Institut für
betriebswirtschaftliches
Management im Fachbereich
Chemie und Pharmazie
Technology Forecasting
Marius Chofor Asaba
Marius Chofor Asaba I
Expected Knowledge Stack
Technology Management
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What is technology Forecasting (TF)?
What importance does TF have in Technlology Management?
What methods can I use for forecasting?
When is it best to use TF?
What are the strengths and weaknesses of TF?
Marius Chofor Asaba I
Agenda
2
1 Introduction
2 Methods
3 Case Study on Delphi
Anticipation of industry convergence
Marius Chofor Asaba I
Introduction: How Tech Forecast defined?
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• Forecast: a probabilistic statement, highly confident about the future
• TF: probabilistic assessment, on a high confidence level of future technology transfer
• Provides information about the direction and rate of technological changes
• Note: it does not predict the precise for technology will take in respect to a future
date
Marius Chofor Asaba I
Introduction: Why is Tech Forecasting Important?
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It uses logical processes to generate explicit information to help industry and
government anticipate practical, ecological, political and socual consequences of
developments in technology
Marius Chofor Asaba I
Introduction: Why is Tech Forecasting needed?
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• To orient future R&D
• To prevent the import of obsolete technologies
• To anticipate technical innovation
• To assist the shift towards appropriate technology
• For effective technology transfer and Development of exportable technologies
• Rapidity of innovations and to avoid surprises
Marius Chofor Asaba I
Introduction: Elements of forecasting
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A time horizon
A specific technology (Qualitative)
Some parameters to the technology (Quantitative)
A probability statement about the outcome
Marius Chofor Asaba I
Introduction: Elements of forecasting
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Time:
Resource-time relationship
Qualitative:
Identification of factors likely to
change the activities/tech trends in
areas of interest
Quantitative:
Measurement and Assessement of
level of performance of various
technologies
Propability of occurence:
Prediction of different alternatives
and their level of confidence
Marius Chofor Asaba I
Introduction: TF Background
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After WW2 there was technological explosion in growth
Following the radical growth in technological development, competition became intense
and unpredictable
US space and defence industries implemented TF in the 1940s and 50s
The US used TF as a tool to keep its technology ahead of the Russians during the Cold War
Technology change -> modification of government policy | loss of market share | loss of a
market
Marius Chofor Asaba I
Introduction: Strategic Rationale and Implications
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The products a firm markets, the processes a firm uses or the equipment it use may be
superseded (outdated)
Competitors have an advantage
Can gain a price advantage over competitors by investing in more efficient technological
processes
Internal functioning of a business relies on technology
Technological forecasting predicts the future developments by anticipating the probable
characteristics and timing of technology
Marius Chofor Asaba I
Introduction: What can be predicted?!?
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Misconception: technology is a quite specific physical entity | it has no variable
characteristics dependent on probability statements
Meaning precise technologies will exist in a specific given situation only
Truth: Technology is not am immutable piece of hardware or a bit of chemistry | It is simply
„knowledge of physical relationships“
It can range from initial basic ideas of how to apply a solution to a practical problem up to
an end product, device, or production machine
Basically any technology has a wide and relatively continuos range of characteristics in
various applications over a give time period
Marius Chofor Asaba I
Introduction: What can be predicted?!?
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Marius Chofor Asaba I
Introduction: What can be predicted?!?
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Marius Chofor Asaba I
Agenda
13
1 Introduction
2 Methods
3 Case Study on Delphi
Anticipation of industry convergence
Marius Chofor Asaba I
TF methods
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Exploratory forecasting:
Delphi method
Analytic method
Multivariante analysis
Trend extrapolation
Growth models
Brainstorming
Scenario writing
Substitution analysis
Input-output models
Monitoring
Normative forecasting:
Operations research models
Network techniques
Cross-impact analysis
Relevance trees
SEER
Morphological analysis
Dynamic modeling
Marius Chofor Asaba I
TF methods
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Qualitative methods:
- Are subjective, based on the
opinion and judgement of
consumers/experts
- They are appropriate when past
data are not available.
- They are usually applied to
intermediate- or long-range
decisions
- e.g. Delphi, market research
Quantitative methodes:
- Used to forecast future data as
a function of past data
- Appropriate to use when past
numerical data is available and
when it is reasonable to assume
that some of the patterns in the
data are expected to continue
into the future.
