ADMS 4010 Decision Making Process Speech Draft

Book Title: eTextbook: Organization Theory and Design
Organizational Decision Making
Incremental Decision Process Model
Incremental Decision Process Model
Henry Mintzberg and his colleagues at McGill University approached organizational
decision making from a different perspective. They identified 25 decisions made in
organizations and traced the events associated with these decisions from beginning to
end.* Their research identified each step in the decision sequence. This approach to
decision making, called the incremental decision process model, places less emphasis
on the political and social factors described in the Carnegie model, but tells more about
the structured sequence of activities undertaken from the discovery of a problem to its
solution.*
Sample decisions in Mintzberg’s research included choosing which aircraft to acquire
for a regional airline, developing a new supper club, developing a new container terminal
in a harbour, identifying a new market for a deodorant, installing a controversial new
medical treatment in a hospital, and firing a star radio announcer.* The scope and
importance of these decisions are revealed in the length of time taken to complete them.
Most of these decisions took more than a year, and one-third of them took more than
two years. Most of these decisions were nonprogrammed and required custom-designed
solutions.
One discovery from this research is that major organizational choices are usually a series
of small choices that combine to produce the major decision. Thus, many organizational
decisions are a series of nibbles rather than a big bite. Organizations move through
several decision points and may hit barriers along the way. Mintzberg called these
barriers decision interrupts. An interrupt may mean an organization has to cycle back
through a previous decision and try something new. Decision loops or cycles are one way
the organization learns which alternatives will work. The ultimate solution may be very
different from what was initially anticipated.
The pattern of decision stages discovered by Mintzberg and his associates is shown in
Exhibit 13.4. Each box indicates a possible step in the decision sequence. The steps take
place in three major decision phases: identification, development, and selection.
Exhibit 13.4.
Adapted and reprinted from “The Structure of Unstructured Decision Processes,” by Henry Mintzberg,
Duru Raisinghani, and Andre Theorêt, published in Administrative Science Quarterly 21, no. 2 (1976),
266, by permission of The Administrative Science Quarterly. Copyright © 1976 Cornell University.
The Incremental Decision Process Model
Identification Phase
The identification phase begins with recognition. Recognition means one or more
managers become aware of a problem and the need to make a decision. Recognition is
usually stimulated by a problem or an opportunity. A problem exists when elements in
the external environment change or when internal performance is perceived to be below
standard. In the case of firing a radio announcer, comments about the announcer came
from listeners, other announcers, and advertisers. Managers interpreted these cues until
a pattern emerged that indicated a problem had to be addressed.
The second step is diagnosis, in which more information is gathered if needed to define
the problem situation. Diagnosis may be systematic or informal, depending upon the
severity of the problem. Severe problems do not allow time for extensive diagnosis; the
response must be immediate. Mild problems are usually diagnosed in a more systematic
manner.
Development Phase
In the development phase, a solution is shaped to solve the problem defined in the
identification phase. The development of a solution takes one of two directions. First,
search procedures may be used to seek out alternatives within the organization’s
repertoire of solutions. For example, in the case of firing a star announcer, managers
asked what the radio station had done the last time an announcer had to be let go. To
conduct the search, organization participants may look into their own memories, talk to
other managers, or examine the formal procedures of the organization. The screen
routine is used when search is expected to generate more ready-made alternatives than
can be practically evaluated. Screening “is a superficial routine, more concerned with
eliminating what is infeasible than with defining what is appropriate.”*
The second direction of development is to design a custom solution. This happens when
the problem is novel so that previous experience has no value. Mintzberg found that in
these cases, key decision makers have only a vague idea of the ideal solution. Gradually,
through a trial-and-error screening process, a custom-designed alternative will emerge.
Development of the solution is a groping, incremental procedure, like building a house
brick by brick.
Selection Phase
The selection phase is when the solution is chosen. This phase is not always a matter of
making a clear choice among alternatives. In the case of custom-made solutions,
selection is more an evaluation of the single alternative that seems feasible.
