Deeper Insights from System Dynamics Models

1. Deeper Insights from System Dynamics Models Mark Paich Lexidyne Consulting 10/9/08

2. Observations from (too much) experience • Decision makers are hungry for policy insights • Forecasts are not believed • Many SD models leave insight “on the table” • Modeling project time allocation – to much time modeling not enough time on analysis • Techniques for analyzing models and extracting insights are not well developed • Simple techniques can yield significant insights • Techniques are know but are not standard in SD • Techniques used in analyzing agent and discrete event models

3. Concepts that often generate useful policy insights • Synergy • Implementing policy A and policy B together produces more improvement that the sum of policy A and policy B individually • Multiple changes are necessary to achieve significant improvement • Timing – the timing and ordering of policies significantly change their effectiveness • Robustness – the policy is effective enough across many uncertainties • Value of flexibility and policy rules • Real options

4. Example – Process Improvement Project • Project description • Synergy analysis • Generate multiple simulations (design of experiments) for • Decision variables • can be discrete or continuous • Useful to categorize them into low medium , high buckets • Uncertain parameters • External scenario variables. e.g. product demand • Outcome metrics – what is important • Concluded that there are significant synergy effects. Policy changes must be implemented as a total package to get breakthrough results. Leaving elements out greatly increases the likelihood of failure

5. Example – Process Improvement Project • Export data to Excel and import into a standard statistical package • Plot relationships between policy variables and outcome metrics • Estimate simple statistical models that relate outcome metrics to policy and uncertain parameters • Direct effects • Synergy interaction effects • Analyze relationships and outlying data points

6. Extensions • Robustness • How do uncertain values change the effectiveness of policy? Are there strong interaction effects • Many other techniques for “Robust Adaptive Planning” Steve Bankes Rand Corporation • Value of flexibility – Real options and SD. (David Ford Texas AM) • Data analysis tools • Non linear estimators (neural nets) • Rule induction