Defining KM RoI in terms of critical failure cost
Stephen Bounds — Mon, 16/03/2009 - 07:57
As we all know, trying to pin down a tangible return on investment (RoI) for Knowledge Management initiatives is often difficult.
What we do know is that KM implemented properly reduces risk profiles. For example, less chance of having to re-learn a process because your critical staff member just moved to Rome, or less chance of a critical failure driven by inadequate communication.
Sameer Patel focuses on Enterprise 2.0 and social computing rather than KM, but the same issues apply here as well. He has an interesting take on defining RoI in these circumstances:
The standard justification here is: X hours per employee saved x Y# of employees x Some cost per hour = Savings ... The problem [is] that none of them are really what a smart buyer can justify to a senior executive as “return”. What’s worse, software was sold a decade ago in this fashion and the scars from unattained real dollar productivity savings from CRM, Portal and KM implementations are still very visible in the enterprise ...
Enterprise social software needs to be sold based on one simple end goal: How the income statement will look like before and after the investment ... model just 2 representative use cases at narrow functional levels ... for instance "on 5 occasions, our software enabled a sales rep to find a subject matter expert/a white paper/an up sell opportunity, resulting in total sales of $20 million" is much more tangible for an IT director to take to her CFO.
I believe this is sound advice for any KM project, not just for E2.0-style initiatives. However, this post triggered a key realisation. KM should not be aiming to achieve "x minutes per day" style savings. Rather, our job is to save "$X million over 5 years" by reducing the number of critical incidents where problem solving failure and/or knowledge loss occur. Otherwise, Fogbank happens. There are three components to this equation for critical KM failure in an organisation:
- the current risk probability
- the level that KM can reduce that risk
- the true cost of a critical KM failure
Let's assume for the sake of argument that KM can produce a positive RoI for Company X. So if Company X's directors don't accept the value of KM, there are three possible reasons:
- they are underestimating the current risk of failure
- they don't believe the quoted level for how KM can reduce that risk
- they are underestimating the true cost of failure
Now, it should be possible to establish reasonable metrics for components 1 and 3. (Most companies will privately admit to their worst failures, and we can extrapolate the costs of these failures fairly easily.) Multiplying these two components gives KM a maximum budget.
Let's turn this into an example: If Company X has lost $10,000,000 over 3 years due to preventable KM failures, a KM program is a no brainer if it can reduce that amount by just 20% on a annual budget of $400,000 ($2 million saved vs $1.2 million outlaid).
Now for the scary bit - this gives KM a solid target to aim for and hence, full accountability. The one remaining problem is that because KM deals with low probability events, one bad year will throw the numbers right out. Similarly, one good year may look like a resounding success.
So management will need to be convinced to commit to KM for 3 or 4 years to make sure that overall trends are heading in the right direction.
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