Evaluation and choice may be accomplished in three ways. The judgment form of
selection is used when a final choice falls upon a single decision maker, and the choice
involves judgment based upon experience. In analysis evaluation, alternatives are
evaluated on a more systematic basis, such as with management science techniques.
Mintzberg found that most decisions did not involve systematic analysis and evaluation
of alternatives. Bargaining occurs when selection involves a group of decision makers.
Each decision maker may have a different stake in the outcome, so conflict emerges.
Discussion and bargaining occur until a coalition is formed, as in the Carnegie model
described earlier.
When a decision is formally accepted by the organization, authorization takes place. The
decision may be passed up the hierarchy to the responsible hierarchical level.
Authorization is often routine because the expertise and knowledge rest with the lowerlevel decision makers who identified the problem and developed the solution. A few
decisions are rejected because of implications not anticipated by lower-level managers.
Dynamic Factors
The lower part of the chart in Exhibit 13.4 shows lines running back toward the
beginning of the decision process. These lines represent loops or cycles that take place in
the decision process. Organizational decisions do not follow an orderly progression from
recognition through authorization. Minor problems arise that force a loop back to an
earlier stage. These are decision interrupts. If a custom-designed solution is perceived as
unsatisfactory, the organization may have to go back to the very beginning and
reconsider whether the problem is truly worth solving. Feedback loops can be caused by
problems of timing, politics, disagreement among managers, inability to identify a
feasible solution, turnover of managers, or the sudden appearance of a new alternative.
For example, when a small local airline made the decision to acquire jet aircraft, the
board authorized the decision, but shortly after, a new chief executive was brought in
who cancelled the contract, recycling the decision back to the identification phase. He
accepted the diagnosis of the problem but insisted upon a new search for alternatives.
Then a foreign airline went out of business and two used aircraft became available at a
bargain price. This presented an unexpected option, and the chief executive used his own
judgment to authorize the purchase of the aircraft.*
Because most decisions take place over an extended period of time, circumstances
change. Decision making is a dynamic process that may require a number of cycles
before a problem is solved. An example of the incremental process and cycling that can
take place is illustrated in Gillette’s decision to create a new razor.
In Practice
Gillette Company
The Gillette Company uses incremental decision making to perfect the design of
razors such as the Sensor, the Mach3, and the vibrating M3Power. Consider the
development of the Mach3. While searching for a new idea to increase sales in
Gillette’s mature shaving market, researchers at the company’s British research
lab came up with a bright idea to create a razor with three blades to produce a
closer, smoother, more comfortable shave (recognition and diagnosis). Ten years
later, the Mach3 reached the market, after thousands of shaving tests, numerous
design modifications, and a development and tooling cost of $750 million, roughly
the amount a pharmaceutical firm invests in developing a blockbuster drug.
The technical demands of building a razor with three blades that would follow a
man’s face and also be easy to clean had several blind alleys. Engineers first tried
to find established techniques (search, screen), but none fit the bill. Eventually a
prototype called Manx was built (design), and in shaving tests it “beat the pants
off” Gillette’s Sensor Excel, the company’s best-selling razor at the time.
However, Gillette’s CEO insisted that the razor had to have a radically new blade
edge so the razor could use thinner blades (internal interrupt), so engineers began
looking for new technology that could produce a stronger blade (search, screen).
Eventually, the new edge, known as DLC for diamond-like carbon coating, would be
applied atom by atom with chip-making technology (design).
The next problem was manufacturing (diagnosis), which required an entirely new
process to handle the complexity of the triple-bladed razor (design). Although the
board gave the go-ahead to develop manufacturing equipment ( judgment,
authorization), some members became concerned because the new blades, which
are three times stronger than stainless steel, would last longer and cause Gillette to
sell fewer cartridges (internal interrupt). The board eventually made the decision to
continue with the new blades, which have a blue indicator strip that fades to white
and signals when it’s time for a new cartridge.