- These methods are usually
applied to short- or
intermediate-range decisions
- E.g. poisson process model-
based
Marius Chofor Asaba I
TF methods: Exporatory methods
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Starts with the present state of technology and quantitatively projects future possibilities
Provides a means for exploring the shape of tomorrow given the state, trends, and
promises of today
Applicable in systems which grow under a specific environment
Methods
Intuitive Extrapolative Growth curvesTechnological
monitoring
Technological
monitoring
Marius Chofor Asaba I
Based on the ability of one or more experts to assess the future
TF methods: Exporatory methods
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Intuitive methods
• Individual forecasting: experts in specific fields prepare forecasts in their field
Lacks multidisciplinary interaction and is often biased (High probability to failure)
• Opinion polls: opinions are gotten from several individuals and combined
Minority opinion is drowned by majority opinion irrespective of significance
• Panels: Group of experts interact across a table (multidiciplinary advantage)
Extreme views are eliminated | Dominance influence | Stuborness | Hierachical fear
• Brainstorming: Frank and free unconventional alternative search technique (mostly
used in situations where unconventional alternatives are needed)
• Scenario writing: creative method of deriving possible composite scenario
Marius Chofor Asaba I
DELPHI Method: Expert opinion
TF methods: Exporatory methods
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Intuitive methods
• The delphi is a group process technique for eliciting, collating and generally directing
expert judgment towards a consensus on a particular topic.
• If the general questions are asked then the panel should have representatives from a
variety of disciplines
• Experts are expected to have specific experience
• A facilitator is needed to co-ordinate the process and send a questionnaire or survey
to each of the experts (anonymously)
• Facilitator collects and combines responses, and clarifies any issues leading towards
finding a consensus
Marius Chofor Asaba I
• HOW?
- Consider change over a period of time
- Understand the factors that have driven that change
- Predict the future change from this knowledge
• Generally statistics are plotted onto a graph against time
• Limit analysis may be used to check the utility of a trend extrpolation plot
• May be used to forecast future technology that has a precursor technology with a
known path of change
• The shape of the curve for the presursor is used as a guide
• May also predict future ones on the basis of judment
TF methods: Exporatory methods
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Extrapolative
methods
Extrapolative
methods
Marius Chofor Asaba I
TF methods: Exporatory methods
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Extrapolative
methods
Extrapolative
methods
Marius Chofor Asaba I
„S“ shaped fashion curves with a finite limit showing technology capabilities growth
TF methods: Exporatory methods
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Growth Curves
Can be used to assess future profitability of a product
Most commonly used models of growth curves:
• Pearl curve
• Gompertz Curve
• Fisher-pry curve
Inflection
point
Upper limit of sales
Marius Chofor Asaba I
Example of future estimation using Pearl curve
TF methods: Exporatory methods
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Growth Curves
Marius Chofor Asaba I
TF methods: Exporatory methods
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Technological
monitoring
Technological
monitoring
• Monitoring of technological growth through the early signals of innovation
• Achieved by searching patents, radical alternatives and literature for the embryo of
new technology
• Software programs are available which facilitate this process
Multivariante analysis: Used in cases where the cause and effect of a relationship is not
obvious
- Dependent variable and the independent variable are analyzed
- Results gotten can be used in forecasting
Marius Chofor Asaba I
TF methods: Normative methods
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Begin with an objective/goal and work backwards to the present to find the best approach
to realize the predetermined objective
Need-based: needed capabilities are identified for the achievement of the goals
Methods
Network
techniques
Network
techniquesSEER
Cross-impact
analysis
Cross-impact
analysis
Morphological
analysis
Morphological
analysis
Relevance
trees
Relevance
trees
Dynamic
modeling
Dynamic
modeling
Some methods are simple variants of techniques used in other areas and are mainly used
to eliminate subjective errors associated with intuitive forecasting techniques.
Marius Chofor Asaba I
TF methods: Normative methods
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• This is a method for structured thinking identifying all possible system alternatives
• The main idea is not to miss any options
• HOW?
