A nice video that captures the rationale for a focus on questioning. Questioning is necessary for scientific inquiry and breakthroughs. Questioning is also essential for us to build viable business organizations that can innovate, be resilient, and leverage human potential.

This blog post is not meant for those who are content to let their $110,000 MBA diploma hang on the wall as an indication of a job well done.  Nor is it designed for those persons who feel that now that their education is complete, they have all the necessary tools for success.  I encourage managers and executives to read and participate in this posting if they feel that there is a next step in the educational process...one that is more critical to success than showing off that graduation tie!

We are bombarded with information at a near constant rate. Managers face information overload challenges at their organizations.  They have to contend with information that is emitted from a wide assortment of agents and objects, and this information might arrive through various information channels and devices. Consequently, it is impossible to inspect and process all the information one receives. Some information nuggets receive attention and are carefully considered, while other nuggets might get lost (or are even purposely ignored), and yet others, might be acted on without enough consideration.

What is troubling to me is how frequently managers assume that information that stems from the external world is right or appropriate for their organizations. Often this gets exhibited as follows: a manager gets his recent issue of Harvard Business Review and skims through it during a business trip (of course, only after the manager has exhausted the batteries on the laptop). The manager reads a few articles, finds one or more them to be interesting, and then without much questioning begins to think about how to duplicate practices or approaches described in their own organization. Most managers take a lazy approach when it comes to evaluation of information from external sources. Consider the last time that you really took the time to evaluate information coming from an external source (e.g. a consultant or a recently released business book that touts the next buzzword) with the same amount of care as information that comes from your direct reports. Much of this lazy approach, in my opinion, can be linked to the MBA mills. During MBA programs, degree candidates are rushed through the fundamentals of accounting and finance, given tours of the latest practices in human resource management and information systems, and spend their time working through team and trust building exercises. These are all nice, but do not teach managers the art and science of questioning. Moreover, in some course and management approaches, questioning, especially, the questioning of authorities and authoritative sources is frowned upon. This is common in disciplines such as accounting and finance, where students are made to drink from the fire hose in terms of the terminology and techniques. Student learn to marvel at external information, especially information published in the so-called authoritative sources, rather than to critically evaluate it.

Most managers with whom I speak admit that they have a long way to go in terms of harnessing their questioning capabilities. Key aspects of a questioning capability include:

1.      Knowing how to develop questions for a given context

2.      Knowing when to ask questions

3.      Knowing how to evaluate and process answers to questions

4.      Knowing how to develop an effective, and efficient, questioning process that is refined, and optimized, on a regular basis

Being busy, or overworked, or just being fearful of consequences, are not legitimate reasons for questioning. To retain the human and intelligent aspects of organizations, one must question. Questioning prompts us to seek clarification, act intelligently and mindfully, and promotes constructive discourse.

I would like to hear your thoughts on questioning. Do you ask difficult questions of external information? What are some reasons why you are less critical of information that come from external versus internal sources? What challenges do you face in terms of asking difficult questions? Do you think questioning is a lost capability within current enterprises?

Resources are needed in order to invest in knowledge management and innovation programs. Whether it is discretionary resources to acquire a new system for knowledge discovery or cash to buy gift cards to be used as incentives to promote knowledge sharing among employees, it is important to remember that resources can make, or break, a knowledge management effort. Not all resources are of a monetary nature. Many times, the most valuable resource required is attention. Employee attention to the knowledge management effort (e.g., a new method for codifying knowledge) is also salient for success. To get employee attention, in most cases, you need the attention of senior executives, who give their attention to the projects in which they invest significant resources. So, there is no getting around the fact that securing resources for knowledge management is a critical issue.

Unfortunately, few managers know how to write business cases that attract the necessary resources for their knowledge management and innovation programs.Business cases are strategic artifacts aimed to sell internal and/or external stakeholders on the merits of a project. Upon reading a business case, one should come away with a clear strategic understanding of the project and its value proposition, confidence in the project team, assurance that the budget for the project is reasonable, and awareness that the high-level project plan is sound. Based on my experience, I would suspect that out of every 20 business cases for a knowledge management related effort, about one is funded at the level requested, up to three are funded at 30% or below of what was requested, and the rest are not funded at all!

First, the scarcity problem means that organizations do not have unlimited resources (e.g., capital, or even more intangible resources, like managerial attention), meaning all needs are not going to be met. Recognizing the criticality of the scarcity problem means that when an organization considers a case for investing in knowledge management, it is going to be evaluated against every other case that is asking for resources. Too often, knowledge management business cases do not understand or account for this reality, and go by the wayside.

