Is IT Worth it?
The Business Value of Information Technology
Espen Andersen, 1992
Contents
-
Introduction--the accusing chorus
-
A framework for investigating IT
-
The role of IT in each quadrant
-
Quadrant
2: Design and diagnosis (physical product, unstructured process)
-
Quadrant
4: Knowledge worker (information product, unstructured process)
-
Movements between quadrants: IT and the redefining
of tasks
-
Moving West: Industrialization
-
Moving East: Informating
-
Moving North: embedding information
-
Moving South: manipulating information rather
than physical
product
-
How are we doing: Evaluating the contribution of IT
-
Manufacturing: increased productivity, but how much
is IT?
-
Design and diagnosis: Quality at a price
-
Back office: the easy things are done
-
Knowledge worker: a matter of personal learning
-
IT and movement between quadrants: the loss of
measurability
-
Conclusions -- a CIO's strategy of defence
-
Tables
-
Endnotes
-
References
Introduction--the accusing chorus
The 1990s promise to be a rather tough period for many CIOs. An
increasing
number of academic and business writers hold that information
technology
has not delivered on its many promises of increased business value. In
fact, information technology, according to a number of writers, often
is
detrimental to profitability: computers raise costs, seemingly without
contributing to income.
It all started with Lester Thurow, then dean of MIT Sloan School of
Management. In May 1986 he gave a speech at the American Association
for
the Advancement of Science, showing that while the number of
blue-collar
workers in the US was reduced by 6% between the 1978 and 1985, total
output
rose 15%. Fewer people produced more--a growth in productivity
comparable
to Europe and Japan during the same period. At the same time, however,
the number of white-collar workers (including managers) grew 21%,
swallowing
the productivity growth in the blue-collar industry and making the
United
States less competitive (Thurow, 1986). This period of sagging
productivity
coincided with a period of high investments in office automation,
technologies
that intuitively should have increased, not decreased, productivity of
white-collar workers.
Stephen S. Roach, an economist of Morgan Stanley, found through an
elaborate
analysis of labor statistics that productivity1
in the US service sector had not increased since the late 1960s (Roach,
1987). Martin Neil Baily, an economist at the Brookings Institution,
showed
that the investments in technology in the white collar industries has
been
immense, particularly in banks (Baily & Gordon, 1988, p. 390) where
information technology has gone from representing 3.9% of capital
during
1970-79 to 34.1% as of 1987. For insurance carriers the figures are
7.2%
to 63.8%, respectively (see Exhibit 2). Much of
this
investment is in personal computers: The number of PCs used in Fortune
1000 companies rose from 2.5 million in 1983 to 18.4 million in 1985,
and
the percent of white-collar staff using them from 7% to 56% (Jeffery,
1991).
Paul A. Strassmann (1990, pp. 31-58) has shown that there is no
correlation
between financial return (as measured in profitability, sales per
employee
etc.) and the various measures used by the computer trade press for
technological
excellence (IT investments as a percentages of revenues, PCs per
employee,
etc.).
Books and articles like these, or rather the references to them in
business
journals, is causing difficult questions from CEOs to CIOs all over:
Are
they really getting any value out of having information systems--or
should
they maybe spend their money on something else instead--like
advertising?2
Unfortunately for the CIO, there are vast differences between what
economic
analysis and overall statistics tell us, and what is found when we look
at individual companies. The picture is far from clear, partly because
the data is lacking and faulty for large parts of the economy, but also
because the role of information technology is not well understood. In
this
note, I will try to bring some clarity to the picture by examining the
role of IT in providing business value on two steps: First, I define a
framework to discuss the role of IT in supporting different types of
tasks.
Within this framework, I try to show what effects use of IT can
produce,
and how these effects can provide business value. Second, I try to
assess
how successful the use of information technology been so far. Third, I
try to give a strategy for the plagued CIO: how to respond to the
challenges
posed by the debate over the value of information technology in
business.
