Unreliable Data in PRP
“Our heads, just like our hearts, follow where they are appreciated”
The Task
We were tasked with creating a model to calculate fair bonus payments to be made to salespeople within an organisation, where the source of referrals (which they were to be targeted on) were not wholly complete or accurate.
The number of sales where the source was unknown was growing each period, much higher than the number of total sales, which meant each salesperson were seeing decreases in their area – despite the company reaching record levels.
Staff being told that they have not reached their targets was destroying motivation.
Arguably more important however was the company was breaching the employment contracts with its employees – as they all knew the data was wrong.
The solution
Glimpse Media made a model based upon the data that we did know. From the data that was recorded correctly, we could see the proportion of sales each salesperson contributed to each segment.
From this analysis, we can estimate that the unknown ‘bucket’ for each segment can be distributed in the same proportions as the sales data that was recorded correctly.
Once the same calculations and adjustments were made to the period prior to this, we could more accurately measure the growth (or decline) each sales person experienced.
The Outcome
Perviously, bonuses were unethically paid on guesswork and the measures for the bonus were changing each quarter.
This formerly illegal and demotivating practice was soon ended thanks to the introduction of the updated bonus model we provided.