Following up with the second part on identifying quota fairness for volume-based quotas. We will use Absolute Volume Growth numbers to test quota fairness in this blog. Absolute volume growth by itself is a deceptive metric as it bases your analysis on absolute numbers without giving any indication of how substantial the volume growth is as compared to the considered baseline.

Let’s use an example to understand this metric, 2 territories can have an absolute volume growth of 500 but the territory size or baseline product volume of one is 5,000 and the other is 50,000. As baseline product volume or territory size is missing in our dataset/analysis so we do not have the complete picture to come to a conclusion.

Hence, the underlying guideline while using this metric is that Absolute Volume Growth does not have any relationship with territory performance as this metric by itself is not sufficient to define a relationship.

Similar to the Baseline Product Volume metric, we start with determining a historical test period to evaluate the fairness of quotas, i.e. a historical period with stable and achievable sales that can be used as a benchmark to evaluate the current quota set. In this case, we used the Aurochs Target Setting philosophy and in-house quota management tool to set quotas for the test period and calculate Territory Achievement.

**Quota Fairness Test 1**

The 1st way to evaluate the fairness of your quotas is by creating a scatterplot of Territory Achievement against the Absolute Volume Growth of territories in the test period.

The above out-of-the-box scatterplot shows the relationship between Territory Achievement and Absolute Volume Growth of a territory. Looking at the scatterplot we can say that:

**Observation:**

- The achievement for territories with negative or small absolute volume growth is pretty evenly spread out
- Territories with Absolute Volume Growth greater than 45k approx. are exceeding their targets
- Achievements skyrocket as the Absolute Volume Growth increases

**Takeaway:**

- The quota set can be called out as fair for almost all territories with small absolute volume growth, as there is no relationship between the growth and achievement
- The quotas are biased towards territories with large absolute volume growth territories. Without the territory size, we cannot rationalize this relationship which in turn tells us that the quota set may not be fair
- Quota needs to be evaluated for skewness on a more tangible metric like Baseline Product Volume or Percentage Volume Growth and any imbalance can either be handled as a part of the quota refinement process or by adding a small tweak to the methodology/indices used for quota setting

**Quota Fairness Test 2**

The second way to evaluate quota fairness is to bucketize the absolute volume growth numbers using the 20-60-20 analysis which distributes the audience in small, medium, and large buckets. We then used the out-of-the-box capability to create a boxplot of each bucket with their territory achievement.

A boxplot or a box and whisker plot tells you how the values of a variable are spread out where the box has 50% of the concentration and the whisker tells you the top and bottom 25%.

The above box and whisker plot tells us the spread of territory achievement for each bucket. These buckets have been created based on the Absolute Volume Growth; small, medium, and large.

**Observation:**

- At a glance the above box and whisker plot tells us that absolute volume growth has a highly positive relationship with the territory achievement, the smaller the volume growth lesser the achievement, and the higher the volume growth higher the achievement.

**Takeaway:**

- Looking at this from a layman’s point of view, this is good. But let’s go back to the example discussed at the start of the blog, any clear relationship with Absolute Volume Growth by itself indicates that the results may be skewed.
- Similar to the scatterplot example, we need to evaluate quota fairness using a more tangible metric and use the quota refinement process or tweak the methodology to get rid of the skewness determined in the quota set.

In conclusion, we need to evaluate and make sure that the quota set for the field force is fair and achievable. There are several metrics that help you identify unfair quotas. Either of these metrics is a good indicator for you to step back, evaluate and take corrective measures to fix your ongoing quota methodology.

In our next blog, we will discuss how we can determine quota fairness using percent volume growth in territories.