The second thing to understand is that knowledge management efforts need to show payoffs. In an organizational context, payoffs are compared across projects that are candidates for investments. Business cases that are able to demonstrate payoffs that are worthy of the effort (time, cost, personnel, etc) of the investment, and present convincing arguments on why the payoff will better the organization towards its future objectives, stand a high chance of being funded. Simply claiming a high payoff is not sufficient. The business case presented must be sufficiently evidenced to show that achieving the payoff is reasonable.

From the outset, one must realize that making the case for a knowledge management effort and calculating payoffs is not easy, when compared to making the business case for a new piece of manufacturing equipment, such as new welding machine or a color photocopier. Investing in a piece of new machinery can be directly tied to increases in product quality and/or quantity through multiple metrics (e.g., lower defect rates, finished products per hour, etc). Calculating the payoffs for investments in knowledge management efforts is not as easy, nor is it as direct, and first-order effects are difficult, if not impossible to measure. Knowledge management efforts lead to changes in behaviors, approaches, and methods that, on their own may not have direct bottom-line impacts. However, when these are mapped and traced to organizational processes, the impacts can be measured and articulated. Needless to say, this is often a more time consuming and creative effort than simply measuring direct impacts as in the case of outcomes from a new piece of manufacturing equipment.  Equally important is that there is a lag time between when one invests in a knowledge management effort and when one witnesses outcomes that result in payoffs. Accounting for this lag time is not easy, yet it is essential to building an adequate business case.

The third, critical realization that we need to appreciate is the fact that investing in knowledge management is akin to a group as a whole investing in a common effort. Consider the case of investing in initiatives such as the promotion of fair trade practices. Most people agree that increasing the adoption of fair trade practices benefits society. The challenge arises when we ask who wants to take responsibility for investing in these efforts. If taxes were raised to support these efforts, would you be happy? Rational individuals often want others to bear the cost of these common efforts and gladly enjoy the benefits, yet hesitate to initiate responsibility. A similar predicament faces knowledge management efforts. Departments within an organization want their peers’ units to invest in a common effort. Each department might see knowledge management as an effort someone else should put up resources for and hence defers spending its own resources. In some organizations, knowledge management efforts might be viewed as a tax levied on a department’s resources. This tax, is something every department either does not want to pay or wants to pay the lowest possible amount; yet any outcomes from the tax, such as infrastructure (e.g. a new intranet) is of interest to all. Moreover, the departments may get upset if they see the common effort they invest in does not perform up to par. This is akin to how one feels when one drives down a poorly maintained road, knowing that one has paid taxes for its upkeep. Knowledge management is seldom viewed as a profit center in an organization. It is important to remember that building a business case for a knowledge management effort is often similar to trying to build a case for increasing investment in an effort common to the whole organization.

The above three challenges, while severe, are not insurmountable. To learn more about how to build a good business case for knowledge management and innovation programs, please send me an email and stay tuned for my forthcoming article in Business Information Review.

Without a good business case, knowledge management will remain a theoretical, and even an impractical, concept in organizations. Good business cases give individuals a chance to put theory into practice, by providing resources for implementing knowledge management programs, processes, and technologies. Writing good business cases requires time, effort, and practice. Seldom is one born with the ability to write good business cases.

Akshay Bhagwatwar (University of Washington), Ray Hackney (Brunel University), and I have authored a paper that examines the knowledge integration challenges faced by organizations as they try to recover from backsourcing endeavors. The paper will appear in a future issue of Information Systems Management.

Abstract
Backsourcing is motivated by opportunities arising from changes in the business situation, redefinition of the character of outsourced service declining in quality or due to the discovery of flaws in the contract. The situation of backsourcing clearly has major implications for an organization in terms of monetary investments, IS infrastructure and changes in employee requirements during and after the process. The research in this paper consequently acknowledges a serious challenge involving the management of systems within organizations following backsourcing events. This paper considers a detailed analysis of two case studies of backsourcing: JP Morgan Chase (USA) and Sainsbury (UK). A major contribution of the paper is to identify important strategies to be followed in backsourcing projects to ensure efficient knowledge re-integration. In this respect, it is believed the paper is unique in identifying emergent suggestions for strategic backsourcing decision making through a series of insightful observations.

Bhagwatwar, A., Hackney, R., and Desouza, K.C. “Considerations for Information Systems ‘Backsourcing’: A Framework for Knowledge Re-integration,” Information Systems Management, Forthcoming.