The board gave final approval for production of the Mach3 to begin in the fall of
1997. The new razor was introduced in the summer of 1998 and began smoothly
sliding off shelves. Gillette recovered its huge investment in record time. Gillette
then started the process of searching for the next shaving breakthrough all over
again, using new technology that can examine a razor blade at the atomic level and
high-speed video that can capture the act of cutting a single whisker. The company
has moved ahead in increments; in 2006, Gillette launched its Fusion Power line of
razors, which took eight years of innovation to develop. The line has 20 patented
features.*
At Gillette, the identification phase occurred because executives were aware of the need
for a new razor and became alert to the idea of using three blades to produce a closer
shave. The development phase was characterized by the trial-and-error custom design
leading to the Mach3. During the selection phase, certain approaches were found to be
unacceptable, causing Gillette to cycle back and redesign the razor, including using
thinner, stronger blades. Advancing once again to the selection phase, the Mach3 passed
the judgment of top executives and board members, and manufacturing and marketing
budgets were quickly authorized. This decision took more than a decade!
Book Title: eTextbook: Organization Theory and Design
Organizational Decision Making
Carnegie Model
Carnegie Model
The Carnegie model of organizational decision making is based on the work of Richard
Cyert, James March, and Herbert Simon, who were all associated with Carnegie-Mellon
University.* Their research helped formulate the bounded rationality approach to
individual decision making, as well as provide new insights about organizational
decisions.
Until their work, research in economics assumed that business firms made decisions as a
single entity, as if all relevant information were funnelled to the top decision maker for a
choice. Research by the Carnegie group indicated that organization-level decisions
involved many managers and that a final choice was based on a coalition among those
managers. A coalition is an alliance among several managers who agree about
organizational goals and problem priorities.* It could include managers from line
departments, staff specialists, and even external groups, such as powerful customers,
bankers, or union representatives.
Management coalitions are needed during decision making for two reasons. First,
organizational goals are often ambiguous, and operative goals of departments are often
inconsistent. When goals are ambiguous and inconsistent, managers disagree about
problem priorities. They must bargain about problems and build a coalition around the
question of which problems to solve.
The second reason for coalitions is that individual managers intend to be rational but
function with human cognitive limitations and other constraints, as described earlier.
Managers do not have the time, resources, or mental capacity to identify all dimensions
and to process all information relevant to a decision. These limitations lead to coalitionbuilding behaviour. Managers talk to each other and exchange points of view to gather
information and reduce ambiguity. People who have relevant information or a stake in a
decision outcome are consulted. Building a coalition will lead to a decision that is
supported by interested parties.
The process of coalition formation has several implications for organizational decision
behaviour. First, decisions are made to satisfice rather than to optimize problem
solutions. Satisficing means organizations accept a satisfactory rather than a maximum
level of performance, enabling them to achieve several goals simultaneously. In decision
making, the coalition will accept a solution that is perceived as satisfactory to all
coalition members. Second, managers are concerned with immediate problems and
short-run solutions. They engage in what Cyert and March called problemistic search.*
Problemistic search means managers look around in the immediate environment for a
solution to quickly resolve a problem. Managers don’t expect a perfect solution when
the situation is ill defined and conflict laden. This contrasts with the management science
approach, which assumes that analysis can uncover every reasonable alternative. The
Carnegie model says that search behaviour is sufficient to produce a satisfactory solution
and that managers typically adopt the first satisfactory solution that emerges.
Discussion and bargaining are especially important in the problem identification stage of
decision making. Unless coalition members perceive a problem, action will not be taken.
The decision process described in the Carnegie model is summarized in Exhibit 13.3.
The Carnegie model points out that building agreement through a managerial coalition
is a major part of organizational decision making. This is especially true at upper
management levels. Discussion and bargaining are time consuming, so search
procedures are usually simple and the selected alternative satisfices rather than
optimizes problem solution. When problems are programmed—are clear and have been
seen before—the organization will rely on previous procedures and routines. Rules and
procedures prevent the need for renewed coalition formation and political bargaining.
Nonprogrammed decisions, however, require bargaining and conflict resolution.
Exhibit 13.3.
