Forecasting and Scenario PlanningThe Challanges of Uncertainty and Complexity

Agenda

Introduction on forecasting

Introduction

Methods of forecasting depend on two variables

Uncertainty

The degree of available knowledge about the target variable

Complexity

The number of variables and the extent to which they are interrelated

Introduction

Low uncertainty / Low complexitt (LL)

Point estimates

A single number

Forecasting the demand of a known product in a stable market

Introduction

High uncertainty / Low complexity (HL)

Confidence ranges

Upper and lower boundaries

Estimate the oil reserves in a new offshore field

Introduction

Low uncertainty / High complexity (LH)

Deterministic models

Identify, measure and relate different influencing variables

Fundemental forecasting of exchange rates

Introduction

High uncertainty / High complexity (HH)

Scenario planning

Introduction

Deterministic models

Scenario planning

Point estimates

Confidence ranges

High complexity

Lowcomplexity

LowUncertainty

HighUncertainty

The Challange of Uncertainty

Definition of uncertainty

As to the correct value of an unknown quantity of interest:

disagreement among forecasters

doubts within a single forecaster

The Challange of Uncertainty

Why disagreement?

Overconfidence (marriage, business success)

Illusion of control (choose lottery number)

Information distortion (availability heuristic)

Risk perception

Assessing or weighing probabilities

The Challenge of Complexity

Definition of complexity

How many variables

How deeply they interact

The Challanges of Complexity

Cognitive simplifications

The abbility to identify all variables and combine them sufficiently

Bounded rationality

Cognitive devices (for instance schema’s and associateive networks)

The Challanges of Complexity

Dynamic complexities

Cross-sectional complexities

How variables interrelate at a given point in time

Dynamic complexity

How variables interrelate over time

Research shows that people have a difficulty learning over time => internalisation of the concept not to give up and try and try again.

The Challenges of Complexity

“We should make things as simple as possible,

but not simpler” (Albert Einstein)

Uncertainty / Complexity

LL (Point estimates)

Problems

Focus extensively on one value

Reluctant to diverge from an initial estimate

Use of heuristics and consequent bias

Improve

Extrapolating forecasting

NPV analysis

Decision analytic models

Uncertainty / Complexity

HL (Confidence ranges)

Problems

Overconfidence which makes ranges to narrow

Ignoring base rates

Ignoring sample size

Improve

Event diagrams

Fault trees

Simulation

Uncertainty / Complexity

LH (Deterministic models)

Problem

Humans simplistic notion about cause and effect

Think about everything that is said during election campaigns

Improve

Assumption analysis

Influence diagrams

Uncertainty / Complexity

HH (Scenario Planning)

Problem

Inability of human beings to deal with ambiguity

Improve

Focus on exploration and learning

Feedback loops

Posing disconferming questions

Scenario Planning

Focus on the joint effect of many factors

Helps us understand how various strands of a complex tapestry move if on or more threads are pulled

The art of scenario planning lies in blending the known and the unknown into a limited number of internally consistent views of the future than span a very wide range of possibilities.

How to develop scenarios

Define the scope and time frame

Identify the major stakeholders Overview of players, there interests and power position

Identify basic trends DESTEP

Why is it relevant

Direction of the trend (positive, neuteral, negative)

How to develop scenarios

Identify key uncertainties Aimed at issues concerning the company

Determine possible outcomes for each uncertainty

Construct initial scenario themes Identify two extreme worlds by putting all the positive

outcomes in one and all the negative outcomes in the other scenario

Or, select the two most significant uncertainties and postulate two rather extreme outcomes for each uncertainty

How to develop scenarios

Build a scenario blueprint Create a matrix that represents the identified uncertainties and plot

the scenarios you constructed

Check whether all scenarios are:

Plausible

Internally consistent

Sufficiently relevant

Develop full-fledged scenarios Identify general themes

The overall goal is to identify storylines and themes for the scenarios that cover a full range of possible outcomes for the uncertain issues at hand

Highlight competing perspective

How to develop scenarios

Identify research needs To flesh out your understanding of uncertainties and

trends, as well as perhaps their interrelationship over time

Develop influence diagrams

Develop quantitative models Simulations

Usually done with specific software

How to develop scenarios

Evolve towards decision scenarios Converge towards a limited number of distinctive different

scenarios that you will eventually use to test your strategies and generate new ideas

Windtunnel the scenarios with the business ides

Assignment / Break‘Your personal scenario’s’

Take 20 minutes to answer the following questions: Which two variables in your environment will be most

important in the way your life will develop over the next 5 – 10 years?

For both variables, determine (realistically) what the most negative an most positive outcome would be for you.

Combine the 4 outcomes => 4 possible futures

How well are you prepared for these 4 possible futures and why?

What do you possible have to do the be better prepared for these 4 possible futures?

After 20 minutes I would like to ask 3 -4 students to elaborate on their scenario’s.