I have received the 2010 Outstanding Reviewer award for my contributions to Strategic Outsourcing. I serve as on the Editorial Board of the journal. We would welcome your papers on all aspects of outsourcing (see, Author Guidelines)

Once you have advocated, screened, and funded ideas, the next step is to engage in experimentation. To experiment is to try something new. It allows you to observe the interplay between cause and effects—i.e., it is the application of scientific methods to generate actionable knowledge. Simply put, experimentation can be considered the sum of all activities we engage in to test the feasibility and elasticity of an idea. On the feasibility side, we are normally looking at the cost, benefits, effort, resources, and risks involved in transforming the idea into a viable product and/or service. In addition to feasibility, the experimentation process will also unearth the elasticity of an idea. Idea elasticity focuses on the reach of the product and/or service. Elasticity tries to see how far you can stretch ideas, both in terms of the number of products and/or services that you can develop from them, and also the domains in which you can deploy them.

It is through the process of collecting data through the conduct of experiments that we can find support for the ideas. Data collected during the experimentation process will help us gather the necessary evidence to support decision-making. Today, there is a big movement in medicine called evidence-based medicine (EBM), which demonstrates that a move towards more scientific and data-driven decision-making can prove to be valuable, rather than purely relying on gut instincts. Dr. Dave Sackett, a pioneer in the field states “EBM is saying rather than just rely on tradition, expert opinion, wishful thinking, let's try and find the evidence and apply it.” [1] To build a culture of experimentation one must focus on the following principles: 1) do not just discard ideas without adequate evidence, 2) do not support or move ideas ahead without adequate evidence, and 3) always look to exploit data from experiments.
While at Amazon from 1997-2002, Greg Linden prototyped a system that would make personal recommendations to customers as they checked out. Linden commented, “I heard the SVP was angry when he discovered I was pushing out a test. But, even for top executives, it was hard to block a test. Measurement is good. The only good argument against testing would be that the negative impact might be so severe that Amazon couldn't afford it, a difficult claim to make.” [2] Linden’s experiment showed how much the customer liked the feature and it won praise – the end result is that this has become a signature design feature for Amazon, and most online web marketers have introduced a similar concept. This illustrates the value and capabilities of organizations to test incremental ideas and achieve innovation through “continual tiny experiments in such areas as business processes and customer relationships rather than a single, company-transforming idea.” [3]

Experimentation needs to be made part of every employee’s work and has to move beyond the R&D Labs. The R&D Labs have natural constraints that leave a lot to be desired in terms of experimentation. For example, most of the R&D personnel are detached from the day-to-day running of the business and hence are not the best people to experiment on the problems and solutions of interest for today. In addition, these labs are often physically secluded from the operational centers of the business. This separation leads to difficulty when you try to transport (mobilize) ideas from the lab in order to address problems that are happening on the ground. Finally, you also have a numbers issue. The number of individuals working in an R&D lab is minimal compared to employees who are involved with the day-to-day running of the business. As such, no matter how brilliant your R&D lab personnel are, you will be at a loss if you cannot find ways to tap into the 85-90% of your organization’s employees who do not work in the lab. At the Engaged Enterprise, we had a R&D lab, the Institute for Engaged Business Research (IEBR). IEBR was focused on working on applied management problems that had value propositions to our clients. We determined upfront that simply relegating experimenting and innovation to the labs was not optimal. We needed to find a way to blend the experiences of those working on the consulting side with the R&D side. In addition, we needed to find ways to take knowledge that was being generated on the consulting side (as experiments were conducted “live” while projects were being done – i.e. as we tried to install a new service or strategize with a client – we were in essence engaging in experimentation) and move these into the R&D lab. We did this by having people share their time between consulting and R&D. Also, we had our R&D folks develop a method and handbook that could be used for experimentation which explained the basics of experimentation and how to capture and store results. We also encouraged sharing of results from experimentation efforts so that others might use the results, or provide their reflections on the experiments.

