by Kurt Schroeder and John Seeds
Workforce management has come a long way in a very short period of time. As modern tools such as AI-enhanced forecasting and scheduling become the preferred options, best practices continue to evolve. Previous to these tools becoming available, figuring out the number of people needed per hour for each service level and factoring in shift preferences, breaks and mealtime, all had to be done by hand. This process was ultimately left to team leads and those leads also needed to gauge call volume when making these decisions.
It’s critical that your organization engages with innovative solutions and technologies that will transform your workforce management. Tools today enable your organization to move past manual processes and allow you to view multi-week forecasts and schedules across all your queues, media types and skills without a single calculator or email.
Our Senior Director of Innovation Architects, Robert Wakefield-Carl, sat down with our Senior Workforce Management Consultant, John Watkinson, to discuss new developments in workforce management and how companies are missing out on these technologies.
Senior Workforce Management Consultant
John Watkinson has over 20 + years in the contact center industry. Prior to this role, John worked at Interactive Intelligence for 10 years. He held roles including WFO Consultant, Sr. Training Consultant, and Sr. Technical Sales Consultant. John’s primary responsibilities include working with strategic accounts to assist with contact center best practices with a strong focus on Workforce Management. This also includes in-depth training of the interaction Optimizer product, everything from front-end consulting to initial set up and end user training.
[Robert] John, you have been in this industry for 20 years. What have you seen as the single most import technological change in WFO/WFM over that time?
[John] That’s a tough one… If I had to pick one thing it would be the ease of use for complicated calculations and schedule jockeying because it reduces it to a few clicks of the mouse. When we first started you had to go to class for weeks just to understand workforce optimization before you could even begin to generate meaningful schedules. Now, I can train up an analyst or supervisor to produce fully optimized schedules across the entire organization in just a few hours and it takes them so much less time.
[Robert] I agree, simplification of the tasks to forecast and schedule is a definite ROI when it comes to adoption, and when you look at what the AI does in the background with the different optimization techniques and algorithms – I couldn’t even think of the hours that would take to do by hand. Also the way you can manipulate schedules by just dragging and dropping to make changes is much easier.
[John] It is not only that. The AI can take in so much more information that we could never include in our old erlang-C calculations. Things like ASA, Handle Time, Multi-Skill, abandoned rates, and so many other data points can determine the optimal algorithm along with the method for the absolute best estimate for forecasting future volume. When you combine that with the what-if scenarios you can include, you can get headcount down to 1 or 2 FTE of actual needs through each day – weeks ahead of time.
[Robert] All true. How has this technology segment morphed from when you first got into it and what you are working with today?
[John] We used to only involve WFO for forecasts and schedules – never anything more than the output of a paper or digital schedule in the agent’s calendars. These days, we have agent-driven time-off request, shift swapping and bidding, performance-driven learning management, quality management, speech analytics, knowledge management for agent assist, customer surveys, and predictive routing all based on how agents are skilled, scheduled, optimized, and utilized. The entire product is now truly Workforce Engagement Management – so much more than scheduling.
[Robert] But the core is still scheduling and optimization of the workforce. That still takes time to learn and skill to operate doesn’t it?
[John] That is the real difference -the system works for you! Yes, there is “some” manual intervention, but the system will “alert” you if something is going not as planned, high interaction volume, High AHT, SL Goals dropping etc. This will allow us to be more proactive that reactive – You no longer have to wait until later into the day or tomorrow to see if negative events are happening in your contact center
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[Robert] Quite a bit to take in there. I understand the learning management and quality management being part of WEM, but where exactly do you fit in things like speech analytics and predictive routing?
[John] Many of these features are just being developed but we are months away from those being reality. Here’s an example: Imagine that the speech analytics engine watches for certain keywords or phrases and is able to judge that an agent consistently gets better sentiment scores in the afternoon than in the morning. You would want WFM to be aware of that and offer more afternoon and evening schedules to that individual.
Another integration would allow the WEM system to understand agent handle time for certain types of calls and automatically schedule learning management to improve that time and schedule the learning module for them without hurting your occupancy. There are so many combinations of technologies to help agents engage customer more efficiently and to create a lower cost of running the contact center by allowing agents to handle customers faster and with better results on the first call.
[Robert] I would assume things like knowledge management and agent assist can play a big part.
[John] Yes, especially with work at home agents. Agent assist gives the information from the knowledge management system in real-time to agents as customers speak or type keywords so they can respond faster and more consistently. We could eventually base the use of agent assist to drive learning modules to the agents based on the conversations we mine using speech analytics. Now that we have so many technologies under one roof, it is so much easier to design scenarios for better customer experiences through agent knowledge enhancements and scheduling. That is what WEM is all about – one toolset to optimize and engage your agents.