Collections Capacity Optimization - Part 3

The following article is the third in a series from credit cycle consultants PIC Solutions that looks at optimizing the capacity of collection operations in a bank or financial institution environment. PIC has written many articles on collector effectiveness at the creditor level.

Recapping on our discussion on collections capacity optimization thus far, in Part I of the series we argued that capacity optimization is critical to managing resources within a collections environment.  We further argued for the need to monitor the right metrics, in order to be able make meaningful conclusions of the collections resourcing required.  Part II of the series discussed one of the fundamental metrics which underlies capacity optimization, namely volume.  In particular, ways in which volume could be forecasted were entertained and it was contended that time series decomposition forecasting techniques are a useful and convenient means for collections professionals to make use of in forecasting collections volumes.

In this, the third part in the series, we proceed to consolidate on what has been presented to date by discussing a basic working model for optimization.

Building a Basic Optimization Model

In order to calculate the total number of collectors required within a collections environment, the following steps should be followed (these steps are illustrated by way of example in the accompanying table):

• Step 1: Calculate the total number of required connects by dividing the forecasted volume of accounts by the Right Party Connect rate (RPC rate)

• Step 2: Calculate the total time required to work through the RPC contacts by multiplying the volume of accounts by the time required to get through each RPC contact

• Step 3: Calculate the total time required to work through the non RPC contacts by multiplying the volume of accounts by the time required to get through each non RPC contact

• Step 4: Add the results from Steps 2 and 3 in order to determine the total amount of time required to work though the volume

• Step 5: Determine the total number of minutes which each agent is able to work for in a working day

• Step 6: Divide next the output from Step 4 by that of Step 5.

• Step 7: Finally divide this all by the inverse of the Overhead. The Overhead is the time that is wasted due to staff taking leave and so on and is generally between 5% and 15%.

This process demonstrates how to assemble a basic optimization model to determine the number of collection agents which are required within a collections environment using relatively few variables.  In next month’s tip we will consider nuances of this basic model, showing that it is not necessarily as simple as it would seem – it’s only as complex as you want to make it.

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