A framework for investigating IT
To look closer at the role of information technology in work and its
effect
on business value, I will categorize tasks into one of four types.
These
types are derived by looking at the end results--the products--of a
task,
and the processes through which the results are achieved. The products
can be divided into physical goods and information
(following
Jonscher's (1983) division of the economy into a production and an
information
sector)3. The processes through which
products
are made can be divided into structured (that is, known and
repeatable
procedures) and unstructured (where either the process has to
be
reinvented each time or is not explicable or replicable by another
person).
These two dimensions give us the matrix which forms the basis for the
framework4
in Figure 1. More details are provided in Table 1.
PROCESS
Structured Unstructured
***********************************
* * *
Physical * Manu- * Design and *
goods * facturing * diagnosis *
* * *
* 1 * 2 *
PRODUCT ***********************************
* 3 * 4 *
* Back office/ * Knowledge *
Information * office * worker *
* factory * *
* * *
***********************************
The framework is imprecise in the sense that it is not readily apparent
in which quadrant a task falls: most work contains elements of all
these
categories5, the distinction between
physical
and information product may be dubious6,
and furthermore, the axes are continuous rather than dichotomic. Still,
using this rather crude categorization enables us to focus on the
effect
of information technology and on singular types of tasks, a more
precise
viewpoint than looking at computers in management, the service
industries
or productivity statistics. I believe information technology can be
used
to improve productivity in the traditional sense only in some of these
quadrants, either by increasing the capacity within the quadrant or by
creatively moving tasks, or portions of tasks, from one quadrant to
another.
This implies that the kinds of systems that improve performance in one
quadrant, as well as the measures used to gauge its success, might be
useless
or even counterproductive in other quadrants.
The role of IT in each quadrant
Quadrant 1: Manufacturing (physical product, structured process).
The first quadrant typifies the production and distribution of physical
goods, primarily industrial manufacturing, but it encompasses service
production
to the extent that production or delivery of a physical product is
important
to the business7. The typical image this
quadrant evokes is that of a worker standing by a machine, producing a
tangible product. The work is routinized and standardized, the routine
generally not designed by the person doing it, and is traditionally
only
changed through outside intervention. This is part of a long tradition
of productivity enhancing industrial engineering, beginning with
Frederick
Taylor's Scientific Management movement during the early decades of the
century, currently culminating in the Japanese methods of JIT
manufacturing
and linking to suppliers. There is little doubt about what the end
product
is and how it is measured: quantity is relatively directly observable,
quality measured against standards. Traditionally, the skill level
necessary
to perform a task in this quadrant is not very high, although there can
be significant differences in quantity and quality of output depending
on how skilled the person performing the task is.
In this quadrant, information technology can increase capacity by
improving
quality and quantity of products through faster, more reliable, more
precise
and more continuous operations. In- dustrial robots, for example, do
not
need coffee breaks, sanitary facilities and fringe benefits, and can be
put to use in dangerous or dirty environments where humans prefer not
to
work. Information technology, being electronic, is less prone to wear
than
mechanical devices--there is no need to grease a microprocessor. The
effects
of IT translates into business value through lower cost and increasing
flexibility in the production process.
Quadrant 2: Design and diagnosis (physical product, unstructured
process)
The second quadrant is the production (and repair) of physical products
where the production process is not routinized. There may be several
reasons
for this: The product may be unique in each instance, as for instance
the
building of a ship, an office block. It might require creativity or
knowledge
that is not readily explicable, as in art or industrial design. It
might
be that the product, though simple in itself, is new and that
routinized
procedures have yet to be implemented.
Although the products in this quadrant are complex, there is little
doubt about what they are. Quantity is readily observable, quality is
measured
by comparing to standards or to equivalent products from other sources.
Although errors in design and diagnosis often are traceable, there may
be considerable disagreement as to which inputs provide increases in
quality.
