Km Forecasting

Knowledge Management Forecasting For any knowledge management forecasting exercise to be at least reasonable in its overall analysis one needs to understand the history of knowledge management, where it is today and where it might be tomorrow given the most likely business environment in the medium-term future. In other words, an accurate as-is picture of knowledge management needs to be generated, the to-be image needs to be conceptualized and then a clearly articulated transition strategy from the as-is state to the to-be state is to be put forth. The knowledge management v1.0 era was often defined by its emphasis on the creation of containers of knowledge that were supposed to store the employees’ explicit knowledge into tacit knowledge form. The early approaches to knowledge management leaned heavily toward top-down, organizational-wide, monolithic knowledge management guidelines with a heavy emphasis on technology as a way of connecting people-to-content. Without a holistic approach to implementing a knowledge management strategy that would include creating the necessary change in corporate culture, the efforts made on creating the containers of knowledge failed, as the new digital libraries were void of relevant content, were awkward to use and as a result usage rates were low. This failure of implementation has led to the unsatisfied user syndrome in the context of first (1st) generation knowledge management as the experience for many users has been no more than that of saving and/or retrieving information and asking and/or answering questions. As a result, the perceptions built around those early knowledge management initiatives were that they were yet another attempt to automate knowledge capture and reuse, that they were complex, costly, difficult to use and overly bureaucratic. Most importantly they were not helping employees make their jobs any easier nor better. Overall most companies did a poor job of capitalizing on the wealth of expertise scattered across their organizations due to their over-reliance on centralized knowledge management systems and technologies. What was not fully understood was that such systems were really only good at distributing explicit knowledge, the kind that could be captured and codified for general use. They were not very good at transferring tacit knowledge, the kind needed to generate new insights and creative ways of tackling business problems and opportunities. The knowledge management v2.0 era learned from previous experiences and its emphasis swung to focus on people and ways of identifying employees holding expert knowledge and connecting people-to-people. The knowledge management implementation approach became increasingly holistic moving beyond technological tools to include the necessary changes in the other dimensions of operational performance such as people, processes, governance and corporate culture. Bottom-up, grassroots adoption of knowledge management initiatives led to greater rollout success as it helped build trust among the participants and encouraged constructive debate on how best to integrate knowledge management in daily tasks such that employees would find relevancy and meaning in the knowledge management activities they would undertake. From an enabler perspective, technology and the emergence of the web 2.0, has 1|Page

facilitated the progress of knowledge management due to its inherent characteristics to facilitate social computing, collaboration and collective intelligence. Initiatives such as Communities of Practice (CoPs), that refer to ‘the process of social learning that occurs and shared socio-cultural practices that emerge and evolve when people who have common goals interact as they strive towards those goals’1, started being used in the context of increasingly robust knowledge management strategies. These collaboration and collective intelligence-oriented strategies were integrated with business strategies and backed by meaningful and relevant knowledge management metrics to help measure and assess the overall effectiveness of the knowledge management implementation. Employees were encouraged and empowered to share knowledge freely across their organization while remaining committed to their individual business unit’s performance. The payoffs of this new step on the knowledge management evolutionary ladder were significant and included: • Increased efficiency achieved by transferring best practices, including cost reductions due to the reuse of solutions previously developed. • Improved quality of decision making companywide. • Helped increase revenues through shared expertise. • Developed new business opportunities through the cross-pollination of ideas. • Made bold strategic moves possible by delivering a well-coordinated implementation. Looking to the future, knowledge management v3.0 needs to build on the success and learn from the failures of previous knowledge management eras to help businesses grow sustainably in tomorrow’s business environment. While no two businesses are alike and no one can predict the business environment of the future, it is safe to assume that there will always be a need for the four drivers of business success that knowledge management has been recognized to enable: • Innovation, allowing for the creation of new value through innovative products or services. • Knowledge about customers, allowing for the enhancement of the value proposition of existing products or services by custom tailoring the offerings to the customers’ needs. • Knowledge about business processes, allowing for lean operations focused on reducing input consumption, avoiding costs and promoting reuse of production factors. • Knowledge about the overall business environment, allowing for the reduction of operational uncertainty and increased response speed to market and demand fluctuations. Ultimately, the evolution of knowledge management will be shaped by (1) the business needs of the future, (2) the technology that would be available and (3) other influencing factors such as the increased information literacy of younger professionals entering the workforce. Given these premises, let us consider three specific challenges an organization 1

