Workforce Management - Incorporate Zendesk SLA Rules into Forecast

Please give a quick overview of your product feature request or feedback and note who in your org is affected by this issue [ex. agents, admins, customers, etc.]. (2-3 sentences)

In Workforce Management, the forecasting functionality only allows for a single First Reply Time variable. First Reply time can vary based on the urgency of the ticket, so a global first reply time can make it challenging to forecast for surges of High or Urgent priority tickets. 

What problem do you see this solving? (1-2 sentences) 

First reply time varies based on ticket priority and SLA policy. By incorporating actual SLA data, we would be presented with a more accurate forecast. With a large focus on efficiency across the industry, this would be a major improvement. 

When was the last time you were affected by this lack of functionality, or specific tool? What happened? How often does this problem occur and how does this impact your business? (3-4 sentences)

Monthly, when reviewing forecasting data. For example, our team is 24/7, but only High and Urgent priority tickets are addressed after 5pm ET. Workforce Management has no way of knowing this and thus forecasts that our after hours team should be 5x the size it currently is, but then also forecasts that we are drastically overstaffed at 8am when, in reality, the folks working at 8am are working on Normal and Low priority tickets from the prior evening that are still well within SLA. 

Are you currently using a workaround to solve this problem? (If yes, please explain) (1-2 sentences)

Intuition and "eyeballing" the forecast to see if it looks okay overall. 

What would be your ideal solution to this problem? How would it work or function? (1-2 sentences)

Rather than allowing for a first reply time parameter, it would be great to see the forecast engine use the SLAs configured within Zendesk and forecast based on historical ticket volume and historical SLA assignment. By default, the forecasting engine would show you the minimum staffing to meet SLA. You could then add parameters for meeting the SLA, such as target achievement percentage or how much of the SLA has passed. For example, being able to configure the forecasting engine to staff an agent when the SLA target is 75% of the way to being breached.