5) Other scenario planning schools

Question 1

Michael Porter

Answer 1

‘Macro-scenarios, despite their relevance, are too general to be sufficient for developing strategy in a particular industry’

-> the five competitive forces that determine industry profitability

Question 2

Industry scenarios

Answer 2

• encourage managers to make their implicit assumptions about the future explicit
  
  • think beyond the confines of existing conventional wisdom
• allow a firm to translate uncertainty into its strategic implications for a particular industry
• time period should reflect time horizon of the most important investment decisions

What distinguishes industry scenarios?

• each scenarion = full analysis of industry structure (competitor behavior, and the source of competitive advantage under a particular set of assumptions)
• merely a framework to identify the key uncertainties and analysing them (not end)

Question 3

The Probalistic Modified Trends School

Answer 3

Two distinct methodologies:

Trend-impact analysis (TIA)

Cross-impact analysis (CIA)

• TIA and CIA began as essentially standalone probabilistic forecasting tools
• generate a range of alternative futures rather than a single point naive extrapolation of historical data
• combined with judgements and narratives -> constitute scenarios

Question 4

TIA: Trend-Impact Analysis

Answer 4

• quantitive methods based on historical data to produce forecasts extrapolating data into the future but ignore the effects of unprecedented future events
• simple approach to forecasting: time series is modified to take perceptions on how future events may change extrapolations into account

Steps

1. collect historical data relating to the issue
2. surprise-free extrapolation (curve-fitting)
3. develop a list of unprecedented future events
   
   • can cause deviation from extrapolated trend
   • plausbile
   • potentially powerful
   • verifiable in retrospect
4. make judgements about each selected event
   
   • estimate probability of occurrence as function of time
   • estimate impact on trend
   • expect judgements on time and impact to produce adjusted extrapolations

Question 5

CIA: Cross-Impact Analysis

Answer 5

Derived from question: can forecasting be based on perceptions about how future events may interact?

• analytical approach to probabilitoes of an item in a forecasted set
• cross-impact questions can help illuminate hidden causalities and feedback loops in pathways to future

Steps

1. define the events to be included in study (10-40)
   
   • literature search, interview key experts
   • initials set + clustering, excluding, refining
2. estimate the initial probability of each event
3. estimate the conditional probabilities: ‘If m occurs, what is the new probability of event n?’ -> cross-impact matrix ready for sensitivity testing or policy analysis

Question 6

La prospective and morphological analysis

Answer 6

exploring all the possible solutions to a multi-dimensional and non-quantifiable problem

• eliminates incompatible combinations of factors and creates plausible combinations of the key variables
• we can see various elements and dimensions in the system and develop raw scenarios for the future

Scenario development

• decompose the system into components, each with a number of possible configurations
  
  • components must be the most independent possible and cover all of the studied system
• there are as many possible solutions as combinations of configurations
• a ‘path’ that associates one configuration for each component constitues the backbone of a possible scenario

COMBINATORY - EXCLUSION - REPRESENTATIVENESS

Question 7

Morphological analysis - how does it work?

Answer 7

1. Morphological field - with all scenarios
2. Exclusion constraints -> reduced morhological field
   
   • configurations and possible evolutions of the different drivers must be compatible - incompatibilities must be excluded
3. Morphol calculations -> list of closest scenarios
   
   • CT - sum of common hypotheses with the rest of the scenario group (the sum of the number if configurations that the considered scenario has in common with other scenarios)
   • CM - number of scenarios with which considered scenario differs in only one configuration
   • CX - number of times the considered scenario is completely different from the other scenarios
   • List of closest scenarios
4. List of closest scenarios -> selected scenarios
   
   • ​​Selection methods:
     
     • tools of the morphol software (selection of representative scenarios) (proximities map)
     • adaption of the ‘extreme-world method’

Question 8

Extreme world method

Answer 8

• results in two-extreme scenarios
• go beyond the normal optimistic-pessimistic by allowing planners to better and more fully explore the effects of extreme event interactions when there is high degree of uncertainty
• third scenario can be detailed: extrapolation of the present -> often called ‘status quo’ scenario

Steps

1. identify issue of concern and horizon year
2. identify predetermined trends that have come degree of impact
3. identify critical uncertainties
4. identify the degree to which the trends and resolved uncertainties have a negative or positive impact
5. create extreme worlds by putting all negative and all positive resolved uncertainties together
6. add predetermined elements
7. check for internal coherence
8. add actions

Question 9

Backcasting

Answer 9

Backcasting gives you a chance to look through the front shield seeing clearly the road ahead, as well as the tools to imagine the best possible destination where you could arrive and thrive

• relation between scenario and backcast
• desired endpoint is chosen (e.g., for 2050) and strategies are developed to achieve the endpoint
• strategies need to be effective in the context of one of the four scenarios by working backwards from 2050 to present
• done for each scenario, thus creating backcasts