Assembled Workforce Management

Overtime in Assembled is currently limited to a headcount-per-slot model tied to specific time windows. This requires managers to predefine exact hourly slots and capacities, which is restrictive for teams that want flexible, first-come-first-served overtime based on total hours available per day. Use Case Managers want to offer a fixed number of overtime hours per day (e.g., 20 hours total), allowing agents to claim any combination of hours: Example: 5 agents take 2 hours each (10 hours), 3 agents take 3 hours each (9 hours), leaving 1 hour remaining. Once the 20-hour daily cap is reached, overtime sign-ups automatically close for that day

Currently, we only can see that level of detail one agent at a time. This impacts our ability to see trends and larger picture.

Right now, the staffing timeline only supports searching for a single agent by name. It would be super helpful to have the ability to filter for multiple agents by name at once. There are many scenarios where a client team needs to focus on a specific subset of agents across different teams or groups, and the existing filters don't always allow for that level of granularity. A multi-agent name filter would streamline workflows and improve usability for team leads and workforce planners.

The various Zendesk & Chrome extensions rows on the activity timeline scorecard are really hard to parse. I understand that the extension adds another line to the scorecard, but what's the purpose? If we get Zendesk UAS, and we get Zendesk, why does adding another line matter? Wouldn't it be better if it makes the Zendesk line more accurate? The difference between the various rows in the Scorecard and the purpose of each one could be better clarified, especially in the help center articles.

I would love to be able to select agents who get these notifications versus the ones who don't maybe based on their department or based on a particular skill set because we don't schedule our BPO agents. Other teams do that and they might do schedules differently than we do.

Feature Request: Automated Schedule Approvals Based on Coverage and Policy Objective Transition our schedule change process from a manual review to an automated system that immediately approves or denies requests based on strict coverage thresholds and country-specific labor policies. Auto-Approval Criteria A schedule change should only be automatically approved if it meets all of the following conditions: The total scheduled hours perfectly align with the region's specific working hour policies. The requested change maintains adequate staffing levels without creating any coverage gaps. Auto-Denial Criteria The system must automatically deny a schedule change if any of the following occur: Coverage Gaps: The change causes scheduled headcount to drop below the required staffing levels. Overstaffing: The change schedules more staff than is required for those hours. Policy Violations: The total working hours violate country-specific compliance rules (e.g., exceeding maximum allowed hours). Incomplete Shifts: The shift duration contains unassigned or "blank" time on the calendar. Operational Standard: India (Example) Shift Duration: Engineers must be scheduled for an exact 9-hour shift. Comprehensive Scheduling: The entire 9-hour block must be completely filled with designated events. Allowed Events: The schedule must account for every minute of the shift, including productive time, Lunch, Breaks, Meetings, Trainings, and any partial Time-Off events (applicable if the time off exceeds one hour). If there are any requests to delete the schedule as they are taking week offs during weekdays as they are scheduled for weekend working, do not auto approve to deny those schedule deletion requests and keep it in the bin to manually approve.

we would like the option to start a backfill forTalkdesk without opening a ticket

Show forecast and actual totals to date, or to the hour or half hour if viewing by interval.

It would be helpful if Assembled allowed users to run “what-if” scenario forecasts to explore hypothetical volumes without affecting the current staffing plan.