The forecasting step is one that every company needs to do, yet not all those in charge of the process enjoy doing. There tends to often be a reliance on historical data that sometimes plays too heavily into the mix. When the forecasted timeframe comes along, extenuating variables may have played a part that no longer exist or vice versa – creating a much different reality than what you expected.
If this occurs for omni-channel customer engagement, the outcome could cause more damage than you imagine. Consider the customer who prefers the self-service channel for managing information and interactions. Upon a standard visit, he discovers that his information is not available in the standard location and there isn’t a way to access it through other means. He’s stuck and he can’t take the next step he wants to make. He switches over to the competitor, quickly sets up a new account and completes his transaction.
It’s not readily apparent in this example exactly what happened to cause this problem, but let’s assume that forecasting was based solely on historical data and didn’t take into account that the database has grown 300 percent. Let’s also assume that there’s a new special going on and those who take advantage by the end of the day get an extra discount. This special was heavily promoted and the app was inundated with self-service customers seeking to take advantage. But the app crashed under the weight of the traffic and our customer example above wasn’t the only one who couldn’t complete the transaction and decided a competitor was the better offering.
While forecasting for the omni-channel customer engagement experience is not the only thing that could have prevented this problem, it could still lend considerable value. When you harness that data you already have, you can take your forecasting to levels that you haven’t yet enjoyed, taking the customer experience over the top. A recent Aspect (News - Alert) blog examined the potential here, and why the spreadsheet is no longer equipped with the necessary capabilities to help with effective forecasting.
That means it’s time for a strong technology solution that enables you to harness all of your data and interpret it correctly to enable strong forecasting. This is particularly valuable as it enables both internal teams and outsourcers to accurately predict periods of high demand so they know when they will need all available resources. It also helps them make preparations for what they need to do during slower times so that agents are not sitting idle.
The use of predictive analysis tools and advanced workforce management solutions help to spot opportunities early so as to better leverage forecasting capabilities. These tools bring all data into one location so that forecasting not only takes into account all relevant information, but also delivers a more accurate outcome.