Assigning Top-Down Quotas

Now it’s time to assign the quotas for each territory. In this lesson, we will focus on top-down quotas; in the following lesson we will assign bottom-up quotas. Our first step will be to set the quota baseline. A baseline refers to the starting reference value in the Quota Setting/Quota Breakdown process. The baseline may represent prior period historical performance, current period opportunity data, custom value, or a combination of the listed options.

The Distribute action initiates the quota distribution and acceptance workflow. This workflow allows sales managers to provide feedback into the quotas that are used for each of their territories and sub territories. The distribution action takes the current target values for the given territory or territories and replaces them with the pending target values.

As we saw earlier, when using the top-down methodology, the top-level quota is distributed to each territory, one level at a time, by the director or manager at each level, repeating until the quotas are assigned to the rep level territories.

In our scenario, we are distributing the top-level quota to the Vice President of Sales for North America. The vice president can then allocate quotas for the different territories on the next level down in the hierarchy.

Once you have distributed the quota on the top level, you can then distribute quotas to lower levels. This can be done in three different places, depending on your needs.

• Territory Program Detail tab: This distributes quotas for all targets to the affected territories.
• Allocation workspace: This distributes quotas for all targets that are associated with the subordinate territories.
• Manage Quotas: Use the Save and Distribute button to distribute quotas for all targets.

Now that the quota has been distributed, the payee assigned to the top-level territory can allocate quota values for each dimension.

Top-Down quotas can be set a number of ways. The first option is an even distribution of the overall quota across each dimension. If we have historical and opportunity pipeline data, we can use either of these, or we can use a weighted combination of historical and pipeline data.

Let’s look at a few examples of when we might use each allocation method. Bikes In Motion has a long history of sales in the USA and Canada, so they have enough historical data to forecast future sales, and therefore set realistic quotas. For this scenario, using historical values would be a good choice.

On the other hand, sales in Europe have only taken place for six months, which is not enough data to predict future sales. However, the company has built up a considerable pipeline of sales prospects, along with reasonably accurate estimates of the probability for each opportunity. For this scenario, Bikes In Motion would use the Pipeline option to allocate quotas.

Since we have historical data and we are using accounts as our primary dimension, let’s see how to use historical data to allocate quotas by account.