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Management and Planning – lecture 1 - decision-making
Geoff Leese September 2008, revised August
2009
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Decision-making
Integral part of management Occurs in every function and at
all levels Choosing necessary or
desirable outcomes Is an iterative process Needs flair, intuition, judgment
& creativity
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H A Simon’s phases of decision-making (1) Intelligence
search the environment for conditions calling for decisions
Design Inventing, developing and
analysing possible courses of action. Understanding the problem, generating possible solutions and testing solutions for feasibility.
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H A Simon’s phases of decision-making (2)
Choice Selecting an alternative or course
of action from those available. The choice is then implemented
Review Assessing past choices
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Programmed(structured) decisions
Characteristics repetitive, routine, known rules or
procedures, often automated, involve “things” rather than people, can be fairly easily delegated, more likely at lower levels of management
Examples inventory control, machine loading,
scheduling
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Non-programmed (unstructured) decisions Characteristics
novel, non-routine, decision rules unavailable or not known, high level of uncertainty, cannot be easily delegated, can involve things but always involve people, more likely at higher levels of management
Examples recruitment, employee appraisal,
mergers, launches of new products
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Levels of decision-making (1)
Strategic
Decision characteristics Information characteristics
Long time horizons, large scale resources, creativity & judgment,usually unstructured, problems difficultto define, much uncertainty, infrequent
Largely external, informal, qualitativeinfo important, forward looking,precision unimportant, instant access not vital, wide ranging,incomplete.
Tactical
OperationalRepetitive, frequent, shorttimescale, small scale resources,clear objectives and rules, little or no discretion
Largely internal, mainlyhistorical, detailed, high precision,often quantitative, instant accessoften critical, narrow in scope butcomprehensive
Rational!
Heuristic!
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Strategic decision-making
Examples mergers & takeovers, new product
planning, capital investment, financial structuring
information needs Market & economic forecasts,
political & social trends, legislative, environmental and technological constraints
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Tactical decision-making
Examples Pricing, capacity planning,
preparation of budgets, purchasing contracts
Information needs Cost & sales analyses, performance
reports, summaries of operational/production activity, budget vs. actual comparisons
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Operational decision-making
Examples production scheduling, maintenance,
re-ordering, credit approval Information needs
Sales orders, production requirements, performance measures, customer credit status, delivery records, despatch records etc
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Certainty, Risk and Uncertainty Certainty
only one possible outcome for each alternative, complete and accurate knowledge of that outcome
Risk many possible outcomes for each alternative,
but a value and probability can be assigned to each one
Uncertainty number of possible outcomes, probability and
value is unknown
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Decision models
Prescriptive (normative) automatically selects best option,
e.g. CVP analysis, linear programming, investment appraisal techniques
Descriptive try to explain decision-making
behaviour - are we always rational?
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Single, unambiguous objective
Rational decision-makingStated in numerical or financial terms
All outcomesor alternativesknown
Alternativesexpressed asobjectives
Alternativesevaluated andranked
“Best”alternativechosen
Shouldn't be used uncritically - consider “softer” issues!
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Risk assessment (expected value) Alternative A Alternative B Alternative C Probability Profit Probability Profit Probability Profit Optimistic 0.2 9000 0.3 9500 0.1 10000 Most Likely 0.6 7500 0.5 7000 0.7 6500 Pessimistic 0.2 5000 0.2 4000 0.2 3000
Expected valuesAlternative A - (0.2*9000)+(0.6*7500)+(0.2*5000) = 7300
Alternative B - (0.3*9500)+0.5*7000)+(0.2*4000) = 7150
Alternative C - (0.1*10000)+(0.7*6500)+(0.2*3000) = 6150
If objective is to maximise expected value, Alternative A is preferred.
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Decision trees
D1
D2
D3
Action A1
Action A2Outcome Y1
Outcome Y2
Outcome X1
Outcome X3
Outcome X2
Action B1
Action C1
Decision node
Outcome node
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Satisficing (1) Know all alternatives? Single, clear-
cut objective? Imperfect world! Limited search for a few
satisfactory alternatives Bounded rationality within
limitations of imperfect info and decision makers perceptions
Decision made which satisfies aspirations (that’s good enough!)
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Satisficing (2)
Very, very common! Subjectivity, rule of thumb and
judgment often used instead of mechanistic decision rules
MIS needs to supply background info and ways of finding alternatives, not mechanical decision rules
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Consensus decision-making
Most appropriate to small changes (conventional view)
Japanese think differently! What’s the question? Decision-making can be
protracted, but once taken implementation follows swiftly and effectively
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“Quality” decisions? Consideration of full range of objectives Explicit statement of objective conflict Wide range of alternatives Careful evaluation of costs & risks All available sources of info used Expert opinion used Re-examination, iteration Detailed planning for implementation Review effectiveness of past decisions
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Decision-making and MIS (1)
Supplies information, explores alternatives, provides support where manager makes the decision
or MIS takes the decision itself. Most
appropriate with routine operations where decision rules are known
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Decision-making and MIS (2)
Stru
cture
dSem
i structu
red
Unstru
cture
d
Strategicmanagement
Tactical management
OperationalManagement
Executive info systems
Expert systems, DSS
Transaction processingADM, OR &Accounting models
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Further Reading Cole G (1996) Management Theory and
Practice, DP publications Chapter 19 Elliot G & Starkings S (1998), Business
Information Technology (Prentice Hall) Chapters 2 and 7
Hannagan T(1998), Management Concepts and Practices, FT Pitman Chapter 13
Someone else's view! (follow the link) Decision making tools (follow the link)