The life sciences industry is evolving quite a bit, with more and more companies focussing on the research and commercialization of speciality drugs. These new product launches, at times, are in relatively newer areas and always bring in too many uncertainties with them. Despite thorough market research using epidemiology techniques and the availability of sophisticated forecasting tools/methodologies, it is often difficult to predict how a newer product is going to do in any particular market. Changing healthcare dynamics and competitive landscape in different therapeutic areas add to the overall prediction difficulty. Once the national forecast is determined, the next step is to allocate the goals to individual territories/reps using various volume performance and market parameters in accordance with broader strategic business objectives. Every incentive cycle, sales leadership/sales operation group face a difficult job of setting fair but challenging goals. As a company, you want your sales team to meet their goals but also push the envelope to enable business growth.

Lack of complete understanding of market dynamics and several other affecting local external factors for newer products in the market makes the goal allocation process cumbersome and inaccurate. There are several indicators which highlights the problem with Quotas/Targets:

  • Too-Few or Too-Many hitting targets
  • High performance standard deviation resulting in wide or uneven distribution of target attainment
  • Extreme outlier performances
  • Disconnect between performance and top/bottom performers
  • Performance of salespeople drastically changing over period
  • Systemic Payment biases based on specific market situation or historical product performance
  • Mismatch between team performance and business objectives

Ineffective goals may result in either windfall gains for the reps or can be de-motivational resulting in misalignment with business goals and may impact top-line revenues. In order for an organization to set fair but challenging quotas the following requirements are critical:

  • Reliable historical information at individual territory or rep level is available
  • National Sales Numbers can be forecasted with reasonable accuracy
  • Reasonable understanding of variation in sales potential across territories
  • Selling process is reasonably well defined

As you can see for newer products above information is either missing or inadequate (depending on the phase of the product) so, it is of the utmost importance to spend time understanding various success parameters and impact of different quota setting methodologies before finalizing the territory level goals. As the market understanding improves, there are new sets of information which can be considered to decide how to allocate the national forecast within territories. It is desirable to segment new product in 3 sub-groups based on their time in the market:

  • Just launched or yet to launched
  • Recently launched with less than 24 months of the sales history
  • Growing product with more than 24 months of the sales history

It is advisable to revise the goal allocation strategy once a product transcends from one phase to another. As with each passing phase, more reliable product and market information becomes available which opens door to the use of several other markers and helps with more reliable distribution of goals.

Let us discuss in detail what information we have at different phases of the product growth and can it be used to better estimate the territory’s potential for goal allocation purposes.

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Just launched or yet to be launched

This is the phase where a product is yet to be launched or just launched. It’s the most indecisive phase, as the volume of data and information available is highly limited. All we are aware of is efficacy of product based on clinical trials and it’s comparison with other products in the market. We do know that how the market has behaved in the past for similar profile products in the same therapeutic area or at times belonging to comparable therapeutic area. Given the limiting nature of the data available, we can use the following markers to get some sense of the goals for different geographies:

  • Potential based on # of patients
  • Potential based on existing market size calculated using performance of other existing products in the same market
  • Performance of proxy/analog product belonging to comparable therapeutic area

Combination of above factors can help an organization to come to a ball park estimation of the goal allocation percentage, but given the limiting nature of real product performance data there will be a possibility of certain territories over-performing while a few others under-performing. In these kind of situations, it is desirable to have a performance pay curve with lower threshold limits while higher excellence performance limits to ensure that more people are in the money but without windfall.

Recently launched with less than 24 months of the sales history

The second phase of the product is when product has been launched within last 2 two years. During this phase, we generally have access to some sales history in addition to better understanding of initial growth trends and market behaviour. Though, the available product performance data and initial market behaviour cannot be the sole parameters for calculating territory contribution but definitely needs to be considered as part of a broader fair-share calculation paradigm. The factors used in phase 1 continue to be relevant but it is equally desirable to add some weight to the recent historical sales as well. Logically some weight of the distribution of proxy product in phase 1 can now be shared by the actual sales of the product. This weight must be decided depending on the therapeutic area and the number of months since the product has been launched.

As we have short term history of the sales, we can use it to trend the sales for the goal setting period using sophisticated trending and forecasting methodologies. Customized time series methodologies works best for projecting sales data.

Therefore 3 factors which should be considered during this phase are:

  • Potential based on existing market size calculated using performance of other existing products in the same market
  • Weighted average of the % contribution of the proxy product and % contribution of the historical sales of the product
  • % contribution of the trended sales of the product trended over historical sales for the goal setting period.

Growing product with more than 24 months of the sales history

Once the product is in existence for over 2 years and has shown sustainable sales growth then that provides us good visibility into market’s adoption pattern and also it’s sustained capability to maintain existing sales or capture share from other competitors.

This capability to capture share from existing competitors (untapped potential) becomes another important measure to understand products capabilities to grow in each territory. Each territory is governed by various market situations like, the position in formulary list, type of marketing messaging and the quality/value of customers, distribution and supply chain, and many such demographic, social and geographical factors. Therefore it is advisable to give some weight to capability of the product to pull the sales from its competitor. A thorough competitor’s analysis within each territory is required before including this factor.

Also, when a product reaches a growing stage, the weight of the historical sales should be considerably increased with minimum/no reliance on proxy product’s performance.

To sum up, we should expect a better goal allocation by the time product reaches this stage because there is more reliable historical sales information about our product is available, therefore giving us the below four factors to consider:

  • Potential based on existing market size calculated using performance of other existing products in the same market
  • Weighted average of the % contribution of the proxy product and % contribution of the historical sales of the product
  • % contribution of the trended sales of the product trended over historical sales for the goal setting period.
  • Projected increase in the market share (based on individual territory’s untapped potential)

Conclusion

Setting goals for newer products in the market is a trickier proposition but being conscious about the product’s growth pattern and market behaviour / response in addition to some of the other factors can still be a good strategy to come up with reliable goals. Improving the perception of fairness in quotas can enhance the morale of the salesforce and can also maximize its sales effectiveness.

Various metrics discussed above can help in better understanding the territory potential and hence improve the accuracy of the allocated goals. These data sources are generally available within any life sciences company and leveraging these data sets along with robust quota setting methodology can significantly enhance the quality of quotas.

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