Tuesday 17 August 2021

How KM adds value by increasing the learning rate

What is your organisation's learning rate?  What could KM increase this to? And what's the value of the difference?

Over time, with any product or process, the costs come down. The rate of decrease is known as the learning rate. One value proposition for Knowledge Management is to accelerate the learning rate.

The concept of the learning curve is very common. Wikipedia tells us that the term is used when the same task is repeated in a series of trials, or where a body of knowledge is learned over time. The first person to describe the learning curve was Hermann Ebbinghaus in 1885, in the field of the psychology of learning, and in 1936, Theodore Paul Wright described the effect of learning on production costs in the aircraft industry. This form, in which unit cost is plotted against total production, is sometimes called an experience curve.

Learning curves can be drawn as an upward sloping curve, representing gaining knowledge over time, or a downward sloping curve, representing decreasing costs over time. Experience curves are generally drawn as downward sloping curves, as are the learning curves from drilling in Oman, and oil platforms in Trinidad.  The steepness of the curve is determined by something called the Learning Rate.

The value of Knowledge Management

The Learning Rate when applied to production costs represents the percentage reduction in cost when production doubles. In the case of oil wells, its the percentage reduction in cost when the number of wells doubles. Learning rate therefore is linked to cost, and a higher learning rate leads to  greater cost reduction.  I have explained here that the value of learning is represented by the area under the learning curve. The greater the learning rate, the steeper the curve, and so the more value generated through learning. 

The value from Knowledge Management, in any organisation involved in repeat activity or in learning something new, comes in increasing the learning rate. The diagram above shows the link between learning rate and savings. Imagine you do a task 10 times, with a learning rate of 8%. The reduction in cost should deliver 17% savings compared to no learning at all. However if you can learn twice as quickly (16%) the savings increase to 30%.

Typical learning rates.

There is a natural learning rate, where people just get better through practice with no intervention from KM. Knowledge Management should help you improve on this natural learning rate, and so deliver added value. But what is a typical natural learning rate, and what is an enhanced KM-accelerated learning rate?

This is difficult to answer, and any studies of experience curves are usually careful to point out that there are other factors than knowledge behind the reductions in cost (economies of scale, innovations in labour, costs of raw materials etc).

However this paper shows some learning rates for Power Generation technology, for example

  • Coal - 8.3%
  • Onshore wind - 12%
  • Natural Gas - 14%
  • Solar - 23%
Also we have the examples of learning curves already mentioned on this blog:
  • Trinidad Platforms - 16%
  • Oman oil wells - 21%
  • I also have a North Sea example with a learning rate of 34%
The paper on the power generation examples attempts to separate what they call "learning by doing" from "learning through research", which maybe gets close to a "natural learning rate" vs an "enhanced learning rate". For the 5 examples where they manage to separate these factors, "learning by doing" averages at 7.5% and "learning through research" at an additional 11%, making 18.5% in total.  The difference between 7.5% and 18.5% is an additional 20% savings over a program of 10 projects. 

It would be interesting to see if this also holds within organisations, with in-company Knowledge Management replacing "learning through research". If it does, then we could maybe take that 11% additional learning rate and 20% cost reduction as a rule-of-thumb value for KM.

Implications for Knowledge Management programs

The implication for Knowledge Management is that this provides us with a potential way to measure the value delivered through Knowledge Management. You would need to do the following:

  • Collect data on the learning rate of repeat projects within the organisation prior to the introduction of Knowledge Management
  • Collect data on the learning rate of repeat projects within the organisation after the introduction of Knowledge Management
  • Calculate the additional cost savings related to the increase in learning rates.

This should work when the organisation is involved in repeat activity or repeat production, and where operational efficiency (measured in cost or time) is the primary business driver.

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