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Isolating factor

The latest research into salesforce effectiveness provides fresh insight into how teams function and crucially, allows managers to identify factors driving stellar performance

It is an old adage that you can't manage what you can't measure, and salesforces provide a prime example of this principle. Yet, thanks to the latest leading-edge research and salesforce metrics, previously unrealised performance gains are possible, offering an important lever of sustainable competitive advantage.

The old salesforce model assumes that salesforce performance follows a normal (Gaussian) distribution where average performance clusters at the centre of a continuum between poor, unsatisfactory performance, and the excellent performance demonstrated by top sales people. Under this model we provide a strategy and direct our salesforce to carry it out. The tools we use are worn with age but include customer priority lists, key performance indicators, call rates, coverage, frequency and post-call assessment.

Under this set of rules our task is to maximise coverage of priority customers, ensure that the majority of customers are seen at an effective frequency and give our salesforce the correct training so they can deliver the appropriate message at each and every call. It is a model built on consistency, where the management task is to shift the modal performance to the right of the curve.

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The reality is that although this system is effective to a degree, most companies follow essentially the same process, and several of our key assumptions are wrong. First, the intended strategy - what we expect our salesforce to carry out, is modified by each and every sales person. Second, it assumes a certain degree of homogeneity of customer response, illustrated by our customer target lists. Third, the sales response does not usually follow a normal distribution, which incidentally invalidates the majority of the statistical methods used to measure it.

What actually happens is that sales people are opportunists (if they were not then we would not employ them) and they adapt our strategy instructions, based on how they perceive them, their selling history, the training they have received and a myriad other factors. These individual actions are then tempered by their experience, reinforced by results, and modified in the light of relative success or failure. A further important factor is that sales people copy and learn from their peers. Which one of us, when working with a previous company, has not picked up an idea or habit and deployed it to the benefit of our current employer?

We are creatures of habit and our ideas become combined in our ways of working, we adopt successful practices and copy or adapt the actions of other sales people, field trainers, etc. The result is that different strategies develop within a common salesforce, and the performance implications of these different strategies can be very marked.

Research to date, carried out within a range of leading UK pharmaceutical companies, indicate that there are frequently six to eight very different and distinct strategies operating within the same field force. The important finding is that performance between these different `ways of working' often differs markedly (see figure 1, right).

In the diagram below, the most common (modal) strategy is assigned an index of 1. Each of the other strategies is compared to this index. This illustrates that reps deploying the most effective strategy (strategy 2) are on average 37 per cent more productive than reps pursuing the average (most common) strategy. Strategy 3, the second most effective strategy, produces 26 per cent more sales per rep than average. This means that if the rest of the salesforce could be persuaded to adopt either strategy 2 or strategy 3 then sales would increase by some 30 per cent. This represents a considerable window of opportunity to ratchet up sales results.

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Understanding the realised strategies of your salesforces helps explain the variation between mirror salesforces, selling the same product, on the same territory. It also allows us to isolate the factors which drive stellar performance. A common observation when presenting the results of this analysis to a pharmaceutical company is that the top reps occur in the same high performing group. This often prompts the remark so that's what they have in common.

If we examine mirror sales teams (see figure 2, right) a common finding is that results can differ markedly between teams of the same size selling on the same territories. Figure 2 shows that salesforce number 1 is considerably more effective than sales-forces 2 or 3 despite delivering less calls than salesforce 2. This indicates that salesforce 1 is a higher quality team.

Often, different results between salesforces can be quite marked in two key areas. First, some teams deliver a much higher unique contribution to sales as compared to merely reinforcing the other teams' effects. Second, quality between salesforces can vary significantly. This is especially true of contract sales teams.

The implication of these findings is that there appear to be several viable strategies to selling a given product, one of which is optimal and clearly outperforms the others. The number of realised strategies in a field force varies, sometimes it can be as few as three, occasionally as many as 10. There is, however, invariably a significant difference between the most common strategy, that which most sales people follow, and the most effective strategy. Often this can be 50 per cent or more. This represents the `low hanging fruit' of sales performance where by migrating more reps from a less effective strategy on to a more effective strategy significant productivity gains can be achieved. The insights gained by this analysis are thus both practical and informative where with the aid of a straightforward template a regional manager can direct his team more effectively.

A further implication of this research is that we can now begin to really dissect the different activities that contribute to performance. Figure 3 (right) shows a standard promotional model which demonstrates the dominant effect of salesforce activities on performance. The main activities driving sales, in this instance, are appointment calls, in surgery meetings, opportunistic and follow up calls. These are some of the elements of a successful sales strategy where they represent different dimensions of salesforce activity, measuring planning, opportunism and persistence, respectively. These are all recognised as qualities of a successful rep.

Aside from the more obvious factors, other elements which may contribute to a salesforce strategy include time on territory, training courses attended, type and nature of tertiary education, and so on. A considerable asset of a pharmaceutical company is the collected data. We benchmark everything, but unfortunately we often fail to make use of it, or choose to discard useful categories in favour of a more simple approach. This is a mistake which may lead to a loss of competitive advantage.

Strategy is a question of what we choose to do from the many choices around us. What we do versus what we do not do. Sometimes the choice is obvious but more often it is a mix of overt and tacit activities. It is the tacit activities which we cannot see that underpin competitive advantage. Traditional analysis fails to take account of these tacit processes but they are very often the linchpin of performance. An observation supported by the considerable body of strategic management literature devoted to the resource-based view of the company.

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The research presented here offers a number of benefits. It provides a fresh insight into how salesforces function and why one team outperforms another. It also explains a great deal of salesforce variation and why different teams make a success of a given product, while others do not and it provides the opportunity to separate one team from another.

We can for example separate sales driven by target calls versus non-target calls and decide whether our target list is wearing out. We can calculate return on investment on a given cohort of reps, a team, or an entire salesforce. Thus, we can compare sales teams like-for-like. Which regional team is the most cost-effective? Is our contract team generating significant extra sales, covering its costs effectively or adding heavyweight costs to an already overstretched budget?

To date, most firms rely on benchmarking the activity - coverage of target doctors, recall of key messages, etc. This is the old black box model, where we assume actions link to sales. To assess the effect of activities, it is not good enough to measure post-call effects, or to plot sales against activity. These graphs can hide a multitude of different explanations; are we seeing the correct effect or has the external effect not captured by the graph? Appropriate analysis includes all factors where each can be weighted and assessed in relation to its peers.

Only then can we discern which activities directly influence sales growth, which contribute a shared but not unique effect and which are displacement activities of limited, if any, commercial value. With these tools we can craft effective strategy, without them we are still reliant on past assumptions. Market change brings new opportunities and threats to our competitive position. The environment is changing and our strategy must match it. Only through appropriate measurement can we effectively manage strategy to this aim.

The author
Graham Leask is a member of the economics and strategy group at Aston University in Birmingham

13th March 2007

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