Strategic Decision Making: A Systems Dynamic Model of a Bulgarian Firm

1. Strategic Decision Making: A Systems Dynamic Model of a Bulgarian Firm David L. Olson, University of Nebraska Madeline Johnson, Univ. of Houston-Downtown Margaret F. Shipley, Univ. of Houston-Downtown Nikola Yankov, Tsenov Academy of Economics

2. Transition Economies • Transition from centrally-planned to market economies • Face ambiguous information and cues • Challenge existing ownership & operating principles • Firms responsible for strategic decisions

3. Joint Effort • University of Houston-Downtown • NSF Grant – Joint International Workshop on the Use of Information Technologies in Modeling the Bulgarian Firm in Transition from a Planned to a Free Market Economy • Tsenov Academy of Economics • Svishtov, Bulgaria

4. Subjective System Dynamics Model • Winery • Tool to simulate impact of key strategic decisions: • Market selection (local, national, international) • Promotion & pricing • Product quality decisions • Capacity (vineyards and bottling) • Distribution

5. Open Systems Theory • Ludwig von Bertalanffy • An organization exists in relation to its environment • There is a continuous flow of energy & information • System features: • Self-organization - progressive differentiation • Equifinality – initial condition doesn’t matter • Teleology – systems are purpose-driven

6. Cybernetics • Stafford Beer • Cybernetic systems are complex, probabilistic, self-regulatory, purposive, have feedback and control • Operations research only works when you consider the whole • Viable System Model – organization regulated, learns, adapts, evolves, or doesn’t survive

7. Mental Models • Systems consist of interacting parts working toward some end, feedback control • Purposive • Synergistic • Complex • Feedback

8. System Dynamics • Jay Forrester • Developed technique for deterministic simulation of systems • Identify influences • Estimate effects • Develop feedback model

9. Forrester’s World Dynamics Model • Sectors • Population • Natural Resources • Capital Investment • Pollution • Metrics • Quality of life • Material standard of living • Ratios for FOOD, CROWDING, POLLUTION

12. Soft Systems TheoryPeter Checkland • Interpretive action research • Model interacting system • Define problem done • Express situation done • Root definition • Conceptual model done – simulation model • Compare model/real world • Use model to determine improved methods • Action

13. Simulation Approaches • DYNAMO/Ithink/Stella/PowerSim • VENSIM • Commercial implementation of system dynamics • Support conceptual modeling • EXCEL • Probabilistic simulation over time • CRYSTAL BALL • Probabilistic simulation output

14. Development of Model • Symposium in Svishtov, Bulgaria • May 2002 • About 20 from U.S., 20 from Svishtov • Selected winery because of knowledge of Tsenov Academy faculty • Selected system dynamics because: • Problem involved subjective data • Complex interactions among decisions, time

15. Winery Model • Time frame: 6 years • Show impact of strategic decisions • Inputs: • Promotion • Pricing • Quality (grow or purchase grapes) • Market selection (local, national, international) • Outputs • Profit • Cash flow • Market share by product (3 levels of quality)

16. Promotion • Lagged over three month • Impact differentials • 0.5 prior month • 0.35 two months prior • 0.15 three months prior • Media: firm representatives interacting with distributors • Management could constrain local, national, or export markets to emphasize others • Demands in each market probabilistic

17. Quality • If winery controls vineyard, quality higher • Constrained by amount of hectares in vines • Three years between planting, use • Use own grapes as much as possible • Any extra production capacity used for purchased grapes (lower quality bottles)

18. System Variables • Exogenous: • System Variables: • Control Inputs:

19. Exogenous Variables • Demand (normally distributed, change per month) • By market (local, national, export) • By product (correlated) • Seasonal • Market Price (normally distributed, change per month) • Independent of firm decisions • Competitor promotion (normally distributed by market) • Market share possibilities • Prior market share multiplied by ratio of prior promotion to base promotion, divided by that of competitors • Crop yield

20. Control Inputs • Price • By product by month • Promotion • By product by month • Plant Capacity • Depreciation, plus construction • Labor • Permanent (higher quality) vs. temporary

21. System Variables • Sales • By market, by product • Inventory • High, low quality • Bank Balance • 5% gain on positive balance, 15% cost on negative

22. Results • Varied prices, promotion levels • Price: base, cut 10%, increase 20% • Promotion: base, emphasize local, emphasize export • Measured • bank balance after 6 years • Probability of losing initial capital (going broke) • Probability of breaking even • Market share (low, high quality)

23. Base Run

24. Base Model • 1000 replications • Crystal Ball software • Cyclical demand for high quality • Base case has National focus • Without pricing & promotion, loss

25. End Bank Balance

26. Bank Balance • Mean 117,458 Lev • Probability of losing bankroll: 0.0 • Probability of losing money: 0.0 • Most optimistic: • Worst: loss:

27. Market Share - National

28. Mixed Price, Promotion

29. National Market Share – Mixed policies

30. Model Validation • Initial visit May 2002 • 3 day workshop to build model • Built model summer 2002 • Followup visit October 2003 • Went over model in detail • Refined model structure • Identified detailed data needs

31. Conclusions • System dynamics useful to model subjective input, complex interactions in temporal environment • Need for validation