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April 10, 2008
Orthogonality
Lately I’ve been thinking a lot about orthogonality in KPI’s.
Perhaps I should specify - when I talk about orthogonality, I’m pretty much talking in vectorspace, meaning that if the KPI’s are perfectly orthogonal they do not contain any form of information about eachother. Or in other words - independent KPI’s.
The trouble with interdependent KPI’s is that it will give an overestimation of the challenges in the company - imagine a situation where you have 4 KPI’s, one on customer satisfaction, one on revenue, one on orders quality and one on employee satisfaction. All are red.
Which one would you focus on?
Well - most companies would implement an revenue improvement - by going more aggresively in the market, after that they would ensure that their share of voice would grow, and become morepositive by branding themselves better, while getting the employee satisfaction up by having more socialization internally in the company - e.g. giving an office party. Finally, off course, they would get the orders quality up by putting out a memo stating that employees need to be more thorough in their job when putting orders into the system.
What should be realised is that the 4 KPI’s might be interdependent.
What actually happens is that:
1.The quality of orders data is low
2.Due to low quality data - orders do not get delivered on time - if at all
3.Customers get dissapointed, and move their business elsewhere
4.People feel that they cannot perform as well as they would like to, while listening to a lot of customers complain that they work at a bad company - their satisfaction falls
5.Revenue falls (naturally) stemming from the fact that the customers do not reorder
The right action to take would have been to impose a new governance on orders quality, or change systems such that the quality would go up.
Off course you have the same problem with weighted importance within all KPI’s, and you could argue that this is where the good management comes into play - finding out what KPI’s to focus on, but in many cases of missing orthogonality you will not be able to realise that you actually have a interdependence problem, and will try to isolate the problem and solve on a point basis.
Another form of interdependency is when we meassure the same process in different ways - such that the process is overrepresented in the KPI map. This kind of overrepresentation will bias the attention towards areas that it will be less efficient to focus on, and will ensure that you direct your focus towards a less than optimal area.
So how do you avoid creating these kinds of problems for your company? I will write it here when I have the definite answer.
Posted by Peter Møllebjerg Andersen at April 10, 2008 5:30 AM