The effort to move experimentation beyond the R&D labs needs to be a conscious one. Both, organizational (management) and employee level interventions need to be in place to promote this concept. Managers should not only encourage their employees to experiment with their ideas, but even go so far as making it a requirement when ideas are being developed and proposed. In addition, employees should take responsibility to engage with the experimentation process, and be aware of methods and practices for conducting experiments.

please stay tuned for my new book or send me a note via email…

[1] Sackett, Dr. Dave. (October 30, 2009). Interviewed by André Picard. Available at: http://www.theglobeandmail.com/life/health/when-we-began-we-were-almost-pariahs/article1344833/
[2] http://glinden.blogspot.com/2006/04/early-amazon-shopping-cart.html
[3] McCann, David. (March 15, 2010). Testing, Testing: The New Innovation Game. Available at: http://cfo.com/article.cfm/14482988?f=search

Volodymyr V. Lysenko and I have authored paper that explores the possibilities of the Internet as a tool for supplying information necessary for the organization and mobilization of successful opposition movements, especially under non-democratic regimes. Examples of the roles the Internet plays in the political processes in Russia are discussed in detail. In particular, the recent cyberprotest cases of the Ingushetiya.ru website and the movement to release political prisoner Svetlana Bakhmina are investigated. Besides showing the Internet’s significant role in organizing modern protests, these cases also demonstrate that in environments where practically all traditional mass-media are under the authorities’ control, the Internet becomes the major source of alternative information. Our paper offers a look at how deploying technologies can bring about social change, even in some of the most difficult political environments.

The paper will appear in Technology Forecasting and Social Change. Volodymyr and I will present the paper at the Harriman Institute for the Etiology and Ecology of Post-Soviet Media Conference at Columbia University on May 7-9, 2010.

Yuan Lin, Sumit Roy, and I have authored a paper that examines the use of network entropy and mutual information to measure the agility of networked organizational structures. The paper will appear in Applied Mathematics and Computation.

Abstract
While the agility of networked organizational structures is important for organizational performance, studies on how to evaluate it remain scant, probably because the difficulty in measuring network evolution. In this conceptual paper, we propose two measures – network entropy and mutual information – to characterize the agility of networked organizational structure. Rooted in graph theory and information theory, these two measures capture network evolution in a comprehensive and parsimonious way. They indicate the uncertainty (or disorder) at the network level as well as the degree distribution at the individual level. We also propose an algorithm for applying them in the scenario of adding links to a network while holding the number of nodes fixed. Both simulated and real networks are used for demonstration. Implications and areas for future research are discussed in the end.

Lin, Y., Desouza, K.C., and Roy, S. “Measuring Agility of Networked Organizational structures via Network Entropy and Mutual Information,” Applied Mathematics and Computation, Forthcoming.

Nicholas D. Sweers II and I have authored a case study on the complexities of change management when underground resistance is present. The case study will appear in the Journal of Business Strategy.

This case study highlights the challenge of dealing with underground resistance when leading organizational change. Underground resistance has deterred many change management efforts. Moreover, strategies to address underground resistance are still at a nascent stage of development in management practice and literature. The case tells the story of Sam Bridgeport, a Senior Partner at a major consulting firm in Seattle, who has been charged with leading a restructuring effort that will significantly affect the everyday operations of the organization. Unlike past change management initiatives, which often failed, Sam was wise to encourage employee participation from the start. As a result, Sam was able to mitigate most of the opposition against his plan, but he soon finds out that he gravely underestimated the natural human tendency to resist change. Sam discovers a covert, underground resistance effort is quickly gaining steam, and he must put a stop to it before it’s too late.

Executive responses to the case study from Mark R. Jones, CEO, The Sunyata Group and George Head, Senior Vice President Broadband Services for Stratos Global will also be published.

Jared Keller, Yuan Lin, and I authored a paper that describes how agent-based modeling can be used to consider policy options for dismantling terrorist networks. The paper will appear in Technology Forecasting and Social Change.

Dismantling Terrorist Networks: Evaluating Strategic Options Using Agent-Based Modeling

Dismantling dark networks remains a critical goal for the peace and security of our society. Terrorist networks are the most prominent instantiation of dark networks, and they are alive and well. Attempts to preemptively disrupt these networks and their activities have met with both success and failure. In this paper, we examine the impacts of four common strategies for dismantling terrorist networks. The four strategies are: leader-focused, grassroots, geographic, and random. Each of these strategies has associated pros and cons, and each has different impacts on the structure and capabilities of a terrorist network. Employing a computational experimentation methodology, we simulate a terrorist network and test the effects of each strategy on the resiliency of that network. In addition, we test scenarios in which the terrorist network has (or does not have) information about an impending attack. Our work takes a structural perspective to the challenge of addressing terrorist networks. Specifically, we show how various strategies impact the structure of the network in terms of its resiliency and capacity to carry out future attacks. This paper also provides a valuable overview of how to use agent-based modeling for the study of complex problems in the terrorism, conflict studies, and security studies domains.