complex societal issues that the previous forms cannot. This is why changing how we work seems critical to so many people today.
Figure 5 Organizing Characteristics Domain (Cynefin)
Society (TIMN)
Communication Medium
Practice (Cynefin)
Work
Chaotic
Tribal
Oral
Novel Practices
Action
Simple
+Institutions
Written
Best Practices
Coordination
Complicated
+Markets
Print
Good Practices
Collaboration
Complex
+Networks
Digital
Emergent Practices
Cooperation
David Ronfeldt’s TIMN framework [Tribes-Institutions-Markets-Networks] shows how we have evolved as a civilization. It has not been a clean progression from one organizing mode to the next but rather each new form built upon and changed the previous mode. We are currently a predominantly triform society (T+I+M) .
But what happens as we become a quadriform society (T+I+M+N) ?
Jarche.com > 2004–2014
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has long maintained that, beyond today’s common claims that
government or market is the solution, we are entering a new era in which it will be said that the network is the solution (e.g., here and here). Aging contentions that turning to “the government” or “the market” is the way to address particular public-policy issues will eventually give way to innovative ideas that “the network” is the optimal solution. —David Ronfeldt
One key point of this framework is that Tribes continue to exist within Institutions, Markets and Networks. We never lose our affinity for community groups or family, but each mode brings new factors that influence our previous modes. For example, tribalism is alive and well in online social networks. It’s just not the same tribalism of several hundred years ago. Each transition also has its hazards. For instance, while tribal societies may result in nepotism, networked societies can lead to deception. Network societies and tribes have something in common. They are mainly cooperative, where people share without any requirement for reciprocity. What was kinship in tribes, is seen as connections or affinities in networks. When the rules are clear (as in institutions and markets) and we know who we are working with (suppliers, partners, customers) then collaboration, working together for a common objective, is optimal. But in networks, someone may be our supplier or even our boss one day and our customer the next, so cooperation becomes the best behaviour. In such a society, people can have multiple valences as nodes in many networks at the same time. Successful individuals in a network society will see that their connections change over time, and that openly sharing will make them more valued nodes in the long run. In networks, cooperation is simultaneously altruistic and selfish. Jarche.com > 2004–2014
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Figure 6 TIMN (David Ronfeldt)
large scale
Market
Network
Institution
Tribal
collaborative
cooperative
competition
small scale
hierarchy
connection
kinship
According to Marshall McLuhan’s tetrad of media effects, from the laws of media, every medium 1) extends a human property; 2) obsolesces the previous medium; 3) retrieves a much older medium that was obsolesced before; 4) flips or reverses its properties into the opposite effect when pushed to its limits. The medium of a network society could then be seen to extend civil society; obsolesce hierarchies; retrieve the cooperation of kinship; and when pushed to its limits, reverse into deception. In a network society, collaboration is outdated.
Jarche.com > 2004–2014
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Figure 7 Tetrad of a Networked Society
REVERSE
EXTEND
into deception
civil society
network society RETRIEVE cooperation
OBSOLESCE hierarchies
Once again using a term from Marshall McLuhan, we are becoming a global village, and like a tribal village, certain aspects of human behaviours that we have ignored for centuries are becoming important as we move into a network society. For instance, there was little privacy in the village, as there seems to be no more privacy today. While we will not repeat the past, there is much we can learn from it. Our new business practices should not just celebrate what we have made obsolete, but we should also look back to see what we can retrieve and most importantly, what reversals we can avoid. > Jarche.com > 2004–2014
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Colophon Design, layout, & illustration by Christopher Mackay of Tantramar Interactive Inc. Set in Hoefler & Co.’s Whitney. Software: • Adobe InDesign CC — page layout • OmniGraffle Professional 6, Adobe Illustrator CC, & Adobe Photoshop CC — graphics & illustration • Smile Software PDFpen Pro 6.1 & PDFpen 1.7 — PDF workflow
Jarche.com > 2004–2014
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