Measuring agility: Data analytics ex psychology to grow your teams agility
summary
Ten years of longitudinal data from 30 organizations and 500+ teams feed a behavioral model that explains 85% of variance in business agility using expert observation, PCA, ANOVA and inter‑rater reliability; four behaviors drive outcomes with self‑organization = 50%, agile values ~10%, sprinting ~10% and continuous learning ~5%. An 85‑question baseline (then 15‑question pulses) powers an AgileIQ app that forecasts defects, overtime and cost impact — mature teams (IQ ~160–180 on a 1–200 scale) hit near‑zero defects and the model projects it saves $40–50k/month per 10‑person team.
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chapters (8)
- 0:00Start
- 3:53METRICS TO MAKE AGILE REPEATABLE
- 7:18STATISTICAL MODELLING TO COMPARE BEHAVIOURS WITH OUTCOMES
- 11:44RESULTS / PREDICTIVE ANALYTICS
- 17:20PREDICTS ORGANISATIONAL RESILIENCE
- 24:16COMPARE STRENGTH OF TEAM BEHAVIOURS NOT VELOCITY
- 26:00IMPLICATIONS FOR EXECUTIVES AND LEADERS
- 29:15FOR LEADERS
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