6. Pattern Recognition Simulation
20th century linear production 21st century non-linear production
Metrics → Forecast Model → Forecast → Metrics → Model
Deterministic → one scenario Probabilistic → many scenarios
Limited inputs due to complexity. Complexity only limited by
computational capacity.
Output forced to fit a pattern. Output can surprise you!
7.
8.
9. I. Human sales reps have a finite capacity.
II. All distribution channels eventually saturate.
III. New hires have a ramp-up period.
IV. Time is the enemy of all deals.
V. All systems, including humans, make mistakes.
VI. Engineers build value.
VII. Marketing communications value.
VIII. Customer success delivers value.
IX. Sales captures value.
X. Drag on organization increases as it scales.
Laws (Governing Equations)
15. THE ROLE OF SIMULATION
Bringing beginners up to the knowledge level of veterans.
Running experiments before real-world trial-and-error.
Focusing us on business model definition, not forecasting.
Understanding all metrics are output of your engine.
Yielding surprise solutions we hadn’t considered: ML?
@mattwensing