Performance conversations have a way of recurring around the same theme.  Some claim that better performance would have been possible if the resources granted were better matched with the opportunities in the market, i.e. if they had received more resources (more capital, personnel, marketing spend, equipment, rent etc.) Others will explain the challenges they face in meeting the recommended targets, given their particular circumstances, arguing they are unique, unlike anyone else in the market, essentially immeasurable!

 

When performance centers are compared against the averages of a population of others sharing certain general labels or attributes, there is always room for discussion. All performance centers are similar in some ways and quite dissimilar in others, making it difficult to objectively argue that a certain level of performance expected of them is truly fair and appropriate.

 

For example, in retail banking, not all "small business" branches are really comparable, neither are portfolios of high-net-worth clients.  Yet, there are always peers that are reasonably similar and at higher levels of performance.  Executives could consider allowing each manager to select a few peers. These self-selected peers would most likely change from one area of performance to another e.g. Customer Service Levels vs. Cross Selling. 

 

The primary objection to “self target setting” based on self selected peers is that managers would make the easier selections, resulting in targets that do not meet the overall enterprise targets.  This is actually what often takes place, followed by an even spreading of the difference with offered and asked performance.

 

What if there was a system that determined a few higher performance peers for each unit and allocated the required level of resources and performance targets simultaneously for all, such that enterprise targets would be allocated for highest possible efficiency? It is exactly this question that we at Alta Bering address.

“Averages are over” argues writer and New York Times journalist Thomas Friedman in his latest book That Used to be Us. Indeed they are. Not only is average performance just simply not good enough anymore in the global competitive environment but so is the notion of performance averaging. Looking at averages in performance levels across a wide range of units - whether they are individuals, sales offices or retail outlets - may have statistical value looking backwards in time.  But where an enterprise is looking to maximize its performance potential averages are of limited value and often even counterproductive).

 

At Alta Bering we propose instead to look at the lonely frontier, i.e. those sparsely populated places on the top of the performance chart that indicate the frontier performance level achieved by a minority of outliers. In other words, we believe that instead of looking at what the majority has achieved we should be leveraging the information provided by the top performers to guide and stimulate overall performance. But to understand what exactly drives frontier performance, a multidimensional analysis of all the factors at work is a must…