Although quality of output may be measurable, the value of increased
quality
may be difficult to measure: how much more secure should a car be, how
much should be spent on "hopeless" injuries or sicknesses, etc. Even
though
the production process is unstructured, there are often standards for
what
constitutes a good process and what does not.
Tasks in the second quadrant are often taught through
apprenticeship:
since the process of, say, blowing glass or taking out appendixes is
not
as easily conveyed verbally as it is shown. The student of these arts
learn
by watching experienced performers and copying their techniques through
a closely monitored process of trial and error. Apprenticeship time may
be long, often because the product is costly or dangerous and the
student
cannot proceed to more difficult levels of performance before mastering
the basic skills. The skill level necessary is high, often not only
because
of the dexterity necessary but because making decision on what to do is
part of the task.
Information technology's main effect in this quadrant is to increase
quality of the product by allowing experimentation, increasing
information
available for decision making, and shortening process time. A flight
simulator's
main advantage is that it allows trial and error without risk to life
and
property: through crashing many simulated planes the pilot-in-being
learns
how not to crash the real ones. And the experienced pilot may try out
hair-raising
new maneuvers without risking his or her pension. Information
technology-based
exploratory tools like computer tomography can guide a surgeon's knife
in real time.
This translates into business value by increasing the demand for the
product, because the product is of higher quality, or is designed or
processed
faster and more accurately than without the technology.
Quadrant 3: Back Office (information product, structured process)
The third quadrant--often referred to as the office factory or the back
office--is where routine information is handled in a standardized way.
This is the place we would expect to find the majority of white-collar
or service workers. Banking, insurance and much of the public sector
fall
mainly in this quadrant. A typical worker here is a bank clerk, a
cashier
at a supermarket, or an IRS officer. Most large corporations have a
sizeable
fraction of their employees in this quadrant, doing chores that support
the main business, such as updating customer and employee databases,
handling
orders and facilitating internal communication. Tasks in this quadrant
are well specified, quantity is measurable, although measuring
individuals
is often done by measuring activity rather than output. Quality
measurement
is done through accuracy or timeliness standards. The necessary skill
level
in this quadrant is often very low.
Increases in capacity in this quadrant is achieved by increasing the
number of operations performed per employee - much like in the first
quadrant.
Information technology may support this process through moving the
recording
of information out of specialized back office departments to where the
transaction takes place. POS (point of sale) systems, which registers
all
information about a sale right at the customer checkouts, is an example
of this. "Business process redesign"--a fashionable approach to
information
systems analysis that uses IT heavily--aims at vastly improving the
productivity
in this quadrant (Hammer, 1990).
The business value should come through record-keeping tasks needing
relatively fewer people than before, through allowing vast increases in
transaction volume, and in providing aggregated information to
decision-makers,
most of whom reside in the fourth quadrant.
Quadrant 4: Knowledge worker (information product, unstructured
process)
In the this quadrant, we find unstructured information work. This is
the
realm of the knowledge worker: "managers, executives and a
variety
of professionals ranging from scientists to lawyers to entertainers"
(Roach,
1991). Even though work here can have a surprisingly high routine
content
(Mintzberg, 1973), knowledge work is generally characterized by dealing
with problems that do not lend themselves easily to direct automation8.
Judgment and specific knowledge, either from specialized education or
relevant
experience, are important, and the problems encountered are mul-
tifaceted,
abstract and often varying. The quality of the product is more
important
than quantity, but contrary to the second quadrant, quality is not
readily
measurable, and the relative contribution of various inputs is a matter
of post fact judgment and open to interpretation and often controversy.
Since quality is so difficult to measure, quantity is often measured
instead.
The effect of IT in this quadrant should be to increase the
knowledge
workers capacity to process and communicate information. This comes
from
two sources: automation what can be automated in the knowledge worker's
job, freeing him or her to do what the computer cannot, and by
increasing
amount and quality of information available through technological
media.
