Quota Setting for one of the leading global vision care organizations, with operations in 60 nations and customers in more than 140 nations.
The Vision Care business unit had an established quota-setting methodology, but the entire process had its own set of challenges:
- The biggest test was to do a quota setting for a portfolio of products with no market data. Without some form of market data, the actual quantification of potential as well as their current market standing, was unknown
- Quota setting for a portfolio of products where each product was in a different phase of its life cycle was a daunting and challenging task. Add to the mix that the entire portfolio was promoted by the same team and the challenge doubled. The portfolio included:
- Mature Products with stable historical sales
- Mature products starting to lose their market
- Seasonal Products
- And the wildcard in the mix was a couple of recently launched high-growth products
- The current process owners created a methodology using statistical parameters that required significant manual work and was a black box for the sales team. They also had no way of doing some basic analysis like and evaluate the quality of allocated quotas – “Is the quota set fair?”, “Are we paying for performance?”, “How does it compare to a different approach?” and so on.
The client reached out to Aurochs with the help of our professional services partner primarily to automate their current methodology, which required significant manual work and was very time-consuming. They were looking to achieve a high level of process automation, change agility and responsiveness, the ability to incorporate local guidance and knowledge, model different factors and evaluate the quality of allocated quotas. The key requirements were:
- High levels of automation and repeatability for their current quota allocation approach using statistical parameters
- The agility and flexibility to try out different permutations and combinations of historical sales and growth parameters for quota allocation
- Use historical sales and growth-based parameters for quota allocation and give credence to local knowledge while doing quota allocation
- Analytical visualizations and statistical summaries to analyze if the quotas set are fair, paying for performance, and so on
- Ability to customize historical periods and add caps and floors to handle outliers and make sure that quota distribution is in line with company goals
- Ability to define scenarios using different forecast scenarios
- Deploys integrated quota management platform with backup support and service operations
The lack of market data necessitated that we look closely at the existing process and evaluate it alongside newer ways in which quota allocation could be done.
To make that possible, the 1st step was to integrate the current statistical process into the tool so that it could be compared with different models. To spice up the results, we also added the ability to add scenarios to the statistical process, which was something that they had really wanted to do but were unable to do in an Excel sheet due to the complexity.
We added models based on volume, volume + growth, and the current statistical models with scenarios and compared their results. For mature products with stable history, we looked at the ML-based sales forecasting trends and used them while doing quota setting. The post-hoc analytical visualizations helped evaluate the methodologies from all aspects, like fairness, performance, and outliers, before coming to a decision.
In addition, we spent time comparing the quality of quotas generated using their traditional statistical process and new Aurochs processes with actual sales results. This helped the client identify gap areas in the entire process.
Quota Manager Platform Rollout
- Data from different sources were collected (primarily, in-house data warehouse), collated, sanitized, and ingested in an automated manner with the click of a button using our proprietary Data Manager
- Aurochs Quota Manager was configured to account for different scenarios involving – historical performance data periods, different sales factors, volume growth, sales trends, caps, floors, etc.
- Configured testing scenarios to evaluate the quality of methodology by allocating quotas for different historical periods
- Designed summary calculation workbooks and reports for quota communication
A comprehensive approach to managing the quota allocation process helped the client see significant improvement in several areas:
- End-to-end automation of quota allocation process with statistical parameters that reduced the processing time by >90%
- Started as a pilot for a small set and eventually got implemented for all teams, roles, and salespeople
- Simplified quota setting process and communication at several places with better results
- Provided the ability to evaluate the quality of quotas at an individual level as well as at the role level
- Additional capability to do scenario simulation for their existing quota allocation methodology
- Easier identification of bias in the quotas due to geographical performance trends