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Justifying Your Knowledge Management Programme
If you are running a knowledge management programme then you know that you do good work. Whether it is involves communities of practice, learning from projects and operational activities, or documenting organisation knowledge in a myriad of ways (from traditional databases to blogs and wikis), you know what you do is important for your organisation. However simply knowing this is not enough. At some point, you will have to justify what you do to those above you. If you don't, you may not get to do it any longer. Often these justifications have to take a financial form.
Having been involved in several attempts (some more successful than others) to justify knowledge management programmes using financial measures to senior executives, it took me a while to understand what I was really doing. Although lots of numbers were involved, I wasn't engaged in some scientific activity. I wasn't researching. I was selling and persuading. Once I understood this, what needed to be done became much clearer.
If you are going to persuade people then you need three things:
in the eyes of your audience. Even if your arguments are good, you may still be ignored if you have no reputation or status.
that will persuade your audience of a particular course of action.
Stories and anecdotes
that capture your audience's imagination and make your argument real to them.
Although this paper will concentrate on the second, for the greatest chance of success you need all three. Ignore the others at your own risk.
The other critical thing you need is to
understand your audience
. Who are they? What matters to them? What will influence them? If you do not know this then you are in big trouble.
1. Framing the Argument - Who is your audience? What do they want? What do you want?
You have been asked to justify your Knowledge Management programme to a senior executive new to your organisation. Where do you start?
Many people panic at this point, so my first piece of advice is the rather obvious one of staying calm. This is an opportunity to present what you do to someone who can help you. The first thing to do is to identify who this senior executive really is:
What is this new executive responsible for?
What are they measured on?
Have they made any pronouncements about their focus areas?
Do you have any contacts that have worked with them before?
What political connections do you have that can influence them?
This last point is critical. Good knowledge managers understand the political nature of their job. KM groups are often small and in danger of getting isolated which in many organisations is risky. "I don't know what they do" often leads to "Why do we need them?" Techniques such as stakeholder mapping can be useful here.
Senior executives may not all care about the same thing. In one justification exercise, one senior stakeholder was primarily interested in any cost reduction benefits that a communities of practice programme could bring. He had financial responsibilities (and was also an accountant). However his CEO-level superior was interested in a different number: the % of community events that involved participants from outside the organisation. The CEO's vision was to make the organisation less insular and he saw the community programme as a means of doing that.
In tough economic times the focus will be on cost reduction and savings. However contributions to sales, new product generation and organisational effectiveness should not be forgotten. Organisations do not cut themselves to growth.
2. Constructing the Argument - What benefits can you show?
As part of your knowledge management programme, you will collect a lot of data. Here are some examples:
Number of documents uploaded / downloaded.
Number of community members.
Numbers of after action reviews run.
These numbers are vital to you but there's a problem with them: No one else cares. And your task here is to make people care. So these numbers by themselves will not be enough. They may even be counterproductive , indicating that you don't understand the needs of the wider organisation. You have to link your activities to the rest of the organisation.
There are at least six sources of information that will be useful to you. You will almost certainly rely on a combination of these.
The first is the
mentioned above. A non-financial indicator of value for a non-compulsory service is continued use. If people don't have to use it but do then they are very likely getting some benefit from it. Some organisations also capture value metrics as part of their operational measures. For example, a knowledge-based help desk that supported consultants in a professional services firm sent out a survey to a sample of its users. It asked general questions about user satisfaction but also asked how much time the service had saved the consultant. With the consultant's billable rate, a calculation could then be made as to the value of the time saved. This was then scaled by the total number of requests the service received and could therefore present a robust value figure.
The example above utilises the second technique:
. Asking a target population the value they receive from KM services in terms of time saved, contribution to deals, etc. Surveys are popular because they can give large volumes of data. However there are several drawbacks with a pure survey approach. Firstly, response rates can be low. Secondly, respondents may not be able to quantify how much value the service gives them. Thirdly, if the survey data is vague then it may get rejected by the executives you are trying to reach. Surveys are best when focused on a specific event or activity and utilised with other techniques.
with KM service users can provide very powerful insights. One question in particular generates a lot of useful conversation: "What would happen if this service was stopped tomorrow?" Unlike a survey, you can carefully probe service users on the impact of KM on their work. Some groups are more inclined to give quantitative estimates than others (engineers and accountants are good examples). Interviews will also generate stories and narratives that can be used in your argument. The big drawback with interviews is that they are time-consuming. You may only get to do 10-20 interviews and therefore their statistical validity may come under criticism if used in a financial model. You can use
operational metrics such as usage to identify who to target for interviews.
or focus groups allow you to involve more people in the data gathering. Participants can also prompt each other with observations and experiences. However in "busy" organisations they may be difficult to schedule. In addition, individuals might be less willing to divulge sensitive information that is useful to you in front of others.