Choice Processes in the Carnegie Model
Organizations suffer when managers are unable to build a coalition around goals and
problem priorities, as illustrated by the case of Encyclopaedia Britannica.
In Practice
Encyclopaedia Britannica
For most of its 231-year history, the Encyclopaedia Britannica had been viewed as an
illustrious repository of cultural and historical knowledge—almost a national
treasure. Generations of students and librarians relied on the Britannica—but that
was before the Internet became the study tool of choice. Suddenly, the 32-volume
collection of encyclopedias, stretching four feet on a bookshelf and costing as much
as a personal computer, seemed destined to fade into history.
When Swiss-based financier Joseph Safra bought Britannica, he discovered one of
the reasons. For nearly a decade, managers had bickered over goals and priorities.
Some top executives believed the company needed to invest more in electronic
media, but others supported Britannica’s traditional direct-to-home sales force.
Eventually, the company’s Compton unit, a CD-ROM pioneer, was sold, leaving
Britannica without any presence in the new market. In the 1980s, Microsoft had
approached Britannica to develop a CD-ROM encyclopedia; when it didn’t work
out, Microsoft went with Funk & Wagnalls and developed Encarta. Microsoft
arranged to have Encarta preinstalled on PCs, so the CD-ROM was essentially free to
new PC buyers. When Britannica finally came out with its CD-ROM version, however,
it was priced at a staggering $1,200. The squabbling among managers, owners, and
editors about product development, pricing, distribution, and other important
decisions contributed to the company’s decline.
The first step in Safra’s turnaround strategy was to install a new top management
team, led by one of his long-time advisers. The team immediately coalesced around
the important problem of establishing a presence in the world of electronic media.
With this goal, the company rushed out a revamped, lower-cost CD-ROM package
and launched the Britannica.com website, which allows users to view encyclopedia
entries online as well as get a list of links to related websites. The team also created
a separate digital media division to focus on new product development, such as for
wireless Web technology. Managers are looking toward the wireless Web as the best
route to a successful future and have teamed up with numerous wireless carriers
and licensed Britannica’s content to other websites.
Building a coalition focused on common goals rather than having managers
pushing and pulling in different directions got Britannica off the critical list by
helping it cross the bridge to the digital era. Managers are in the process of
evaluation to see what new decisions need to be made to help the company thrive
in the digital world.*
The Carnegie model is particularly useful at the problem identification stage. However, a
coalition of key department managers is also important for smooth implementation of a
decision, particularly a major reorganization. Top executives at Britannica realized the
importance of building coalitions for decision making to keep the company moving
forward. When top managers perceive a problem or want to make a major decision, they
need to reach agreement with other managers to support the decision.*
Book Title: eTextbook: Organization Theory and Design
Organizational Decision Making
Management Science Approach
Management Science Approach
The management science approach to organizational decision making is the analogue
to the rational approach by individual managers. Management science came into being
during the Second World War.* At that time, mathematical and statistical techniques
were applied to urgent, large-scale military problems that were beyond the ability of
individual decision makers.
Mathematicians, physicists, and operations researchers used systems analysis to develop
artillery trajectories, antisubmarine strategies, and bombing strategies such as salvoing
(discharging multiple shells simultaneously). This is where management science came in.
Analysts were able to identify the relevant variables involved in aiming a ship’s guns
and could model them with the use of mathematical equations. Distance, speed, pitch,
roll, shell size, and so on could be calculated and entered into the equations. The answer
was immediate, and the guns could begin firing. Factors such as pitch and roll were soon
measured mechanically and fed directly into the targeting mechanism. Today, the human
element is completely removed from the targeting process. Radar picks up the target,
and the entire sequence is computed automatically.