Here we find the end users of DSSs and EISs, as well as personal
computers
and electronic communication services. The knowledge worker often
designs
the production process him- or herself, including the question of how
and
when to use information technology. This means that the frequency of
use
is often an important measure for the quality of the services IT
provides.
The automated parts of a knowledge workers job, such as word
processing
and spreadsheet calculations, are a much smaller part of the time at
work
than the time spent simply communicating with people. Extensive use of
electronic mail and conferencing systems thus should have a great
productivity
potential, especially if an organization is geographically dispersed.
Strassmann
(1990, pp. 357-359) argues that the largest potential is found in
electronic
communications, since 30-70% of an employee's time is spent in
face-to-face
communication, in addition to time spent in the telephone.
The business value provided should be products of higher quality and
quantity: primarily better and faster decisions.
Movements between quadrants: IT and the redefining of tasks
Information technology can facilitate the relocation of a job or a task
from one quadrant to another, and thereby increase its value to the
organization.
In general, the task can be moved either horizontally or vertically,
giving
four distinct movements, here termed North, South, East and West.
Moving West: Industrialization
Transfer of tasks from the second to the first quadrant is
classic
industrialization. Traditionally, when a task is industrialized, all or
most of the physical steps involved in it are identified, set up as
singular,
sequential processes, and then performed by machines to the extent that
machines can outperform humans. The rationale for industrialization has
usually been to increase capacity and thereby draw down unit costs. In
the process, products are standardized and simplified to better suit
manufacturing
needs. Information technology extends the scope of industrialization:
by
using information technology, more complex products can be produced in
an in- dustrialized manner. Flexible manufacturing can alleviates some
of the rigidity in the process, making shorter production profitable.
CAD/CAM
can be used both as a more efficient coor- dinator of production
machines
and as an effective tool to help the engineering and production
functions
of a manufacturing enterprise communicate.
Transfer of tasks from the fourth to the third quadrant is
the
industrialization of clerical work. This shift increases productivity
for
two reasons: the tasks, when automated, can in many cases be performed
by less trained (and presumably cheaper) personnel; and the tasks
become
more measurable, meaning that the effects of changes in procedure can
be
documented better. This process is similar to industrialization in many
respects. Unstructured processes are automated by reducing the process
to identifiable, replicable steps, and then redesigning the process so
it takes advantage of the speed and reliability of information
technology.
This constitutes an explication of the knowledge formerly
contained
in the minds and bodies of the people performing the tasks (Zuboff,
1988).
Explicating and standardizing tasks through specialization has been the
traditional way of increasing productivity: the most visible effect
being
"electronic sweatshops" (Garson, 1988); data entry departments in large
organizations, typically banks and insurance companies, where large
numbers
of employees with low education enter data into mainframes.
Moving East: Informating
Transfer of tasks from the first to the second quadrant happens
every time a manufacturing operation is moved or changed materially.
This
may be a temporary shake-down period, but it can significantly impact
operations.
Information technology can help during the transformation by simulating
the new environment and allowing workers to test and practice new
skills.
A firm that changes strategy from offering commodity products to
providing
a stream of distinctive ones will move manufacturing operations towards
the unstructured end of the spectrum more-or-less permanently. By
committing
to flexibility and continuous change, a firm forgoes some of the
comfort
of structured work. Productivity increases comes from driving down the
cost of change, usually enabling the firm to compete in smaller, more
profitable
segments. IT can be crucial both because it help the organization
switch
between configurations quickly and because it can "remember" the
precise
state of each configuration. In principle this is the same thing as the
automated features of certain luxury cars: each person driving the car
adjusts the seat, mirrors, etc. perfectly. The car has a small computer
that stores the settings, and reproduces them at the driver's command.