Etienne Wenger, Communities of Practice: Learning as a social system, http://www.co-il.com/coil/knowledge-garden/cop/lss.shtml, December 6th 2008

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is likely to face in the future and how knowledge management could be used a solution to these likely emerging business realities. Open innovation As Thomas Friedman, the New York Times columnist and author of the international bestselling book The World Is Flat: A Brief History of the Twenty-First Century mentioned in a Newsweek special, ‘working smarter and smarter rather than working cheaper and harder, is really the only strategy for a developed society…’2 Arguably, ‘working smarter and smarter’ implies moving beyond an efficient and effective use of inputs to generate a product or a service, to include the creation of an environment that fosters the emergence of innovative new products and services on a sustainable basis. In today’s globalized business environment, where product and service development have become decentralized in search of lower cost opportunities, the pace of innovation too rapid, the product lifecycles ever shorter, and the consumer increasingly educated and demanding of highly customized solutions, it has become difficult for even the largest companies to hold all the pieces of their product or service offering within their own organizational boundaries. As a quick literature review3, 4 reveals, one of the top strategies used by large multinationals such as Procter & Gamble, Goldcorp Inc. and IBM for accelerating the pace of innovation is to increase collaboration with external research partners, and even competitors, in order to benefit from increased R&D synergies. The results of reinventing the way an organization innovates can be dramatic. As IBM has proven, the company managed to pool in excess of $1 billion in funding and gain access to qualified brainpower that included more than 250 scientists and engineers5 by tapping into a network of research partners. Open Innovation, the concept behind these emerging innovation networks, holds that in a world of widely distributed knowledge, companies cannot afford to rely solely on their own research, but should instead collaborate and buy or license inventions (i.e. patents) from other organizations. In this context, knowledge management becomes a major enabler of the Open Innovation process by critically facilitating the diffusion of knowledge and encouraging collaboration through sharing and learning across organizational boundaries. Currently emerging technological trends such as open technologies (i.e. open APIs and protocols, open data formats, open-source software platforms and open data) and videoconferencing capabilities through telepresence, would provide the enablers of a new evolutionary step in knowledge management. In tomorrow’s digital society, the first generation knowledge management with its focus on information storage and access will still be important as wireless networks, information processing capabilities embedded into everyday environments, and the expanding possibilities for distributed information storage and processing will guarantee that technological issues will continue being relevant. Technology, as a critical enabler of knowledge management, would allow for a 2

Thomas Friedman, The Knowledge Revolution, Newsweek, December 2005, pg. 12 C.K. Prahalad, M.S. Krishnan, The New Age of Innovation, McGraw Hill, 2008 4 Don Tapscott, Anthony Williams, Wikinomics: How Mass Collaboration Changes Everything, Portfolio, 2006 5 Steve Hamm, Radical Collaboration: Lessons from IBM’s innovation factory, Business Week, August 30th 2007, http://www.businessweek.com/innovate/content/aug2007/id20070830_258824.htm 3

