Management: Six
basic steps in Decision
Making
Step 1: Define the Problem
Decisions do not occur in a vacuum. Many come about as part of the firm's planning process. Others are promptedby new opportunities or new problems. It is natural to ask: What brought about the need for the decision? What is the decision all about? In all kinds of textbooks examples, the decision problem is stated and is reasonably well defined. In practice, however, managerial decisions do not come so neatly packaged; rather, they are messy and poorly defined. Thus, problem definition is a prerequisite for problem management.
A key part of problem definition is identifying the setting or context..
Identifying the decision context and the decision maker represents a large step toward understanding the choice process. The particular setting has a direct bearing on both the decision maker's objectives and the available courses of action. The next two steps consider each of these aspects in turn.
Step 2: Determine the Objective
When it comes to economic decisions, it is a truism that «you can't always get what you want». But to make any progress at all in your choice, you have to know what you want. In most private sector decisions, the principal objective of the firm—and barometer of its performance—is profit: the difference between the firm's total revenues and its total costs. Thus, among alternative courses of action, the manager will select the one that will maximize the profit of the firm. Attainment of maximum profit worldwide is the natural objective of the multinational steel company, the drug company, and the management and shareholders of Disney, Canon, Time Inc., Texaco, and Pennzoil. Sometimes the manager focuses on the narrower goal of minimizing cost. For instance, the firm may seek to produce a given level of output at the least cost or to obtain a targeted increase in sales with minimal expenditure on advertising. In a host of settings, measures that reduce costs directly serve to increase profits.
The objective in a public sector decision, whether it be building an airport or regulating a utility, is broader than the private profit standard. In making its choice, the government decision maker should weigh all benefits and costs, not solely those that accrue as revenue or are incurred as expenses. According to this benefit-cost criterion, the airport may be worth building even if it fails to generate a profit for the government authority. The optimal means of regulating the production decisions of the utility depend on a careful comparison of benefits (mainly in the form of energy conservation) and costs (in material and environmental terms).
In practice, profit maximization and benefit-cost analysis are not always unambiguous guides to decision making. One difficulty is posed by the timing of benefits and costs. Should a firm (the drug company, for example) make an investment (sacrifice profits today) for greater profits five or ten years from now? Are the future benefits to air travelers worth the present capital expense of building the airport? Both private and public investments involve trade-offs between present and future benefits and costs. Thus, in pursuing its profit goal, the firm must establish a comparable measure of value between present and future monetary returns.
Uncertainty poses a second difficulty. In many economic decisions, it is customary to treat the outcomes of various actions as certain. For instance, a fast-food chain may know that it can construct a new outlet in 21 days at a cost of $90 per square foot. The cost and timing of construction are not entirely certain, but the margin of error is small enough to have no bearing on the company's decisions and thus can be safely ignored. In contrast, the cost and date of completion of a nuclear power plant are highly uncertain (due to unanticipated design changes, cost overruns, schedule delays, and the like).
At best. the utilities that share ownership of the plant may be able to estimate a range of cost outcomes and completion dates and assess probabilities for these possible outcomes. (With the benefit of hindsight, one now wishes that the utilities had recognized the risks and safety problems of nuclear plants 10 and 20 years ago, when construction on many plants was initiated.)
The presence of risk and uncertainty has a direct bearing on the way the decision maker thinks about his or her objective. The drug company seeks to maximize its profit, but there is no simple way to apply the profit criterion to determine its best R&D choice. The company cannot use the simple rule «choose the method that will yield the greater profit,» because the ultimate profit from either method cannot be pinned down ahead of time. In each case, there are no profit guarantees; rather, the drug company faces a choice between two risky options. Similarly, public programs and regulatory policies will generate future benefits and costs that cannot be predicted with certainty.
What is the decision maker's goal? What end is he or she pursuing? How should the decision maker value outcomes with respect to this goal? What if he or she is pursuing multiple, conflicting objectives?