Transfer of tasks from the third to the fourth quadrant is
seen
in companies that use information technology to automate the routine
aspects
of clerical work, thereby orienting the job of the employee towards
things
that are less automatable, such as dealing with customers. Employees
shift
from specialization in one repetitive step of a complex task to
handling
all aspects of it. USAA corporation, a large insurance company based in
San Antonio, Texas, has used this approach to advantage: They use
imaging
technology and a job distribution system to banish paper from its
operations.
This frees up insurance clerks to communicate with customers, and
concentrate
on the judgement and relationship aspects of cases, rather than
spending
most of their time keeping the files in order (Harvey & Ryan, 1991;
Henkoff, 1991). A problem in this process is that the necessary skill
level
normally is higher in the fourth than in the third quadrant: although a
task may move, the worker performing it may not.
Moving North: embedding information
Transfer of tasks from the third to the first quadrant means
embedding
information in the physical product. One example of this might be bar
codes.
When a truck full of boxes is unloaded onto a conveyor belt, each box
passes
a bar code reader, which registers the box in a computer system. Clerks
checking packages at the loading dock are gone--the information they
recorded
is now embedded in the product itself. The process is repeated at a
supermarket:
A scanner reads the codes at the checkouts counter and enters it into
the
computer system. For the most part, the cashier does the physical
chores
the computer cannot do: putting the groceries in bags, physically
receiving
the payment, and making sure the customer does not run away with the
goods.
Transfer of tasks from the fourth to the second quadrant:
Although
it may seem counterintuitive, information technology can be used to
transfer,
at least in a limited sense, tasks from being manipulation of
information
to being handcraft. Some of the research being done under the heading virtual
reality asks people do things physically because the information is
not readily explicable in any other way9.
An example of this is an experimental system developed at the Tsukuba
university
in Japan, where a camera designer can put his hand into a "steel
glove",
which lets him "pick up" a camera from a screen. The "steel glove" not
only lets him "lift" the image of the camera on the screen, but also
lets
him feel the balance of the camera -- a feature not easily modelled in
a conventional CAD system.
Moving South: manipulating information rather than physical product
Transfer of tasks from the first to the third quadrant is
manipulating
information rather than physical product. JIT (Just-In-Time) is an
example
of this from the factory, EDI and other interorganizational systems
examples
from distribution. It is generally cheaper to move information than
physical
product: by increasing the quality of the information, the
transportation
of physical product can be delayed up to the point in time when it is
needed,
thus reducing the quantity of products and materials in the chain.
Information technology helps transfer tasks from the second to
the
fourth quadrant by substituting an electronic representation for a
physical product under design. Engineers, architects and designers who
once worked with drawings and physical models can now create designs
through
CAD or mathematical software. Computer-based drawings and 3-D models
not
only automate the step of actually making drawings and models, but
allow
designs to be tested electronically. Cars are now safety-tested by
computer
simulation rather than actual crashes. Electronic designs are more
readily
communicable than physical drawings and models, and may more easily
incorporate
or- ganization-wide standards, such as using common piece parts
wherever
possible.
Diagonal movements
Although most diagonal task shifts are indirect, we see some examples
of
"pure" cross-movements. These are predominantly from the first to the
fourth
quadrant. This is what Shoshana Zuboff, professor at the Harvard
Business
School, terms informating a task: using information technology
to
increase the richness of the job. (The term informating also applies to
transfers from the third to the fourth quadrant). She gives a vivid
example
of this in her acclaimed book In the Age of the Smart Machine
(1988),
describing how the knowledge of workers in a paper plant changed from
being
"within the body" to being systemic: instead of knowing from experience
how to set machines (by looking at and feeling the paper pulp) the
workers
monitored the whole process through a computer system. The productivity
increased when the workers, sometimes clandestinely, started
experimenting
with the system to increase the output10.
How are we doing: Evaluating the contribution of IT
Manufacturing: increased productivity, but how much is IT?