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tight, secure and transparent integration between the knowledge repositories of research network partners, thus promoting sharing and learning and increasing the reach and depth of resources available to any given member of the research network. The successful implementation of a knowledge management framework to enable and support open innovation is a critical step in the value creation process of an organization hoping to compete in tomorrow’s innovation-based economy. Information overload The increased levels of knowledge sharing as well as the need to potentially integrate new businesses acquired through mergers, acquisitions or organic growth into one combined learning organization, could lead to knowledge overload. Empirical evidence suggests that in cases where increasing amounts of redundant knowledge is accumulated, the situation can lead to critical knowledge becoming engulfed by less relevant information and preventing successful retrieval of actionable knowledge when necessary. Beside current knowledge management practices that could be used to identify, assess and safeguard valuable organizational knowledge, upcoming technologies such as the semantic web and natural language processing would open the door to new and exciting possibilities in capturing tacit knowledge, storing it as explicit knowledge and then allowing knowledge seekers to find the relevant explicit knowledge quickly and easily. Artificial intelligence-inspired automated processing systems, such as social filtering, recommendation, and data mining systems will also become increasingly sophisticated. Multimodal interfaces that handle speech, images, gestures, and text, will become widely used as it is expected that knowledge-related content will move beyond the domain of text format. Along with the increased level of information literacy of the born-on-the-net generation, the combination of the semantic web and natural language processing will provide an evolving extension of the World Wide Web in which the semantics of information and services on the web are defined. This will make it possible for the web to better understand and satisfy the requests of people and machines to use specific web content6. The intent of this added level of definition granularity will be to make it easier to cut through the information clutter and achieve the critical connection of people-to-content. Workforce demographics The next decade will see major transformations in the makeup of the workforce through the retirement of babyboomers and the born-on-the-net generation joining the business world. These demographic challenges and the increased workforce mobility will require significant work to be done in the way of managing knowledge through an eventual move towards what Alan Godbout coined as wisdom management. With much of the babyboomers’ knowledge being tacit, their knowledge is not easily articulated in a form that is quickly and conveniently retrievable by other knowledge seekers. It is also likely that the most valuable of that expertise fits the definition of deep smarts, whereby it represents the potent form of expertise based on firsthand life 6

Tim Berners-Lee, James Hendler, Ora Lassila, The Semantic Web, Scientific American Magazine, May 17th 2001, http://www.sciam.com/article.cfm?id=the-semantic-web&print=true

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experiences that provides insight drawn from tacit knowledge, and is shaped by beliefs and social forces7. To a large extent, deep smarts are as close as we get to wisdom. They are based on know-how more than know-what, including the ability to comprehend complex, interactive relationships and make swift, expert decisions based on system-level comprehension and also the ability, when necessary, to dive into component parts of that system and understand the details. Deep smarts may be technical or managerial in nature, as intelligent people can develop competence within a couple years with deep smarts being gained only through ten or more years of diverse, active learning experiences. While learning processes can be replicated, precise outcomes can be identified from tacit knowledge and codified as explicit knowledge, packaging wisdom is a much more difficult proposition. The best an organization can do is to create mentorship programs to try to internalize within more junior employees the bits and pieces gleaned from observing and collaborating with the experts over a certain period of time. Retention of critical managerial and technical knowledge is essential for any organization and with the pending retirement of babyboomers and the coming of age of the born-onthe-net generation, wisdom management will become increasingly important. Even the most sophisticated technological tools for documenting best practices or other knowledge management functions cannot capture and communicate the rich know-how accumulated over the years through experiential practice. To ensure their future success, organizations will need to identify experience-based expertise and then design the human development programs necessary to re-create and thus preserve the organization’s deep smarts. However, without a solid organizational culture based on sharing, learning and communicating common values, managing or tapping into wisdom management (or knowledge management, for that matter) would be a rather impossible and ultimately futile exercise. As these previous examples were meant to illustrate, while the future of knowledge management will depend on (1) the business needs of the future, (2) the technology that would be available and (3) other influencing factors, valuable lessons learned from previous knowledge management eras remain highly relevant and need to be followed. Whatever the approach to knowledge management may be in the future, it is important to keep in mind the need for a holistic approach to any implementation strategy. As such, the following variables need to always be carefully considered in on themselves as well as in relation to each other as more often than not one will influence the other: • People form the basis of any knowledge management initiative. If the employees do not actively participate then tacit knowledge does not get captured, the constant transformation of knowledge and the subsequent improvement in knowledge quality does not take place and any knowledge management strategy is doomed to failure. It is thus critically important to build the employees’ trust and to identify the three (3) types of employees taking part in knowledge management initiatives: the early adopters (who will likely become the champions), the active opponents (who can be engaged and valuable feedback be derived from their opposition) and the passive

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James Heskett, Can an organization’s deep smarts be preserved?, Harvard Business School Working Knowledge, April 4th 2005, http://hbswk.hbs.edu/item/4742.html