Vocabulary
to prompt - подсказывать, приглашать; to state - констатировать reasonably - разумно, приемлемо; neatly packaged - аккуратно упакован messy - неряшливый
prerequisite - предпосылка, необходимое условие
particular setting - конкретная постановка
in turn - в свою очередь
truism - банальность
profit - прибыль
attainment - достижение
shareholder - акционер, пайщик
target - цель, мишень
to weigh - весить
solely – только; benefit-cost criterion- критерий издержек и прибылей;
means – средства; unambiguous – недвусмысленный; trade-off – компромисс; customary - обычный, традиционный; yield – прибыль;
to be pinned down - быть просчитанным, определенным
to predict – предсказывать;
General understanding:
l) What is the difference between the book examples and practice? 2) What role does the problem of definition play for the problem management? 3)What role does context play for problem definition? 4)What is «truism»? 5)What is the difference between the objective in a public and private sector decision? 6)What are the difficulties of the decision making?
1. Which of the following is not true:
a) Decisions come as a part of the planning process. b)In practice problems are very hard to recognize, c) Identifying context is a key part of problem definition, d)Profit is the aim of any firm's transaction.
e) Maximizing profits and minimizing yields is the primary problem of any manager.
f) Ultimate profit from either method cannot be pinned down ahead of time.
2. Define the following in English:
a)profit
b)shareholders
c) particular setting
d)attainment of maximum profit
e) means of regulating the production
f) objective
3. Give an example of truism. What truisms
make it hard to come up with a sound
solution in economics?
Questions for discussion:
l)Give an example of a «messy and poorly defined» problem which you had to solve. What was your first step?
2)Do you agree that problems in textbooks are «neatly packaged»? Is it reasonable to use the examples if one cannot use the solutions in practice?
3)Do you agree that the objective of any firm is profit? What about the image and reputation? What is more important for the development of a firm? Give an example of a situation when a) profit is the objective b) reputation and image are the objectives
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Step 3: Explore the Alternatives
After addressing the question «What do we want?», it is natural to ask, «What are our options?» The ideal decision maker, if such a person exists, would lay out all the available courses of action and then choose the one that would best achieve his or her objective. Given human limitations, decision makers cannot hope to identify and evaluate all possible options. The cost of doing so simply would be too great. Still, one would hope that attractive options would not be overlooked or, if discovered, not mistakenly dismissed. No analysis can begin with all the available options in hand. However, a sound decision framework should be able to uncover options in the course of the analysis.
Most managerial decisions involve more than a once-and-for-all choice from among a set of options. Typically, the manager faces a sequence of decisions from among alternatives.
At the outset, management at Time Inc. had to decide whether or not to develop Picture Week for market testing. The whole point of the development and testing program was to provide information on which management could base its main decision: whether or not to undertake a full-fledged, nationwide launch of the magazine. Notice that the company could have launched the magazine without extensive 
market testing. However, it rejected this riskier strategy in favor of a contingent plan of action: to undertake the testing program and then launch the magazine if and only if the test results and economic forecasts were both favorable.
Sequential decision making also lies at the heart of the negotiation dilemma which many firms face. Each side must formulate its current negotiation stance (how aggressive or conciliatory an offer to make) in light of current court results and the offers (both its own and its opponent's) made to date. Thus, a commonly acknowledged fact about negotiation is that the main purpose of an opening offer is not to have the offer accepted (if it were, the offer probably was far too generous); rather, the offer should direct the course of the offers to follow. Step 4: Predict the Consequences Depending on the situation, the task of predicting the consequences may be straightforward orformidable. Sometimes elementary arithmetic suffices. For instance, the simplest profit calculation requires only subtracting costs from revenues. Or suppose the choice between two safety programs is made according to which saves the greater number of lives per dollar expended. Here the use of arithmetic division is the key to identifying the preferred alternative.
MODELS
In more complicated situations, however, the decision maker often must rely on a model to describe how options translate into outcomes. A model is a simplified description of a process, relationship, or other phenomenon. By deliberate intent, a model focuses on a few key features of a problem to examine carefully how they work while ignoring other complicating and less important factors. Of course, the main purposes of models are to explain and to predict—to account for past outcomes and to forecast future ones.
The kinds of predictive models are as varied as the decision problems to which they are applied. Many models rest on economic relationships.
Suppose the multinational steel company predicts that a 10 percent price cut will increase unit sales by 15 percent in the foreign market. The basis for this prediction is the most fundamental relationship in economics: the demand curve.