- Starts with a goal you wish to achieve
- Gather information about technologies that may achieve a particular purpose
- List attributes you seek
- Display information in graphical form which highlights any gaps (gaps may represent
opportunities for developments)
• To make this process work, all possibilities must be considered
• Time and patience is required
Morphological
analysis
Morphological
analysis
Marius Chofor Asaba I
TF methods: Normative methods
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• Used to evaluated multiple choices where a number of steps may be available to
achieve a certain goal
Steps may be different in effectiveness in terms of cost, profit or probability of success
• Detailed hierarchies of methods for achieving a particular outcome
• This outcome is the question to answer a specific forecast
• It divides a broad subject/problem into increasingly smaller and more detailed
subjects
• Ideally there should be no overlap between items in the tree
Relevance
Trees
Relevance
Trees
Marius Chofor Asaba I
TF methods: Normative methods
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• Example for Pollution control
Relevance
Trees
Relevance
Trees
Develop
alternatives
to internal
combustion
engines
Develop
Petroleum
Tech. to
eliminate
pollution
causing
constituents
Develop external
combustion systems
Develop Batteries
Develop sulphur
removal process
Hybrid Car
Performance
Alternatives
Air
Pollution
control
Level 1
General
Objective
Level 2
Broad
Alternative
Methods
Level 3
Process &
Methods
Level 4
Performance
& cost
Level 5
Applied research
alternatives
Marius Chofor Asaba I
TF methods: Normative methods
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• Network techniques: Used for mission-orriented planning exercises, mainly to
analyse road blocks to achieve final target of objective (SOON: Sequence of
oportunities and negatives)
• System for Event Evaluation and Review (SEER): Modified variance of DELPHI, ideal
for corporate exercises | consist of a single round evaluation of events
• Cross-impact analysis: Different events interact with different strengths towards
other course of events | Interactions and random numbers are used to derive
combined forecast
• Dynamic modeling: computer aided structural modeling with time varying effects
Others
Marius Chofor Asaba I
TF methods: Strengths and Advantages
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• Can inform current and future investment decisions throughout a business
• Provides Flexible process that can be tailored to a business
• Makes a variety of methods available to a firm
• Individual methods all have their own particular strengths:
- Delphi: Allows a firm to tap into the expertise of experts across a range of fields
- Trend extrapolation: uses statistical data to assist in the development of indicators
- Growth curves: usefully predict when a technology has reached maturity
- Relevance trees: identify the relationships between parts of a tech/process and its
potential development
- Monitoring: of patents and general research trends can give a firm warning of new
inventions
Marius Chofor Asaba I
TF methods: Weaknesses and Limitations
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• TF is heavily dependent on the quality of the information and the validity of the
assumptions upon which it is based
• Firm‘s own staff may not be able to determine which factors are most important
• Personality of individual on project may infect the message
• TFs do not provide conclusive results and predicting probability is difficult to do
• Individual analytical methods all have their own weaknesses:
- Delphi method: Qualified experts are crucial
- Trend extrapolation /growth curves: future does not always follow the patterns of
the past, and dependent on the limits chosen for the analysis
- Relevance trees/morphological analysis: subject to human error, vulnerable to lack
of insight, and difficult to construct
Marius Chofor Asaba I
TF methods: Criteria for Applying the techniques
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• Make use of searching questions relevant for applying the TF method:
- Is the system ready to absorb/contribute to arising technology needs of the society?
- Does the system have any mechanism to;
anticipate changes?
assess needed technologies?
assign strategies to implement the technologies?
Marius Chofor Asaba I
TF methods: Criteria for Selection of the techniques
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• This is quite complex and depends on following factors:
- Purpose for which the forecast is being made
- Reliability needed
- Precision of the data
- Time period and resources are available
- Ability to combine various interacting factors
• Cost varies per method used (Modelling is the most expensive) and accuracy also
greatly influences this
Marius Chofor Asaba I
TF methods: Criteria for Selection of the techniques
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The TF Techniques which can be used for
Problem
identification
Relevant factors Trends of
parameters
Relationships
among
parameters
Implications for
action
Marius Chofor Asaba I
TF methods: Brain Teaser
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The TF Techniques which can be used for
Problem
identification
Relevant factors Trends of
parameters
Relationships
among
parameters
Implications for
action
Brainstorming Brainstorming Extrapolation Relationships
among
parameters
Expert opinion
Delphi Delphi Growth curves Dynamic
modelling
Scenario writing
Expert Opinion -Expert opinion
-Monitoring
-Scenario writing
Substitution -Cross-impact
analysis
-Relevance trees
Modelling and
simulation
Marius Chofor Asaba I
TF methods: Application of technology forecasting
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Technique Questions it tries to answer Applications
Trend extrapolation Past versus future | Is there a rate change? | Why is the rating declining?
| Future performance levels | Total market size
R&D Market planning |
Corporate planning
Growth curves Is there a limit? | Sales growth of new product | Setting up new plant
capacity
New product identification |
Production
Delphi When can, will or should certain events occur? | Setting up goals | What
are the elements of future
R&D | Market research | New
product identification
Morphology Can we have a new way? | Did we consider all alternatives? | Listing
diversification alternatives
Value engineering design
Cross-impact analysis Can interaction of events delay or accelerate the growth? LRP R&D
Relevance tree Target-oriented planning | Problem solution convergence R&D
Mathematical modelling Thought provocation R&D of new products | How to assess alternative
policies? | How to change course of action to achieve a desired result
Policy analysis | R&D |
Production
Scenario writing Innovation stimulation | Consideration of all interactions Policy planning
Technology monitoring What are the new areas? | What are the likely new products? |
Prediction of break through threats to existing products
R&D | Production
Production demand /
replacement decisions
R&D marketing New product
Marius Chofor Asaba I
Agenda
36
1 Introduction
2 Methods
3 Case Study on Delphi
Anticipation of industry convergence
Marius Chofor Asaba I
Delphi: Case Study
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Marius Chofor Asaba I
Literature
• Business and Competitive Analysis; C. Fleisher & B. Bensoussan (FT Press
2007)
• 105th FoCARS, Foundation Course For Agricultural Research Service; D.
Rama Rao (NAARM, 2017)
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