The availability of data for the industrial sector of the economy is
relatively
good in most countries. In the US, the Bureau of Labor Statistics (BLS)
collects data on employment, output and profitability. However, the
data
may be flawed. Overall industry statistics, starting with the venerable
SIC code, is fraught with possible measurement errors. For instance,
contrary
to common practice in most other countries, in the US a company is
classified
under one SIC code only, even though it may have large divisions in
several.
ITT, for instance, was for many years classified in the baking
industry.
Also, figures on how much capital is spent on IT run into definition
problems
as to what expenses may be considered to be IT-related and what is not.
For instance, since the capitalized value of a computer normally is
just
25% of the total expense (the rest being software development and
maintenance),
huge differences in IT spending are not captured by the available data.
The picture seems to be that although the manufacturing sector's
role
in the US economy is decreasing, productivity of blue-collar workers
has
increased steadily (Drucker, 1991; Thurow, 1986), causing the
industrial
share of the workforce to drop to 25% of the US total in 1990 (Roach,
1988).
The role of information technology in the increased productivity
remains
unclear, however: several studies (Berndt & Morrison, 1991;
Loveman,
1988) indicate that investments in information technology have little
or
no correlation with increased productivity or profitability in US
manufacturing
industries. Loveman's study of 250 US manufac- turing business units
did
find a small, but significant correlation between IT investments and
productivity
increases three years hence, indicating that it may take time before
the
investments pay off.
The MIT Commission on Industrial Productivity study (Berger, et al.,
1989) shows that US productivity has improved, but productivity in
other
countries has improved more. They propose that productivity improves
not
only by adding automation, but in how the automated features are taken
advantage of. There is evidence to suggest that US companies are
investing
in automated factories, but not changing the way production is
organized.
In particular, flexible manufacturing equipment is not exploited: the
machines
are used for producing a few products in high volumes rather than
taking
advantage of the new machines' ability to produce many different
products
with a very low switching cost (Jaikumar, 1986).
One of CAD/CAM's key benefits is its ability to facilitate
integration
between the design, production and marketing functions of an industrial
enterprise. The problem is often that it is relatively easy to have two
of these functions on good terms with each other, but very difficult to
have all three pull together--and more often than not, manufacturing
gets
low priority (Riggs, 1983). Proposed solutions for these problems have
been many--most of them not including information technology
explicitly,
but instead focusing on project management (such as having dedicated
projects
with high-powered individuals as managers) (Clark & Fujimoto,
1991),
using "overlapping" problem solving (Clark & Fujimoto, 1987), and
designing
for manufacturability (Dean & Susman, 1989).
The research available in this area indicate that there may be a
long
way to go before this potential is properly exploited. A study by Adler
(1988) shows that companies have not found CAD/CAM to be a competitive
advantage, mainly because they have failed to take organizational
issues
into consideration. Some success stories are available: Northrop, in
the
creation of the B2 Stealth Bomber, went directly from an electronic
description
of the system to manufacturing, skipping wind tunnel testing. Gleason
Manufacturing
uses CAD as a communication tool between design and manufacturing,
directly
feeding CAD drawings into manufacturing processes. And IBM, through its
Proprinter project, rendered an automated factory largely obsolete
because
a better design reduced the number of parts to the point where it was
faster
assembled manually (Berger, et al., 1989).
Using the framework, we could conclude that productivity
improvements
within the manufacturing quadrant have been well-mined when it comes to
increasing capacity within the quadrant. However, the external
environment
now values quality and flexibility in addition to low price. This
should
indicate that there is more productivity to be gained from transferring
tasks from the first to the third and fourth quadrant: move information
instead of physical product and exploit the specific knowledge gained
by
those close to the production process by giving them more decision
power.
Design and diagnosis: Quality at a price
In the design and diagnosis quadrant, the health care industry is the
one
that has got most attention because of sagging productivity. The
dramatically
rising health care costs, not only in the US, but in most developed
countries,
are partly attributable to the increased use of technology in
diagnosis,
treatment and research. Sophisticated technology has increased the
quality
of diagnosis and treatment available to patients, but at a very high
price.