Other models rest on engineering, statistical, legal, and scientific relationships.
So far as prediction is concerned, a key distinction can be drawn between deterministic and probabilistic models. A deterministic model is one in which the outcome is certain (or close enough to a sure thing that it can be taken as certain).
For instance, a soft-drink manufacturer may wish to predict the numbers of individuals in the 10-to-25 age groupover the next ten years. There are ample demographic statistics with which to make this prediction. Obviously, the numbers in this age group five years from now will consist of those who today are between ages 5 and 20, minus a predictable small number of deaths. Thus, a simple deterministic model suffices for the prediction. However, the forecast becomes much less certain when it comes to estimating the total consumption of soft drinks by
this age group or the market share of a given product. Obviously, the market share of a particular drink— тsay, one with ten percent or more real juice—will depend on many unpredictable factors, including the advertising, promotion, and price decisions of the firm and its competitors, as well as consumer tastes. As the term suggests, aprobabilistic model accounts for a range of possible future outcomes, each with a
probability attached. For instance, the five-year market-share forecast for the natural-juice soft drink might take the following form: a 30 percent chance of less than a 3 percent share, a 25 percent chance of a 3 to 6 percent share, a 30 percent chance of a 6 to 8 percent share, and a 15 percent chance of an 8 to 15 percent share.
Vocabulary:
option - вариант, опция; to lay out - разложить, скомпоновать;
to identify - определять, идентифицировать; to evaluate – оценивать;
to overlook - упускать из виду; to dismiss - прекращать, отбрасывать;
sound decision framework - система взвешенного управления;
once-and-for-all - на все случаи жизни, однажды и на всегда;
full-fledged - зд. полноценный; negotiation stance - позиция на переговорах conciliatory – примирительный;acknowledged - признанный, подтвержденный purpose - цель generous - щедрый
straightforward - простой, прямолинейный
formidable - трудный, грозный
to suffice - хватать чего-либо
complicated - сложный
to examine - исследовать
account for - брать в расчет, считаться с чем-либо
legal – юридический
age group - возрастная группа
ample- обильный, достаточный
obviously – очевидно
probabilistic model - вероятностная модель
General understanding:
l)What is according to the author natural logic of a manager? 2)What would an ideal decision maker do? 3)What is a sequential decision making? 4)What is a «commonly acknowledged fact about negotiation»? 5)When does elementary arithmetics suffice? 6) When must decision maker rely on models? 7)What is a a model in general? 8) What types of predictive models are mentioned in the text?
1. Define the following in English:
a) human limitations
b)sound decision
c) once-and-for all choice
d)negotiation stance
e) engineering relationships
f) legal relationships
g) scientific relationships h)probabilistic model
2. Answer the following questions judging on your own experience:
What are the alternative courses of action?
b) What are the variables under the decision
maker's control?
c) What constraints limit the choice of options?
ci) What are the consequences of each alternative
action?
є) Should conditions change, how would this affect outcomes?
i) If outcomes are uncertain, what is the likelihood of each?
g) Can better information be acquired to predict outcomes?
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Step 5: Make a Choice
In the vast majority of decisions we may encounter, the objectives and outcomes are directly quantifiable. Thus, the private firm, such as the steelmaker, can compute the profit results of alternative pries and output plans.Analogously, a government decision maker may know the computed net benefits (benefits minus costs) of different program options. Given enough time, the decision maker could determine a preferred course of action byenumeration, that is, testing a number of alternatives and selecting the one that best meets the objective. This is fine for decisions involving a small number of choices, but it is impractical for more complex problems.
For instance, what if the steel firm drew up a list of two dozen different pricing and production plans, computed the profits of each, and settled on the best of the lot? How could management be sure this choice is truly «optimal,» that is, the best of all possible plans? What if a more profitable plan, say, the twenty-fifth candidate, wasoverlooked? Expanding the enumerated list could reduce this risk, but at considerable cost.
Fortunately, the decision maker need not rely on the painstaking method of enumeration to solve such problems. A variety of methods can identify and cut directly to the best or optimal decision. These methods rely to varying extents on marginal analysis, linear programming, decision trees, and benefit-cost analysis. These approaches are important not only for computing optimal decisions but for checking why they are optimal.
