Uncertainty of Average Handle Time in Operational Forecasting

Last week, I discussed how to forecast one component of the demand equation—transaction volume. Today, I will write about the other component: Average Handle Time (AHT). Like my approach to forecasting transaction volume, my understanding of AHT has evolved a lot over time.

Average Handle Time (AHT) often presents a love-hate relationship for operational leaders and forecasters. Operationally, businesses are cautious about focusing too heavily on AHT, as it can lead to misaligned incentives for associates. Forecasters struggle to accurately determine AHT for a transaction, particularly when dealing with various channels. It can be straightforward, such as measuring the start and end of a phone call, or complex, like tracking a ticket that remains open for months, causing the AHT to continuously change. This uncertainty sometimes leads contact center leaders to ignore the metric altogether.

However, overlooking AHT is akin to asking a finance department to forecast a company's revenue knowing only the quantity of products or services sold, without the price per unit. In the world of optimizing contact centers, it's nearly impossible to properly size the center without understanding the AHT of transactions. Metrics like Calls Per Hour or Transactions Per Hour are derived from the foundational metric of AHT, which is why I prioritize it in demand forecasting.

Here are some key insights I've gained about forecasting AHT:

1. In an omni-channel environment, AHT varies significantly, and there will always be some uncertainty in its accurate capture. For instance, AHT for a ticket is measured differently from a synchronous channel.

2. AHT at the business level differs from that at the associate level. For example, if a ticket routed to a service associate is handled for five minutes before being transferred to a sales associate who spends another five minutes, most systems would attribute the full ten minutes to the sales level, but only five minutes to each associate. 

3. AHT forecasts should align with associate-level targets to ensure that the entire team is working towards the similar goal which inevitability will reduce variability in Full-Time Equivalent (FTE) requirements.

4. It’s crucial to balance the effort spent forecasting AHT across different channels, business areas, and types. More time should be invested in channels that constitute a larger portion of demand hours. 

5. As business conditions evolve, the methodologies for calculating and utilizing AHT in capacity plans must also be updated frequently.

6. Accept the variability in AHT and have transparent conversations with the business leaders on the pros and cons of definition AHT one way or the other. 

Understanding and accurately forecasting Average Handle Time is crucial for effectively managing contact center operations. It enables leaders to align resources with actual needs and adapt to changing demands. By continuously refining the approach to AHT, businesses can ensure they are not only meeting current demands but are also prepared for future changes.