Again, care needs to be taken to select a relevant cross-section of people.
involves observing people in their working environment, similar to an anthropologist. It can provide a very rich picture of organisational activities. You have more chance of seeing what people really do rather than what they say they do. However, ethnography is very time-consuming and may not give you the quantitative insights that you need.
and published data from other organisations may be used. Whilst these don't require much research on your part (although they may be expensive), their big vulnerability is their origin outside your organisation. This can immediately provoke the response: "That may be true there but we are different". And this response may be accurate! However if you are able to identify and contact similar organisations to discuss spend and return issues with them confidentially, you can get useful insights.
Whatever techniques you use, you are looking for linkages between KM services and benefits to other business activities. Some of these will be "hard" - e.g. a communities of practice programme decreasing the need for expensive external training, after action reviews reducing the costs from overrunning projects. If you can get comparative data from within your own organisation then so much the better - e.g. are participants in KM activities retained longer or shown to be more productive than those who are not. Comparative data is powerful but it can be hard to obtain and time-consuming to work with.
One approach that is often used is to calculate the amount of "time saved" by employees by using KM services and then attempt to convert that into a financial value using salary figures (or chargeable rates in professional services firms - see the example above). Senior executives have grown cynical about these kinds of calculations (they are a favourite tool of ERP software vendors) as hypothetical time savings do not lead to actual time savings and cost reductions. Unless you can show actual reductions in time spent then you may in for a rough ride.
Another approach looks at risk. Ignorance can expose organisations to risks that may be costly (damaged assets, lost customers, legal exposure). Is the knowledge management programme reducing these risks? Unless the organisation has a very sophisticated approach to recording risks then much of the evidence here will be hypothetical.
Once you have brainstormed a range of potential benefits and assembled your data, you need to build your model. If you are comfortable with numbers and spreadsheets then you can do the first one yourself. Otherwise get someone to help you. My preferred approach is:
On one sheet note what all you your input data is, what its source is and your confidence in it (this may be a statistical confidence level or simply "high", "medium", "low").
Then on a second sheet, identify each of your financial benefits, any notes or assumptions, and your calculations based on your input data.
On the final sheet, write each of your benefits as line items with the calculations linking back to the input data on your first sheet. This means that if you change some of your assumed input data on the first sheet, you can see the outcomes on the third.
Constructing these models is a process of trial and error. Having a friendly accountant or business operations analyst to criticize your numbers here is very useful. You first attempt will almost certainly have holes in it. So how good does your model have to be? The answer is: it depends. And to be frank, it depends a lot on your relationship with those you are trying to persuade. One KM director took a model into their superior, who immediately challenged its assumptions. However the superior picked up her calculator and came up with a number of her own - which was smaller but still favourable! Those two individuals had worked together for years and had built a relationship of mutual respect. If this had been the first meeting between the two then it might not have been so productive.
3. Presenting the Argument - Do you make the grade?
We all know that presentation matters. And so it goes with the presentation of your justification to your audience. Here are some suggestions for the presentation:
Ensure as far as possible that the person presenting your justification is respected by your audience. That means it may not be you but your own superior or even someone else who can act as a champion.
Road test the presentation with the sympathetic and influential within your own organisation. What are you missing? Is your focus right?
Brainstorm hard questions beforehand and come up with a credible response. Focus especially on assumptions and speculative data. If you are asked for data you don't have on the day then use it as an opportunity to explore why that person wants it. What are they interested in? Then either get the data quickly after the event or if it is expensive or difficult to obtain, follow up with an explanation and alternative.
Include a few powerful visuals. Most people struggle to make sense of raw numbers. Simple graphs and charts can turn a numerical soup into a single telling point. However do not go overboard and smother people in pages and pages of charts each containing vast quantities of data. As a rule of thumb, a 30 min presentation means 10 slides which in turn means 6 data charts maximum.
Use the stories and quotes that you have encountered in your research to support your argument. If your audience are purely bean counters then this may not have much impact but for everyone else they will provide a powerful way of anchoring your argument in real life.
If your argument is rejected, then try to find out why. Were the benefits you focused on of no interest to the audience? Was the model not believed? However if your argument is accepted (and hopefully it will be) then what benefits can you get as a result of this? If it's appropriate then what do you want to ask for in return? Don't just prepare for the worst but best too.
Do not treat the creation of a financial justification for KM as purely an analytical exercise. Think about your credibility and the stories you encounter as well in constructing your argument.
Understand your audience for this exercise. What matters to them?
Use a range of qualitative and quantitative techniques to understand your impact on your business.
Road test your argument and don't stint on the presentation.
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