A self learning algorithm that links your project characteristics (specific to a function/department - e.g. Mech Design) to how many hours were actually required from each cost tier (e.g.. Senior Designer) that month. The algorithm retains and uses that data with that month's context to discern the optimal hours for future months and new projects. The system outputs the hours you demand as HOURS per COST TIER per MONTH. It reports on its confidence level and any observed. The output can be easily understood by all stakeholders.
In the app, each function reports on characteritics that drive their project hours. These can be numerical. a selection or a True/False.
Continue the standardized forecasting/allocating process as normal. Kaizen-4™ learns in the background.
Future load from frozen forecasts aggregated across all projects.
CBR gives project leads and function heads a shared, objective starting point. Allocators define characteristics (number, selection, true/false) and values carry forward month to month, so drafts can be iterated with context—then frozen when ready. Kaizen-4™ learns the characteristic→hours relationships from historical data and proposes monthly role demand by cost tier. Side-by-side with human estimates, teams can see where differences come from and why. That removes guesswork, stabilises targets, and keeps downstream planning from chasing a moving number.
✓ Model vs Forecaster comparison and reasoning
✓ Stable targets after freeze; less re-planning churn
✓ Unbiased org-level demand view across projects
✓ Faster alignment between project leads & functions
✓ Clear separation of estimating vs allocation issues
✓ Pre-filled hours by cost tier from learned patterns
✓ Prompts drive 100% on-time submissions
✓ Fewer review loops; faster monthly close
✓ Full audit trail for every change
Budgets and monthly forecasts stop being a blank page. CBR can pre-fill proposals by cost tier using learned patterns from similar projects. Allocators only tweak the deltas when scope changes; otherwise values auto-carry forward. Global characteristics are reusable across projects, and every edit leaves a clean audit trail. The result is shorter planning windows, fewer meetings, and consistently complete submissions—without spreadsheet gymnastics.
For proposed work, enter the key characteristics and let CBR estimate hours and cost before you commit. Test scenarios by toggling characteristics (e.g., module count, platform choice) and spot scarce roles early. Combine with Capacity Strategy to check utilisation peaks, and with Forecast Variance later to track accuracy. Your commercial team gets a defendable estimate with explicit assumptions—so bid/no-bid and pricing decisions are faster and firmer.
✓ Rapid costed estimates from characteristic inputs
✓ Early view of bottleneck roles and months
✓ Clear, documented assumptions in proposals
✓ Tighter hand-off from sales to delivery
✓ Shared, reusable characteristics library
✓ Monthly history for every value (who/when changed)
✓ Consistent definitions across functions and projects
✓ Faster onboarding for new leads and allocators
✓ Model quality improves as data accumulates
As projects ship, their characteristics and actual hours become an institutional memory. CBR turns that history into an explainable model, so expertise survives role changes and growth. A Global characteristics library prevents one-off definitions, monthly history shows how scope evolved, and immutable past months keep insights trustworthy. Over time, Kaizen-4™ improves coverage and confidence—making each new estimate smarter than the last.
Algorithm and learning is isolated. No other parties benefit from your data
System works in the background. You proceed and benefit with no extra workload
System improves every month by adjusting its coefficients to the month's outcomes
Forecasts, Allocate, Track Time, Analyze Discrepanies, & Improve every Month. Streamlined Resource Management and Strategic planning All in one place.
Start training your ORG-Isolated algorithm
