Currently, there is a revolution going on in artificial intelligence. ChatGPT is disrupting many markets, including customer contact markets. What will be the impact of these robotic types of activities? Is this going to replace human interaction? This question is probably now on the mind of every contact center professional.
ChatGPT can sometimes give better customer support than live agents! Thus, ChatGPT will replace some of our customer contacts, especially once it is readily available through the search engine Bing. How much and how fast this will happen, nobody knows, but when you experience an unexpected drop in volume, you know in which direction to think. On the other hand, ChatGPT composes its answers using texts available on the internet. It cannot give answers to questions for which the answer is not publicly available, thus there is a limit to what ChatGPT can do.
ChatGPT in Workforce Management: A Test
Will ChatGPT also change our internal processes? And more specifically, can it simplify or improve WFM? Let’s put it to the test. The first question we asked is: “What is the best algorithm for contact center forecasting?” We get a long answer that makes sense; it even suggests using linear regression, including factors such as marketing campaigns, which is a pretty good method. Its answer is not completely correct, it suggests also using logistic regression which is not appropriate for this kind of situations. This is a known issue with ChatGPT: it produces what is commonly said in similar situations, but there is no concept of true or false in the algorithm, and there is no guarantee that the answer is correct. When we get more concrete and give some simple data containing seasonality and trend, it does not recognize the components and produces wrong results. Also, when asked for staffing models, it comes with an elaborate text, but Erlang is not mentioned. We conclude that ChatGPT is worth trying if we are looking for an answer to a typical customer support question; in a way, it is a knowledge system that obtains its information from scraping enormous amounts of data on the internet. But if we want to be sure about the correctness of an answer, or when answers to closely related questions are not yet answered on the internet, ChatGPT is less valuable. Thus, we have to consider different avenues to automate and simplify WFM. These avenues do exist: AI is more than ChatGPT. (What if doing nothing?)
Beyond ChatGPT: Innovating Workforce Tools
Forecasting tools that do not even require the push of a button, scheduling tools that adapt themselves to agent preferences, automatic real-time management taking expected service levels into account… it exists already or will soon arrive. A combination of AI and more traditional methods makes this possible, and it might disrupt WFM just as ChatGPT is disrupting customer contact. What is needed is thinking in possibilities instead of constraints. It will bring us benefits for all stakeholders!