An oft heard inquiry from clients is, “What is the right metric to use?” The context might be for:
- Defining data quality
- Reporting the business impact of a data governance initiative
- Monitoring the progress of a digital or data-driven transformation
In all cases the assumption is that there is a definitive metric or key performance indicator (KPI). I guess it’s a fair question – it is certainly a popular one.
Some years ago there was great interest and hype associated with Performance Management. It went by other names, such as Corporate Performance Management and Enterprise Performance Management. Such initiatives sought to provide an aligned set of metrics for all the major activities in an organization. The theory made sense: get everyone working to the same hymn sheet (remember that old refrain?).
A simple example exposed the potential value of PM. Think of what happens when you:
- Chief Procurement Officer is encouraged to seek the lowest unit price per item ordered, in order to reduce company costs
- Warehouse Manager is encouraged to reduce average on-hand inventory holding costs, in order to reduce company costs
On paper both tasks seem focused on the same outcome – reduce cost. However the behavior that results leads to chaos. The CPO ends up trying to buy in bulk, in order to lower the unit price, and the warehouse guy tries to turn trucks away since they are adding to overall and average inventory carrying costs. In other words, the two metrics used provide local goals that when taken together, or globally, create complexity that will lead to inefficiencies.
Problems were legion, not least that it was real hard to implement and anyway, most firms have many metrics before they start the effort. Were there many proof points of success? It also took a long time to achieve and due to lack early value, it was a hard sell and not self-evidently valuable. But the concept remains interesting.
Yet here we are, being asked by clients for the right metric. I wonder how the Chairman of the Federal Reserve feels about metrics. I read an article in today’s US print edition of the Wall Street Journal titled, Is Money Easy or Tight? It depends on the Stock Market. The article explores the conditions of monetary policy and if it market is “tight” or “loose”. It so happens that the Fed manages interest rates to help with this tight/loose dynamic in order to help encourage economic growth while keeping inflation at bay.
The article suggests that the metric used to report on this market condition, interest rates, inflation, money support and so on, do not all lead to consistent interpretation. In other words, locally each piece of information means something that might be good – interest rates are low (which was supposed to encourage growth); inflation remains muted (which leads to stability in pricing, which helps – so the theory go – investment strategies), and yet pundits cannot agree if the market is:
- Getting tighter
- Getting looser
It seems we are at sixes and sevens when it comes to some of the economic metrics used to report where we are. I don’t have a quick answer for the Fed Chairman, nor do I have a quick answer for those clients looking for the ideal metrics. I do have silver bullets – bar the ones I had to leave in Calgary – long story; will tell you one day. But I can tell you that with enough understanding of the objective an organization is seeking to achieve, and knowing the stakeholders involved, we can get to the outcome and the metrics needed. Alas for the Fed, they play with much more complex systems.