Sales force optimization in the healthcare industry ı In the first part of this guide we discussed the main resources optimization challenges the pharmaceutical industry is facing. Optimizing two types of resources - Products & People - can be tricky ; in the second part of this guide, we provided you with a comprehensive methodology to optimize your product portfolio. Today, to complete this three-parts guide, we are going to look at your sales force sizing and structure.
On the people side: What is the optimized number of sales reps and how to reach it?
The calculation is usually simple math using visit frequency and customer concentration curves, but the Holy Grail is lying in the precise understanding of the dynamic in people interaction and their response to the promotion.
1. a. How to determine the right frequency of visits/calls? Response-to-promotion curve.
The investment we do by visiting specific customer groups should pay off at the end. Customer response to promotion differs and the highest adoption (or prescription) is only generated after a certain number of visits and calls. This means we shouldn’t just randomly visit customers: optimal frequency is to be computed getting the best ROI.
But how do we actually get these numbers? There is a very good logic behind this, based on psychological aspects of adoption represented by: the response-to-promotion curve.
Each curve represents the share of prescriptions relative to the number of visits over the year. This lets us identify a cap – that is to say the optimal number of visits before they become less profitable than the previous ones – which ultimately yields the optimal visit frequency.
These curves differ according to HCP specializations and are influenced by cultural differences too. Generally, we can say that the magic is in finding the right balance between a too high frequency (which can lead to overcalling syndrome) and a hardly maximized ROI (when frequency is “just right”).
1. b. Do we need to cover all HCP? Concentration curve shows not! Then, what proportion of customers should we cover?
Customer value differs and prescription is concentrated at the beginning of the curve, reminding the 80/20 Pareto rule. This curve computes the share of prescriptions relative to the share of prescribing customers or doctors. This helps us identify how many customers we need to focus on and who the most important doctors are – the ones our reps need to focus their time on. Sure, we count with precise and dynamic customer profiling, segmentation and targeting.
Now, how do we get the right number of reps? The optimal frequency and coverage can help browse the right numbers by combining these two approaches. That is to say: combining the information you get from the concentration and response-to-promotion curves to understand the highest ROI that your optimal visit frequency can yield.
We now have a precise and complete methodology to optimize our second resource: people.
And finally, using the Concentration curve together with the Optimal frequency per segment, we can easily compute the sizing and structure of the sales force.
The combination of our strategic analysis and commercial prioritization results in an optimized scenario, which is ready for P&L testing and fine-tuning when necessary.
The final sales force structure is based on both managerial and financial decisions and respects an optimized ROI approach. This can be fine-tuned anytime during or after process and saved as a separate scenario for future comparison.
Sales force optimization results
We now hope you have been provided with ways “to reach more with less” ; decision making tools and methodologies to meet both your product growth and commercial excellence objectives have been already proven and adapted over the last years in about 30 countries worldwide.
This is where Actando comes in: helping you use these tools to solve your main optimization issues:
- Do I have the right number of the reps in the proper sales team structure?
- How many people do we need in future?
- What products should we promote?
- In which way?
- How can I compute P&L forecasts per product or per sales team?
This results in comprehensive scenarios backed by data analysis; identifying the optimal sales force size and structure to promote the combination of products that brings the most value to your company and your customers.
We strongly believe that not only consultancy companies can provide you with the optimization process and results for your business but, with these commercial excellence decision making tools and appropriate training, you can easily internalize all of this best industry practices and that’s why we encourage you: “…you can do it!”