7 Metrics for the KM supply chain

The Supply Chain analogy for KM suggests several metrics we can use.

I have often used the analogy of the supply chain as one way of thinking about KM. This involves looking at KM as a chain of processes supplying knowledge to the user.

This analogy has the benefit of thinking about KM from the point of view of the knowledge user. You can ask “If a person in this organisation were in need of a specific piece of knowledge to make a specific decision, what system is in place to make sure that this knowledge a) gets to the person on time, and b) is of the correct quality?”

And like any analogy, it brings with it many other ways to think about KM. Can we apply “Lean Supply Chain” thinking to KM, for example? Can we remove waste from our Knowledge Supply Chain? Can we think of the Knowledge Manager as a supply chain manager?

Or – the subject of our blog today – can we use common Supply Chain metrics to help us understand how to metricate KM?

Here are 7 metrics from the supply chain world which might help us decide on metrics for our Knowledge Management Framework.

  • Backorders – unfulfilled orders from the customer. In KM terms, these might be search queries, or questions to a Community of Practice, which receive no answers. These are indications of the need to create knowledge resources for the user, and the number of unfilled requests is a proxy of the completeness of your knowledge base (both tacit and explicit).

  • Cycle time. There are many definitions of cycle time in the Supply Chain world, but for KM the crucial cycle time is how long it takes from the first observation of new knowledge, to that knowledge being embedded in the knowledge bases, training courses and community of practice resources. Or in lesson-learned terms it might be the time from “Lesson identified” to “Lesson closed”. In CoPs it might be the “question to answer” time.
  • Defects – defective supplied material. This is a quality measure of your knowledge content, measuring how much of it is out of date, wrong, or unhelpful. You could measure the quality of lessons entering your lessons management system for example, or of articles published to a knowledge base, or of answers in a community forum.
  • Fill Rate – the amount of ordered supplies filled on the first order. In KM, this might be the number of community questions answered by the first response, or the percentage of times the answer is found in the first search.
  • Inventory costs – what it costs you to stock and manage your inventory (cost of stock, cost of warehouse, salaries of warehouse staff etc). In KM terms, this is the cost of operating your KM framework, including the cost of KM roles, the licence cost for KM software, and the time cost from populating the system. This represents the total costs to the business of operating KM.
  • Gross margin return on inventory – the  gross margin divided by the inventory costs, a popular metric for retail stores. In KM terms, the gross margin would be the overall value of KM to the business, which you would track and estimate through success cases, value stories and metrics such as decreased costs or increased sales. It is in effect the KM ROI.
  • Inventory turnover – the average annual use of your inventory; for example if a store carries 1000 items and sells 10,000 items a year, that’s a 10 times inventory turnover. In KM terms this would be applied only to explicit knowledge, and you would measure the number of reads of knowledge articles divided by the number of articles.  You could of course get smarter, and you could look at which articles get the most reads and which get none at all.

Hopefully that gives you some ideas of a few more metrics you can use to make sure your Knowledge Supply Chain is working – delivering valuable knowledge to the knowledge works in your organisation in an efficient, reliable and effective way.

View Original Source (nickmilton.com) Here.

Expectation, metrics, rewards, support – the KM Governance quartet

Four elements make up Knowledge Management Governance. Expectations, metrics, rewards and support.

Governance is often the missing element in Knowledge Management, and although it is one of the four legs on the KM table, it is the one that gets least attention.  This is partly because governance is not easy, and partly because there is no clear published model for KM governance.

Governance represents the things that the organisation does, and the management of the organisation does, that drive the KM behaviours and adoption of the KM Framework. We see four elements to governance – expectations, metrics, rewards and support.

Knowledge Management Expectations.

The first thing management needs to do in terms of governance is to set the expectations for KM. This requires a set of clear corporate expectations for how knowledge will be managed in the organization, including accountabilities for the ownership of key knowledge areas, and the definition of corporate KM standards, KM principles and KM policies. These documents should tell everyone what is expected of them in Knowledge Management terms.

Different departments can then add to these expectations, and individuals with KM roles will have KM expectations written into their job description (see examples here).  Within a project, the expectations are set by the Knowledge Management Plan.  Expectations may also be set using the competency framework.

If there are no clear expectations, nobody will know what they should be doing in KM terms.

Knowledge Management Metrics.

If standards and expectations have been set, then the organisation needs to measure against these expectations. For example, if the corporate expectation is that every project will conduct a lesson learned session, and every knowledge topic has an owner, then you should measure whether this is happening.
There are other types of KM metric as well – see these blog posts for more discussion.

If there are no metrics, then nobody will know what people are actually doing in KM.

KM rewards and recognition.

If you are measuring people’s performance against the expectations, then this needs to be linked to rewards and recognition. If people do what they are expected to, this should be reflected in their rewards. If they don’t do what is expected, then there should be a sanction. See these blog posts for a wider discussion of incentives.

If there are no links between metrics and reward/recognition, then nobody will care about the metrics. Particularly important are the sanctions for not doing KM. If people can dodge their expectations and get away with it, then this sends a strong message that the expectations are actually options, and not expectations at all.

Knowledge Management support

It is unfair to set expectations, measure people against them, and then reward people based on these measures, unless you make the expectations achievable in the first place. Therefore you need to set up the systems, the training, the coaching, reference materials and so on, that make it possible for people to meet their expectations.

If there is no support, then you have set up an unfair system which people will resent.

Together, the quartet of Expectations, Metrics, Reward/recognition and Support form the basis of an effective Knowledge Management governance system.

View Original Source (nickmilton.com) Here.

Do your KM metrics cover seeking and using as well as sharing?

When it comes to determining Knowledge Management Metrics, make sure you cover the Demand side as well as the Supply side. 

Image from wikimedia commons

The most difficult aspect of Knowledge Management to address is re-use, and yet re-use of knowledge is the whole point of KM. All of the discussing, capturing, documenting and storing of Knowledge is in service of re-use. Therefore when we metricate KM, we need to think about metrics for Knowledge Demand and Re-use, and not just Supply.

It is easy to create metrics for Knowledge Supply, for example:

  • Number of lessons added to the Lessons Database
  • Number of blogs
  • Frequency of articles on the community blog
  • “Best blog post”
  • Number of new items in the portal
  • Frequency of edits and updates to items on the portal
  • Number of wikipages
  • Individuals who make most contributions to the knowledge base
  • “Best knowledge base article”

It’s not so difficult to cover the demand side as well, through metrics such as:

  • Number of questions asked per month on the community forum
  • Time between question and first answer
  • Number of answers per question
  • Number of readers of the community blog
  • Number of reads per knowledge asset or knowledge article
  • Frequency of searches of the knowledge base
  • Search success rate
  • “Time to find” knowledge
It’s a little harder to measure re-use, but it can be done through metrics like these:
  •  instances of lessons reuse
  • evidence of Community value, delivered through solutions to members’ problems, and presented as success stories
  • user feedback and satisfaction ratings
  • number of lessons which have been embedded into procedure 
  • average time taken to embed lessons

The demand metrics and re-use metrics can be very interesting. For example one of the ways the World Bank disseminates knowledge to external stakeholders is by publishing reports. It would be easy just to measure the number of reports created, but in addition they commissioned a study of “Which World Bank Reports Are Widely Read“, which was able to analyse which of the reports were widely downloaded and cited, and which remained unread.  A lot of effort and knowledge goes into these reports, and the last thing the World Bank wants is to create reports which are never downloaded.

Demand-side and re-use metrics such as these are very important to the success of your KM program.

Make sure your metric system is well balanced, covering supply, demand and re-use.

View Original Source Here.