What do you think about when you forecast? For most people, it’s the data. More specifically, it’s taking historical data, applying algorithms, then publishing a forward-looking set of projections based on that. Many forecasters spend 90% or more of their time on the “historical” part of forecasting. However, what’s happened in the past is only part of the equation when looking forward. This is just the start.
Business intelligence is a critical component to getting the forecast right. What is Business Intelligence? It’s taking in the internal and external operating influences that can drive volume or productivity. This part of the process requires close relationships and regular touch points with several departments, including client management, operations, marketing, finance, sales and IT. Often, WFM (Workforce Management) has to take a very active role in engaging with these departments. You can’t wait for them to come to you because often they don’t know or understand the impact. WFM does.
Let’s look at a few of the areas to look at when forecasting. First are the things that will impact productivity:
Changes to Productivity
Generally, productivity is represented by “AHT” or Average Handle Time in a contact center. The longer a call takes, the fewer calls an agent can handle in a day. When Average handle time increases, productivity decreases and the headcount required goes up. This concept is pretty straightforward to workforce management (WFM) professionals. So, how can we get an even more accurate forecast for productivity?
First, talk to the operations leadership team. Is there anything inherently that will make handle time higher or lower than what it’s seen in the past? Some examples here may be a policy change that requires the agent to read a longer script, or verify a customer’s information. Quite often these changes are made independently of WFM, because they’re seen as “small changes” to AHT and focused on legal or customer service requirements. It may be determined that the increase in AHT is offset by some other factor. Unless this is tested through WFM, though, it can mess up the forecast.
Let’s look at the impact of a small change to AHT
In this example, a call center takes on average 95K calls per month with a 5-minute handle time and an 80/30 service-level goal. The difference between AHT being up or down 5% to the forecast can result in a 6 FTE swing in requirements. To put that into context, once you load shrinkage on, your 6 FTE becomes 10 heads. The impact to the financials is even greater because you’ll have additional salaries and benefits costs for that additional labor.
So what are some of the areas to look at for volume impacts?
The following drivers will change by industry and contact type, but they are common in many contact centers and can have a significant impact on the actual contact volume you receive.
The takeaway here is that WFM has to be actively engaged with the operations team to really understand how AHT will be different in the future than the past. It’s worthwhile creating a checklist, so you don’t have to remember every impact factor. Here are some examples to include in that checklist:
- Changes to policies or procedures that impact the call length
- Changes to contact routing (e.g. IVR or menu changes)
- Any changes to the products or services being offered
- Any marketing or billing materials sent to customers or prospective customers
- Changes in the customer tenure (a higher % of newer customers can mean longer calls)
- External factors in the economy or industry
- Service disruptions that can generate long complaint calls
- Expected long queue times (if you know you’re going to be understaffed, expect AHT to go up)
How should you divide your forecasting time up between data analysis and business intelligence? In my experience best-practice is to spend at least 1/3 of your time on the business intelligence side. That means if you took a 40-hour work week to build a forecast, you should spend about 13 of those hours on discussions with business partners to understand how changes in the business will impact the forecast, as well as, figuring out how best to capture those into your forecast.
This rule-of-thumb will vary. As you mature the relationships and regular touch points, you’ll be able to get the business intelligence factored in with less and less time investment. Additionally, for businesses where the data analysis is buttoned up, or that have a lot of automation in the regression analysis, you’ll have more time to reinvest into the quality of the business intelligence. The first step is to build in time for business intelligence and make sure you have a checklist of topics to surface, so that you don’t leave it to chance that you’ll get the information you need. You’ll not only get more accurate forecasts, but you’ll have stronger relationships with critical business partners.
Thanks to Charles Watson and written for injixo
This blog post has been re-published by kind permission of injixo – View the original post