Forecasting changes in the near and longer-term futures

What is on the horizon? Given that contact centre forecasting disciplines have been in place for the last 25 years, it’s probably fair to say that it’s an area where innovation has been slow to take hold.

While Workforce Management tools typically address both scheduling and forecasting, more innovative organisations are now tending to supplement core planning with more complex forecasting work that’s carried out on spreadsheets before being imported.

For the next five years, the focus for organisations looking to optimise their WFM performance should be to extend forecasting activities beyond the traditional voice channel. Initial focus should be around forecasting for real-time channels such as webchat, and there really are no barriers to this happening now. After that, organisations should roll out effective forecasting to their non real time channels such as social media and email.

Over the next five years we also expect an increased rigour around how forecasters tap into the multiple Big Data sources that can help inform effective forecasts. Moving beyond basic call volume weighting, forecasters need to be accessing a broad range of internal and external datasets in order to build the most accurate forecasts possible. While some vendors are starting to investigate how to integrate this kind of Big Data functionality into their workforce optimisation offerings, it will probably take more than five years for this level of Big Data support to become an integral part of their forecasting offering. You don’t have to look very far for ways that organisations can take their forecasting forwards.

What is over the horizon?

By 2025 organisations will be building forecasts based on much more granular Big Data sources. For example, the widespread deployment of Internet of Things sensor equipped technology devices will supply service providers and insurance firms with real-time data about the current status of their entire installed base. From a forecasting perspective this will shift the planning focus from activity that might happen based on past history to an environment where forecasts are predominantly built in real-time based on actual anticipated customer demand.

While smart forecasters might already have a good idea of the events that currently lead to customer demand spikes, equipping products under maintenance with IoT connectivity provides an opportunity to smooth out demand curves through much more proactive customer outreach strategies. Within the next decade we’ll also see an increased shift towards augmented service, with agents particularly provided with much greater assistance in tackling the more complex interactions that will still need to be handled by live contact centres. Forecasters will also benefit from elements of AI support, however this won’t preclude the continued requirement for expert planners with an in-depth understanding of their evolving customer demands and an organisation’s ability to meet them.

Instead we expect the big forecasting performance improvements over the next ten years to come from a broader and sustained application of known technologies and processes. This will apply not just to the majority of contact centres that still don’t take advantage of available forecasting solutions, but also to those additional channels and functional areas such as the back-office that currently haven’t yet factored these elements of their business into their forecasting projections.