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Scheduling and capacity

A self-maintaining plan for 290+ client projects.

An operations team was planning a year of client projects manually. It now runs on an engine that schedules work against real capacity.

290+client projects in the plan
200+incoming projects scheduled
0unresolved conflicts

The problem

Projects ran across several regions, workstreams and delivery stages. The plan lived in a manually maintained spreadsheet, so every holiday, absence or late booking forced manual re-planning, and conflicts surfaced too late.

The system

A scheduling engine that allocates every project against available capacity, weighing:

  • the volume and complexity of each project
  • estimated effort per delivery stage
  • staff availability, holidays and absences
  • daily capacity per team

It flags projects at risk, recommends resourcing changes, re-plans within capacity, supports approvals for exceptions and records every change in an audit trail.

Capacity plan · week 14Illustrative, not real data
Team A72%
Team B86%
Team C At risk112%
Team D58%
  • FlagTeam C over capacity after two absences are logged.
  • Re-planTwo projects moved to Team D, within both teams' capacity.
  • ApprovalException approved and recorded in the audit trail. Resolved
The shape of the weekly output: load against real capacity, conflicts flagged early, and every change approved and logged.

The result

More than 200 incoming projects were scheduled with zero unresolved conflicts. The team now manages by exception rather than rebuilding the plan.

  • Google Apps Script
  • Scheduling logic
  • Audit trail
  • Approvals

Designed and delivered by our founder while employed at a global digital-commerce analytics business. Not client work for Clarke Systems Group. Clarke Systems Group is independent and not affiliated with, or endorsed by, any current or former employer.