workplace forecast people: individual demand forecasting for better space decisions

why person-level forecasting matters

portfolio and team forecasts are necessary, but operational friction usually appears at person level.

without person-level probabilities, organizations overbook or underutilize space because they cannot separate:

• likely attendees from uncertain attendees
• planned collaboration days from focus days
• capacity needs from noise in booking behavior

workplace.forecast.attendance (people output stream) estimates individual attendance likelihood and aggregates it cleanly into team and location signals.

what workplace forecast people does

• person-level attendance probability by date
• confidence scoring for near-term and medium-term horizons
• forecasted seat and room demand contribution by person/team
• dcap and mcap normalized metrics for changing capacity baselines
• explainable features for planner review and governance

this module is designed for opt-in operational planning with policy controls and auditable decision trails.

roi model example (friction reduction)

operations assumptions:

• 5,000 employees in hybrid model
• 2 avoidable workplace support tickets per 100 employees weekly (seat conflicts, failed meeting setup, space mismatch)
• fully loaded handling cost per ticket: 18 dollars

yearly support cost from avoidable friction:

• 100 tickets/week x 18 dollars x 48 weeks = 86,400 dollars

if people-level forecasting plus better pre-allocation removes 45%:

• savings: ~38,880 dollars yearly
• plus reduced employee downtime and better schedule reliability

this is usually an entry-level gain. larger value comes from better downstream desk/room allocation and reduced overflow contingencies.

where it works best

• large hybrid programs with high booking variability
• organizations with strict neighborhood or accessibility constraints
• enterprises moving from reactive helpdesk workflows to predictive operations

ai race angle

mckinsey reports ai usage in at least one business function at 78%. person-level demand forecasting is one of the lowest-risk, highest-utility ways to operationalize that trend in workplace systems.

key kpis to track

• person-level forecast calibration
• avoidable seating/room support tickets
• same-day reallocation count
• confidence-weighted demand error
• planner override rate

sources

• McKinsey, The state of AI (2025): https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
• WFH Research, US Paid Workdays Worked From Home: https://wfhresearch.com/wp-content/uploads/2024/06/US-WFH-map-v4.html
• Kastle Systems, Back to Work Barometer End of Year Highlights: https://www.kastle.com/safety-wellness/getting-america-back-to-work/

Real-World Benchmarks (2025-2026)

• Hybrid work remains structural, with sustained remote-day share in WFH Research data.
• Microsoft reports AI-native firms are redesigning individual workflows and role-level execution.
• BLS compensation baseline used: $45.65/hour.

Monetized ROI Assessment (USD, 2026)

Conservative person-level planning case:

• Execution time recovered: 1,200 hybrid employees x 0.5 hours/week x 48 weeks = 28,800 hours/year.
• Labor value: 28,800 x $45.65/hour = $1,314,720/year.
• Escalation and support reduction: $140,000/year modeled operational savings.
• Total modeled annual value: $1,454,720.

Buyer story: fewer frictions per person, better execution velocity per team, measurable operating return.

Benchmark Sources

• WFH Research, US Paid Workdays Worked From Home: https://wfhresearch.com/wp-content/uploads/2024/06/US-WFH-map-v4.html
• Microsoft, 2025 Work Trend Index: https://www.microsoft.com/en-us/worklab/work-trend-index/the-year-the-frontier-firm-is-born
• U.S. Bureau of Labor Statistics, Employer Costs for Employee Compensation - June 2025: https://www.bls.gov/news.release/ecec.nr0.htm