Management science yielded astonishing success for many military problems. This
approach to decision making diffused into corporations and business schools, where
techniques were studied and elaborated. Today, many corporations have assigned
departments to use these techniques. The computer department develops quantitative
data for analysis. Operations research departments use mathematical models to quantify
relevant variables and develop a quantitative representation of alternative solutions and
the probability of each one solving the problem. These departments also use devices
such as linear programming, Bayesian statistics, PERT (Program Evaluation and Review
Technique) charts, and computer simulations. Management science is an excellent device
for organizational decision making when problems are analyzable and when the
variables can be identified and measured. Mathematical models can contain a thousand
or more variables, each one relevant in some way to the ultimate outcome. Management
science techniques have been used to correctly solve problems as diverse as finding the
right spot for a church camp, test-marketing the first of a new family of products, drilling
for oil, and radically altering the distribution of telecommunications services.* Other
problems amenable to management science techniques are the scheduling of
ambulance technicians, telephone operators, and toll collectors.*
In Practice
Algorithms Rule!
Three professors at the Rotman School of Management, Opher Baron, Oded
Berman, and Dimitry Krass, developed a complex algorithm that reduces waiting
times for many services—from lining up to get a cup of coffee to waiting times for
hospital services. The three researchers used a three-pronged approach to the
waiting problem by accounting for the regulation of demand, capacity versus
waiting time, and the cost versus the number and locations of facilities. The
algorithm is dynamic so it can account for variables such as politics, which are hard
to quantify.*
“Algorithms, they say, are taking over the world. They hold the answers to
everything from designing better cars to finding the perfect mate. …”* While the
trio has not commercialized their algorithm, according to Dr. Berman, “That is part
of the research game. … We may work at a business school but in truth we are
researchers and scientists, not business people.”* Even so, the type of research
they do in advanced mathematics is being used in a partnership between McMaster
University in Hamilton, Ontario, and the world-renowned Princess Margaret Hospital
in Toronto to determine the optimal level of radiation for cancer patients.*
“Mathematical models are bound to play a greater role in business and even
personal decision making,” Dr. Baron predicts.* For example, MapQuest uses
algorithms to work out optimal routes for drivers.
Management science can accurately and quickly solve problems that have too many
explicit variables for human processing. This system is at its best when applied to
problems that are analyzable, are measurable, and can be structured in a logical way.
Increasingly sophisticated computer technology and software programs are allowing the
expansion of management science to cover a broader range of problems than ever
before. For example, some retailers, including Home Depot, Hudson’s Bay Company,
and Club Monaco, now use software to analyze current and historical sales data and
determine when, where, and how much to mark down prices. Managers at Harrah’s
Entertainment have turned the company into one of the hottest operators of casinos by
amassing plenty of data about customers and using sophisticated computer systems to
make decisions about everything from casino layout to hotel room pricing. Prices quoted
for rooms, for instance, are based on a complex mathematical formula that takes into
account how long the customers typically stay, what games they play and how often, and
other details.*
Management science has also produced many failures.* Now, many banks use
computerized scoring systems to rate those applying for credit, but some argue that
human judgment is needed to account for extenuating circumstances.
One problem with the management science approach is that quantitative data are not
rich and do not convey tacit knowledge. Informal cues that indicate the existence of
problems have to be sensed on a more personal basis by managers.* The most
sophisticated mathematical analyses are of no value if the important factors cannot be
quantified and included in the model. Things such as competitor reactions, consumer
tastes, and product warmth are qualitative dimensions.
In these situations, the role of management science is to supplement manager decision
making. Quantitative results can be given to managers for discussion and interpretation
along with their informal opinions, judgment, and intuition. The final decision can
include both qualitative factors and quantitative calculations.
Book Title: eTextbook: Organization Theory and Design
Organizational Decision Making
Organizational Decision Making
Organizations are composed of managers who make decisions using both rational and
intuitive processes, but organization-level decisions are not usually made by a single
manager. Many organizational decisions involve several managers. Problem identification
and problem solution involve many departments, multiple viewpoints, and even other
organizations, which are beyond the scope of an individual manager.
The processes by which decisions are made in organizations are influenced by a number
of factors, particularly the organization’s own internal structures and the degree of
stability or instability of the external environment.* Research into organization-level
decision making has identified four primary types of organizational decision-making
processes: the management science approach, the Carnegie model, the incremental
decision process model, and the garbage can model (discussed in the following section).

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