Building the Business Case for Knowledge Management and Innovation Programs

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.

Idea Experimentation: Putting Your Ideas to the Test

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:
[3] McCann, David. (March 15, 2010). Testing, Testing: The New Innovation Game. Available at: