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66 per cent like being able to shop for more than one product and in many
outlets at the same time； 54 per cent claim that there are products that they
Operations Management 245
can only find online； 53 per cent like not having to deal with salespeople；
44 per cent reckon product information is be。。er online； and perhaps the
most revealing statistic of all； only 40 per cent preferred online to offline
because they expected to find lower prices。
Information systems （IS）
If the internet is the external operations powerhouse； IS systems are the
mirror image； handling all the data needed to run a 21st…century organization。
Every part of a business collects data； production monitors output
efficiencies； stock levels and quality； finance gets the accounts； marketing
gets figures on customer demand and petitor market share； HR keeps
track of pay； training； accidents at work and sickness。 But none of this data
is much use unless there is an integrated system that can integrate； collate；
analyse and disseminate this information in a timely manner and in a
format that can be understood and used by operating management。
To be effective； IS needs an appropriate amount of hardware and so。。ware；
as firms that effectively exploit the power muter information systems
can deliver can outperform others。 It can play a major role in opening new
distribution channels； streamlining supply chains and providing efficient
electronic markets。 Mainframe/legacy systems； PCs； workstations； intranets
and the internet； as well as local area networks （LANs） and wide area
networks （WANs）； customer relationship management （CRM） and the
ubiquitous Moore’s Law stating that processing power doubles every 18
months while costs halve； are all vital elements in an MBA’s IS vocabulary。
Quantitative
and qualitative
research and
analysis
。 Decision…making tools
。 Statistical methods
。 Making forecasts
。 Assessing cause and effect
。 So。。 studies
。 Carrying out surveys
Finance； marketing； operations and HRM （human resource management）
collect an inordinate amount of data and the IT （information technology）
department processes it。 However； it falls to the application of analysis
techniques to interpret the data and explain its significance or otherwise。
Bald information on its own is rarely of much use。 If staff turnover goes
up； customers start plaining and bad debts are on the rise； these facts
on their own may tell you very li。。le。 Are these figures close to average；
or should it be the mean or the weighted average that will reveal their
true importance？ Even if the figures are bad； you need to know if they are
outside the range you might reasonably expect to occur in any event。
Generally； managers prefer to rely on quantitative methods for analysis
and there are always plenty of numbers to be obtained。 Figures are efficient；
easy to manipulate and you should use them whenever you can。 But there is
11
Quantitative and Qualitative Research and Analysis 247
also a rich seam of qualitative methods to get valuable information that you
cannot obtain well with quantitative methods。 These qualitative methods
can be used to study human behaviour and more importantly changes in
behaviour。 plex feelings and opinions； such as why employee morale
is low； customers are plaining or shareholders dissatisfied； cannot be
prehensively captured by quantitative techniques。 Using qualitative
methods it is possible to study the variations of plex； human behaviour
in context。 By connecting quantitative data to behaviour using qualitative
methods； a process known as triangulation； you can add an extra dimension
to your analysis with people’s descriptions； feelings and actions。
In business schools these two methods of analysis are rarely taught together
and are even less likely to be taught in the same department； though
some marketing professors will manage joined…up analysis in areas such as
surveys。 At Ro。。erdam School of Management； Erasmus University （
rsm。nl）； for example； in ‘Quantitative Platform for Business’ students
investigate the qualitative as well as the quantitative methods available for
problem solving within an organization。 But EM Lyon （em…lyon/
english） confines its teaching to ‘Business Statistics’ covering ‘the essential
quantitative skills that will be required of you throughout the programme’。
MIT Sloan School of Management （h。。p：//mitsloan。mit。edu/mba/program/
firstsem。php） has a teaching module； ‘Data； Models； and Decision’； in its
first semester that ‘Introduces students to the basic tools in using data to
make informed management decisions’。 That seems heavy on quantitative
analysis； covering probability； decision analysis； basic statistics； regression；
simulation； linear and nonlinear optimization； and discrete optimization；
but devoid of much qualitative teaching ma。。er。 But MIT does uses cases；
and examples drawn from marketing； finance； operations management；
and other management functions； in teaching this subject。
QUANTITATIVE RESEARCH AND ANALYSIS
The purpose of quantitative research and analysis is to provide managers
with the analytical tools necessary for making be。。er management decisions。
The subject； while not rocket science； requires a reasonable grasp
of mathematical concepts。 It is certainly one area that many a。。ending business
school find challenging。 But as figures on their own are o。。en of li。。le
help in either understanding the underlying facts or choosing between
alternatives； some appreciation of probability； forecasting and statistical
concepts is essential。 It is an area where； with a modicum of application；
an MBA can demonstrate skills that will make them stand out from the
crowd。
248 The Thirty…Day MBA
Decision theory
Blaise Pascal （1623–62）； the French mathematician and philosopher who
with others laid the foundations for the theory of probability； is credited
with inaugurating decision theory； or decision making under conditions
of uncertainty。 Until Pascal’s time； the outes of events were considered
to be largely in the hands of the gods； but he instigated a method for using
mathematical analysis to evaluate the cost and residual value of various
alternatives so as to be able to choose the best decision when all the relevant
information is not available。
Decision trees
Decision trees are a visual as well as valuable way to organize data so as
to help make a choice between several options with different chances of
occurring and different results if they do occur。 Trees （see Figure 11。1） were
first used in business in the 1960s but became seriously popular from 1970
onwards when algorithms were devised to generate decision trees and
automatically reduce them to a manageable size。
Making a decision tree requires these steps to be carried out initially；
from which the diagram can be drawn：
。 Establish all the alternatives。
。 Estimate the financial consequences of each alternative。
。 Assign the risk in terms of uncertainty allied with each alternative。
Figure 11。1 shows an example decision tree。 The conventio