This is really cool! I'm working with a customer support team and getting the right amount of staffing was always a challenge. To really reliably have good support with low wait times for 95% of the time, you'd end up being overstaffed by quite a bit for >50% of the time.
In addition, just communicating with everyone about shifts and managing the people-side was also a challenge, and there never felt to be super-specialized tools for this.
Accurate staffing seems like precisely the kind of problem that good data and modeling could solve. Good communication is something that good UI design could solve too. I'm excited to see how this works!
These are definitely the kinds of problems we're trying to solve. We've been working with our launch customers to get their whole company to understand the tradeoffs involved in customer support.
It's actually very hard to have both fast response times and high occupancy (the percentage of your team's time actually spent answering tickets). Often a company wants both, but it's hard to convince people that you can't have both. We've helped our early customers show this by actually planning different scenarios out.
In addition, just communicating with everyone about shifts and managing the people-side was also a challenge, and there never felt to be super-specialized tools for this.
Accurate staffing seems like precisely the kind of problem that good data and modeling could solve. Good communication is something that good UI design could solve too. I'm excited to see how this works!