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resisters (who often times constitute roadblocks to implementation and put themselves at risk of being let go). Process has to be carefully considered in such a way that any knowledge management initiative is integrated in the daily business processes. Failure to do so will lead to the perception that knowledge management is yet another task to be carried out during an already busy workday. This is not the optimal way to launch a knowledge management project as it leads to resistance to change and an overall reluctance to share and learn in a collaborative manner. Technology is an enabler of knowledge management and can be used as a change agent to initiate and facilitate the transformation process of an organization. Focusing too much on the technology aspect at the expense of other critical areas such as people or corporate culture could easily derail a knowledge management implementation as technology needs to be supported and given an operating context in its facilitating role for knowledge management. Governance is a critical aspect to establishing a set of procedures and rules that promote corporate transparency and accountability. As the learning organizations of the future are rapidly becoming places for learning work-related competencies, the governance structure will need to provide a new framework that defines the mutual responsibilities and rights in the work environment. As such it is a critical element to establishing employee trust and buy-in to any knowledge management initiative. Culture is, along with the people factor, the most important element to knowledge management. The corporate culture defines the organization and permeates all aspects of its operations and all actions of its employees. The organizational culture becomes the main enabling factor in taping the various aspects of intellectual capital regardless of type of knowledge or specific aspect of knowledge management strategy.

In conclusion, while it is quite feasible to predict some of the technological and cultural developments that will influence the evolution of knowledge management in the future, such as the emergence of web 3.0, the semantic web and the move towards wisdom management, to name just a few, the overall evolution of knowledge management is a much more difficult proposition to forecast. To prepare for the future, one needs to learn the lessons of the past, to understand the forces that will influence knowledge management in the future and most importantly to be able to seize on the drivers, the results and the enablers of knowledge management’s next evolutionary step. The new way of thinking with regards to the future of knowledge management is that of peer-to-peer networks in what the organization of labor is concerned; value creation is generated through value networks of complex, interdependent and dynamic relationships; information is infinite and unbounded; knowledge is collectively, collaboratively and organizationally focused; cooperation is the law of success and change is all there is.8 In the face of all these shifts, change will be the predominant factor. As such, the next era of knowledge management will require: 1. The capability to manage change and social conflict.

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Yeona Jang, Ethics, Skills, Governance and Policies, INSY-633, McGill University, November 10th 2008

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2. Organizational structures that make change possible without excessively destroying previously accumulated knowledge assets. 3. New institutional frameworks that make productive conflict resolution possible. It will therefore also require that we better understand the ways in which organizational learning leads to new practices and business approaches. Finally, from a practitioner’s perspective, although the rules of the game are changing on almost every dimension, the bottom line will stay the same. The goal is still to understand what makes knowledge most valuable to an organization. Then the priority will be to find a place where using specific knowledge management enablers and strategies will help employees do their jobs easier and better.

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Bibliography Etienne Wenger, Communities of Practice: Learning as a social system, http://www.co-il.com/coil/knowledge-garden/cop/lss.shtml, December 6th 2008 Thomas Friedman, The Knowledge Revolution, Newsweek, December 2005, pg. 12 C.K. Prahalad, M.S. Krishnan, The New Age of Innovation, McGraw Hill, 2008 Don Tapscott, Anthony Williams, Wikinomics: How Mass Collaboration Changes Everything, Portfolio, 2006 Steve Hamm, Radical Collaboration: Lessons from IBM’s innovation factory, Business Week, http://www.businessweek.com/innovate/content/aug2007/id20070830_258824.htm, August 30th 2007 Tim Berners-Lee, James Hendler, Ora Lassila, The Semantic Web, Scientific American Magazine, http://www.sciam.com/article.cfm?id=the-semantic-web&print=true, May 17th 2001 James Heskett, Can an organization’s deep smarts be preserved?, Harvard Business School Working Knowledge, http://hbswk.hbs.edu/item/4742.html, April 4th 2005 Yeona Jang, Ethics, Skills, Governance and Policies, INSY-633, McGill University, November 10th 2008

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