Step 6: Perform Sensitivity Analysis In tackling and solving a decision problem, it is important to understand and be able to explain to others the «why» of your decision. The solution, after all, did not come out of thin air. It depended on your stated objectives, the way you structured the problem (including the set of options you considered), and your method of predicting outcomes. Thus, sensitivity analysis considers how an optimal decision would change if key economic facts or conditions were altered.
Here is a simple example of the use of sensitivity analysis. Senior management of a consumer products firm is conducting a third-year review of one of its new products. Two of the firm's business economists
have prepared an extensive report that projects significant profits from the product over the next two years. These profit estimates suggest a clear course of action: continue marketing the product. As a member of senior management, would you accept this recommendation uncritically? Probably not. You naturally would want to determine what is behind the profit projection. After all, you may be well aware that the product has not yet earneda profit in its first two years. (Although it sold reasonably well, it also had high advertising and promotion costs and a low introductory price.) What is behind the new profit projection? Larger sales and/or a higher price? A significant cost reduction? The process of tracking down the basic determinants of profit is one aspect of sensitivity analysis.
As one would expect, the product's future revenues and costs may be highly uncertain. As a consequence, management should recognize that the revenue and cost projections come with a significant margin of errorattached.
It is natural to investigate the profit effects if outcomes differ from the report's forecasts. What if sales are 12 percent lower than expected? What if projected cost reductions are not realized? What if the price of a competing product is slashed? By
answering these «what-if» questions, management can determine the degree to which its profit projections, and therefore its marketing decision, are sensitive to
the uncertain outcomes of key economic variables. Sensitivity analysis is useful in: (1) providing insight into the key features of the problem that affect the decision;
(2) tracing the effects of changes in variables about which the manager may be uncertain; and
(3) generating solutions in cases of recurring decisions under slightly modified conditions.
After all analysis is done, what is the preferred course of action? For obvious reasons, this step (along with step 4) occupies the lion's share of the analysis and discussion. Once the decision maker has put the problem in context, formalized the objectives, and identified available alternatives, how does he or she go about finding a preferred course of action?
What features of the problem determine the optimal choice of action? How does the optimal decision change if conditions in the problem are altered? Is the choice sensitive to key economic variables about which the decision maker is uncertain?
Vocabulary:
to encounter - встречаться, сталкиваться
quantifiable - измеримый
analogously - аналогично
enumeration - перечисление
to settle on smth. - остановиться на чем-либо
truly - искренне
fortunately - к счастью
painstaking - кропотливый
optimal decision - оптимальное решение
to tackle - блокировать, справиться
do not come out of thin air - не берутся «с потолка»
sensitivity analysis - анализ чувствительности to alter - изменять(-ся)
extensive report - развернутый доклад
estimate - оценка
to earn - зарабатывать
recognize - распознавать, различать
attached - прикрепленный, присоединенный
insight - понимание
lion's share - львиная доля
General understanding:
1) Under what circumstances can a private firm compute the profit results? 2) What is impractical for solving complex problems? 3) What are methods of identifying the problems? 4) What is important in understanding and explaining the problem? 5) What is sensitivity analysis? 6)How do the projections of renew and costs come? 7)When is sensitivity analysis useful?
1. Define the following:
a)net benefits
b)sensitivity analysis
c) basic determinants of profit
2. Translate into Russian:
a) The objectives and outcomes are directly quantifiable. b) A government decision maker may know the computed net benefits (benefits minus costs) of different program options.
c) The decision maker need not rely on the painstaking method of enumeration to solve such problems.
d)Sensitivity analysis considers how an optimal decision would change if key economic facts or conditions were altered.
e) It is natural to investigate the profit effects if outcomes differ from the report's forecasts.
Questions for discussion:
l)Do you agree that the method of enumeration is ineffective in solving massive problems?
2) Should a decision maker, do you think, rely on the data provided. What sources of information could be referred to as more reliable and less reliable?
3)Could press publications be used as sources of information for making a decision? Give an example of a) international b)federal c) local press which is a)completely reliable b) completely unreliable.