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For as long as customer service has existed, people have been invested in cracking its code. However, as an industry that faces constant change and ever-increasing customer demands, landing on the perfect method is a little less like finding the Holy Grail and a little more like carving a melting ice sculpture.
Contact center managers have relied on tools like forecasting and scheduling spreadsheets, Erlang-C and workforce management (WFM) tools to prepare and respond to demand. But accuracy isn’t necessarily guaranteed for any of these methods — managers now need to look to newer, more innovative technologies to better meet service levels and deliver high-quality service at a reasonable cost.
I recently spoke with Robert Beasley, Global Director of Strategic Solutions for Workforce Engagement Management (WEM) at Genesys, to gain deeper insights into the challenges that modern forecasters face — and why artificial intelligence (AI) is their best bet when it comes to attaining better accuracy and crafting highly effective schedules.
Why is manual forecasting still prevalent in contact centers today?
Robert Beasley: Forecasting and scheduling are such complex tasks; it’s not uncommon for contact centers to have very specialized, highly skilled forecasters with a wealth of experience under their belts. These forecasters have built over time their own approach and processes to arrive at forecasts that serve them well — and that can be on an Excel spreadsheet or even a combination of spreadsheets and WFM tools.
But, because these processes have worked for them, and because they know their contact center so well, the idea of switching over to a different approach can be intimidating. I get it; I was a forecaster; I was a scheduler; I’ve been in these shoes. So, I understand the complexities that go into it. I’m also a big fan of Excel, so I’m not meaning to say, “Hey, don’t use Excel.” Maybe, it’s better to say, “Let’s try to open our minds and take advantage of some of the automated capabilities that are out there.”
Why should companies look to leverage technology to create forecasts and schedules?
Robert: Forecasting isn’t a simple task — for many people it’s actually quite difficult. It’s not just a simple time series analysis where you’re looking for missing data and filling in some gaps. It’s also trying to find outliers and trends that might not be easy to see with a quick glance over some data. It’s important to understand what constitutes an outlier and what constitutes a trend (good or bad). And you need to ask yourself if these outliers are one-time occurrences or if they’re a series of outliers that are trending and developing across months and years. And when you believe you have found the answer, it’s about finding the appropriate pattern inside all of that data. What is the right data set? Does everything align? Do you need to make adjustments? With that information in hand, it comes down to selecting the appropriate model to arrive at the most accurate forecast.
With Genesys Cloud™ Workforce Engagement Management features, we’re are not just looking at a basic Erlang-C or a modified Erlang formula. We’re looking over more than 25 algorithms to arrive at the best possible outcome.
Where does AI fit with Genesys Cloud Workforce Engagement Management features?
Robert: With AI-powered automated forecasting inside of Genesys Cloud, you get one-click planning in 30 seconds, and you leverage more than 25 different algorithms that give, from what we’ve seen, up to 97% accuracy. Once you have confidence in a highly accurate forecast, you can then be confident that you’re generating the best set of schedules to meet your needs. This is very important, because this is one of the areas where I have consistently seen individuals make some of the biggest mistakes. They forecast, but they create schedules that don’t necessarily match that forecast.
It’s not uncommon for me to come across situations where contact centers are understaffed in the morning, at noon they’re net neutral, but by the late afternoon they’re overstaffed. When this happens, how do you build schedules to best meet that type of coverage window? Are you schedules set? Do your schedules offer a lot of flexibility? Ultimately, this is about providing the best set of forecasts, with a model that you’re confident will give you the best outcome so that you can schedule to that.
What does it mean to have a visionary WEM solution?
Robert: It’s really simple, actually. Your employees sit at the heart of everything you do. A good employee experience can go a long way for your company, just like a bad employee experience can go a long way in the wrong direction. So, it’s important that we’re outfitting these employees with the tools to be successful.
For Genesys, it comes down to a few core tenets:
So, at the core, there’s one theme: improving employee engagement. When you think about an agent’s experience, they’re faced with a lot of demands from the get-go. They’re expected to achieve an acceptable level of performance after two or three weeks of training, but they’re also being asked to become experts at any number of tools and capabilities the company has. They need to be proficient with voice calls, email, chat, social, scheduling tools, quality tools, coaching and learning tools, analytics, dashboards, gamification… and that’s without considering additional tools like CRM, knowledge bases, intranet sites, HR tools and so on. This many tools, coupled with high performance expectations, can be overwhelming and can lead to technology fatigue in the agent.
Genesys Cloud helps combat that complexity by making all these tools simpler and more efficient — and delivering as much of these contact center capabilities as you want to consume from a single place.
Join Robert’s session at this year’s SWPP Annual Conference to hear his insights on forecasting and contact center management. Alongside other Genesys WEM experts, Robert will share his workforce management know-how during The Virtual Summit for Workforce Management throughout this month.
Find out how AI can improve contact center and agent performance in this brief.
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