Performa — Performance Gamification Platform

The Operationalization Problem

AI Doesn't Change Behavior.
People Do.

Every AI implementation eventually hits the same wall. The algorithms work. The recommendations are sound. But nothing changes on the plant floor. Here's why — and what Performa does about it.

Invisible Performance

When operators can't see how they're performing relative to their peers and their own history, there's no feedback loop. People optimize for what they can measure. If individual performance is invisible, it doesn't improve.

No Skin in the Game

Recommendations that don't connect to personal accountability get ignored. A dashboard that shows "plant is running suboptimally" gives the operator no reason to do anything differently. Performa makes it personal.

Shift Change Amnesia

Knowledge doesn't transfer between shifts. The day crew knows what happened; the night crew starts fresh. Performa tracks performance continuously and surfaces the handover context automatically — no briefing required.

The Research Case

Why Gamification Works —
And What Our Data Shows

Performa's design is grounded in published engagement research and validated by our own deployment results across multiple coal preparation plants at a major US producer.

External Research

31%

of USA & Canada employees are actively engaged at work — the baseline problem Performa is designed to address

Gallup State of the Global Workplace: 2025 Report — the most widely cited benchmark for workforce engagement globally

6×

more engagement and performance improvement when frequent feedback replaces annual or periodic review cycles

Gallup — Re-Engineering Performance Management — based on longitudinal workplace performance data

Hard-wired

Millennials and Gen Z — now the majority of the mining workforce — expect engaging, feedback-rich work experiences as a baseline

Cross-generational gaming research (Udonis/Medium) — nearly all workers under 45 have grown up with game mechanics as a primary engagement model

4 Pillars

Feedback loops, team competition, peer affirmation, and micro-awards — the four game design elements that translate directly to process performance improvement

Applied game design framework — Performa implements all four: shift scorecards (feedback), crew leagues (team), foreman coaching (affirmation), milestone badges (micro-awards)

Our Results

In early 2025, we deployed scorecards across most sites at a major US coal producer. One mine served as an unintentional control — it maintained existing processes without active scorecard use. The results were clear.

30%

overall score improvement at sites actively using scorecards vs. stagnant performance at the control mine — a statistically significant difference across weekly averages

Internal deployment data — post-scorecard rollout, early 2025, multiple coal preparation plants at a major US producer.

Top Sites

The most active sites — both with direct operator and foreman-level daily coaching — showed the strongest and most consistent gains

Correlation between coaching engagement frequency and scorecard improvement rate across sites

Control

The control mine, which did not actively participate in the scorecard process, showed flat performance over the same period

Confirms that improvement was driven by the scorecard system — not external factors like coal quality or market conditions

"Sites that actively participated in the scorecard process performed consistently better — an overall score improvement of 30% versus stagnant performance at the control mine."

Dr. Data Mining internal deployment analysis — major US coal producer, 2025

Platform Features

How Performa Works

🏆

Operator Scorecards

Per-operator, per-shift performance scores built from actual process behavior — not supervisor opinion. Scores are calculated from TSAI analytics: SG control quality, magnetite usage efficiency, response time to anomalies, throughput contribution. Every operator sees their own score in real time.

📊

Team Rankings & Leagues

Shift vs shift. Crew vs crew. Circuit vs circuit. Competitive structures that tap into the natural motivation of people who take pride in their work. Rankings are visible on the plant floor display — not hidden in a management dashboard. Visibility drives behavior.

🎯

Goal Tracking

Daily, weekly, and monthly targets tied directly to throughput, yield, quality, and cost KPIs. Goals are set at the site level and cascade to shift and individual targets. Progress is visible throughout the shift — not just at the end.

🏅

Achievement System

Milestones and recognition for sustained performance improvement. An operator who achieves best SG control for three consecutive shifts gets recognized — automatically, without supervisor involvement. Recognition that happens at the moment of achievement, not at the annual review.

🖥

Management Dashboard

Site-wide view across all shifts and circuits. Supervisors see aggregate performance trends, individual operator histories, goal attainment rates, and which shifts consistently outperform. Drill down from site to shift to individual with a single click.

📋

LLM Coaching

Personalized recommendations generated by AI from each operator's profiling data. "Your SG control is in the top quartile but your magnetite usage is 18% above average — here's the specific pattern we're seeing." Coaching that's specific, timely, and actionable.

Integration

Built to Work With
What You Already Have

TSAI Integration

Performa scores are calculated directly from TSAI analytics. When TSAI detects an SG drift event, unnecessary magnetite addition, or suboptimal feeder configuration, that feeds directly into the relevant operator's scorecard. The performance system is grounded in real process data — not manual observation or supervisor judgment.

Excel Add-In

All Performa configuration — operator records, KPI targets, scoring rules, league structures, achievement criteria — is managed through a C# Excel-DNA add-in. Bulk load, update, and delete across all configuration tables. Role-based access control built in. Data administrators work in the tool they already know.