Scenario Construction Via Cross Impact

1. The Network Nation and Beyond A Festschrift in Honor of Starr Roxanne Hiltz and Murray Turoff Scenario Construction Via Cross Impact Prof. Victor A. Bañuls Management Department Pablo de Olavide University Seville, Spain Email: vabansil@upo.es Web: http://webdee.upo.es/vabansil Distinguished Prof. Murray Turoff Information Systems Department New Jersey Institute of Technology Newark NJ, USA Email: turoff@njit.edu Web: http://web.njit.edu/~turoff/ NJIT – October 2007

2. Index • Research motivations • Methodological background • Basics of the CIM-ISM • Generating scenarios • Conclusions

3. Research motivations • Why do we need scenarios? • Strategic decision making (policy, business, etc.) compromise resources in the long term. • We need to think about what will happen tomorrow before acting today. • A scenario is a tool for managing the uncertainty of the future. • Our proposal is aimed at contributing to this goal.

4. Research motivations • What is the aim of our proposal? • Helping decision makers to manage the uncertainty. • How? • Structuring and sharing the beliefs and the knowledge of the people involved in decision making. • But… how can we do that? • By the structural analysis of the impacts between the atomic events that are relevant to the decision-making problem.

5. Methodological background • Cross-Impact Method • Events cannot be analyzed in a isolated way. • Alternative cross-impact approach (Turoff, 1972): Inferring impacts between events based on experts’ hypothesis about their occurrence (or not).

6. Methodological background +/- Impacts between events in the model C43 Cross-Impact Matrix Impacts of the events not included in the model

7. Methodological background • Interpretive structural modeling • Taking as an input the impacts obtained with the CIM, this methodology will help us to: • Making hypotheses about the occurrence or not of the set of events and analyzed them (to generate scenarios). • Detecting and analyzing the key drivers (critical events).

8. 8 9 10 2 7 3 6 5 1 4 Methodological background Scenario Occurring events Non-Occurring events Key drivers

9. Methodological background Ei Events Input Pi Sij Rij Set of probabilities (isolated and conditional) CIM Cross-Impact Method Cij Gi Cross-Impact Matrix Output

10. Methodological background Ei Events Pi Sij Rij Set of probabilities (isolated and conditional) CIM Cross-Impact Method Cij Gi Cross-Impact Matrix Input ISM Interpretive Structural modeling Scenarios Output

11. Basics of the CIM-ISM • Starting point • Cross-Impact Matrix (Turoff 1972 paper example).

12. Basics of the CIM-ISM Cross-Impact Matrix

13. Basics of the CIM-ISM • Starting point • Cross-Impact Matrix (Turoff 1972 paper example). • Transforming the Cross-Impact matrix • Transition Matrix (square and positive matrix).

14. Basics of the CIM-ISM Transforming the Cross-Impact Matrix

15. Basics of the CIM-ISM • Starting point • Cross-Impact Matrix (Turoff 1972 paper example). • Transforming the Cross-Impact matrix • Transition Matrix (square and positive matrix). • Transforming the Transition Matrix • Adjacency Matrix (taking an arbitrary Cij value (0.85)).

16. Basics of the CIM-ISM • Starting point • Cross-Impact Matrix (Turoff 1972 paper example). • Transforming the Cross-Impact matrix • Transition Matrix (square and positive matrix). • Transforming the Transition Matrix • Adjacency Matrix (taking an arbitrary Cij value (0.85)). • Connection Matrix (adding the Identity Matrix).

17. Basics of the CIM-ISM • Starting point • Cross-Impact Matrix (Turoff 1972 paper example). • Transforming the Cross-Impact matrix • Transition Matrix (square and positive matrix). • Transforming the Transition Matrix • Adjacency Matrix (taking an arbitrary Cij value (0.85)). • Connection Matrix (adding the Identity Matrix). • Reachability Matrix (powering until it is stable).

18. Basics of the CIM-ISM • Scenario Generation • Determining antecedent and succedent sets • Obtaining the graphical scenario (using graph theory)

19. Basics of the CIM-ISM • Scenario Generation • Determining antecedent and succedent sets. • Obtaining the graphical scenario (using graph theory). • Interpretation of the scenario • Analyzing key drivers. • Analyzing the set of probabilities.

20. LEVEL 1 1 6 4 LEVEL 2 8 5 LEVEL 3 2 7 LEVEL 4 10 LEVEL 5 9 Basics of the CIM-ISM Occurring events Non-Occurring events Scenario Why 0.85? And event 3? P9=0.1 Key drivers

21. Generating scenarios • Sensitivity Analysis • Studying the Cij distribution.

22. Generating scenarios Normal distribution with a reliability of 99% (using K-S test)

23. LEVEL 1 6 10 4 LEVEL 2 1 LEVEL 3 8 9 Generating scenarios

24. LEVEL 1 4 6 5 2 LEVEL 2 1 10 7 LEVEL 3 8 LEVEL 4 9 Generating scenarios

25. LEVEL 1 1 6 4 LEVEL 2 8 5 LEVEL 3 2 7 LEVEL 4 10 LEVEL 5 9 Generating scenarios

26. LEVEL 1 6 1 4 LEVEL 2 5 7 8 2 10 LEVEL 3 9 3 Generating scenarios

27. Generating scenarios • Sensitivity Analysis • Studying the Cij distribution • Solving the forecasted scenario • Determining the limit of the forecasted scenario

28. LEVEL 1 6 4 1 2 5 7 10 LEVEL 2 3 8 9 Generating scenarios Forecasted Scenario Limit = |0.4975|

29. Generating scenarios Cross-Impact Matrix for the Forecasted Scenario

30. Generating scenarios • Sensitivity Analysis • Studying the Cij distribution. • Solving the forecasted scenario • Determining the limit of the forecasted scenario. • Solving the alternative scenarios • Determining the limit of the alternative scenarios.

31. Generating scenarios • Sensitivity Analysis • Studying the Cij distribution. • Solving the forecasted scenario • Determining the limit of the forecasted scenario. • Solving the alternative scenarios • Determining the limit of the alternative scenarios. • Interpretation of results • Analyzing the information included in each scenario.

32. Generating scenarios

33. Generating scenarios

34. Generating scenarios

35. Generating scenarios

36. Conclusions • Aims of the model • Handle complex systems. • Obtain a set of plausible snapshots of the future. • Analyze interaction between events. • Detect critical events. • Application areas • Technology Foresight. • Strategic Management. • Policy Analysis. • Emergency Response. • Etc…

37. Conclusions • Strong points • A strong theoretical background of the techniques on which the authors proposal in based. • The possibility of working with large sets of events. • Tools for analyzing the key drivers of the scenarios. • Specific software is not needed for making the calculations. • A graphic output that gives a clear representation about the forecast. • It is strongly compatible with other techniques such as the Delphi or multicriteria methods.

38. Conclusions • Limitations • We cannot kwon the probability of occurrence of a specific scenario if it is not an output of the model. • The estimation of the occurrence or non-occurrence estimation of the scenarios needs the interpretation of the key drivers and sometimes it would be difficult if there is a probability of occurrence close to 0.5.

39. Thank you for your attention! Scenario Construction Via Cross Impact Prof. Victor A. Bañuls Management Department Pablo de Olavide University Seville, Spain Email: vabansil@upo.es Web: http://webdee.upo.es/vabansil Distinguished Prof. Murray Turoff Information Systems Department New Jersey Institute of Technology Newark NJ, USA Email: turoff@njit.edu Web: http://web.njit.edu/~turoff/