In this case, there is little question that information technology has
increased the quality of the product: diseases and injuries that meant
a certain death not long ago can now be successfully treated, often
routinely.
The increased quality offered by the new technology carries some
problems,
however. One is the unclear pricing of increased quality: The new
technologies,
including information technology, now offers the ability to spend
enormous
amounts of money on marginally prolonging the life or increasing the
probability
of survival of a patient. The second is the unclear implications of how
increased patient care translates into business value: since hospitals
profit from using expensive technology, at least as long as public or
private
insurance is willing to pay for it, the use of technology becomes a
quality
measurement in itself. The tools, rather than the results, becomes the
criterion against which performance is measured.
The combination of available new tools, the use of tools as an
indication
of quality, and the impossibility of pricing human life, has meant that
the minimum acceptable investment level has risen dramatically for
hospitals.
A "normal" hospital has now become a "labor-intensive and
capital-intensive
monstrosity", because in this kind of work, capital is not a substitute
for labor (Drucker, 1991).
Within the framework, we may conclude that information technology
has
been successful in increasing quality, which again has increased
demand.
The problem seem to be that this increased demand has not translated
into
profitability in a way that shows up in productivity statistics. The
exception
may be cases where information technology has been able to move tasks
to
other quadrants: through industrialization or through electronic rather
than physical design representations.
Back office: the easy things are done
The back office is where information technology has been used the
longest,
the traditional business tasks of computers being clerical work like
payrolls
and billing. There are statistics available showing the use of
information
technology in the third and the fourth quadrant; the problem is often
that
it is difficult to separate the two. The industry-wide statistics do
not
match the conclusions of in-depth case stories of companies that were
pioneers
in exploiting information technology. James McKenney, professor of
Harvard
Business School, has studied the development of the bank transaction
and
airline reservation systems in Bank of America and American Airlines,
respectively.
In both these companies, information technology not only increased
productivity,
but enabled the businesses to grow and exploit tremendous economies of
scale (McKenney, 1991). The Bank of America became the largest bank in
the world and essentially eliminated clerical work in the 1960s through
its heavy investments in check and loan transaction systems. American
Airlines
realized returns on investment of over 500% on their reservation
systems
(Copeland & McKenney, 1988). Both these companies were
technological
leaders in their businesses, spending enormous amounts of money on
technology
that was at best promising at the time the decisions were taken.
Since the effect of information technology, like in the second
quadrant,
seem to be more to make things possible than to reduce costs,
productivity
statistics will be misleading. They will be misleading because they
measure
the wrong things, and because advantage held by investors in
information
technology is soon competed away. The story of automated teller
machines
show this: The output per hour in commercial banks grew at only .9% per
year from 1973 to 1979, compared to 2.3% per year from 1967 to 1973
(Baily,
1986). This apparent productivity decline is mainly due to a change in
what banks do: instead of focusing on increasing the volume of checks
processed
and loans made (which constituted the basis for measurement by the
BLS),
banks tried to become more profitable by offering expanded and tailored
services, such as ATM's. The investments in new services such as ATMs,
and in the people who maintained and expanded them, looked like
unnecessary
overhead in the productivity statistics. In reality, ATMs have become a
requirement for being in the consumer banking market.
The second important effect of information technology has been the
ability
to vastly expand scale and complexity of operations, since
record-keeping
is no longer a limit on operations. Without computers to coordinate and
keep track of passengers, maintenance and scheduling, New York would
probably
have had to build one or two new airports to handle the present traffic
(Penzias, 1991). Stock Exchanges around the world could not even be
close
to the transaction volumes they have today without computers. Financial
services of the scale and complexity they are today could not have been
available. These facts do not show up in productivity statistics,
however:
the reason being that we have a different world because of computers,
but
not necessarily a cheaper or more profitable one.
It has been argued that organizations, as a result of reductions in
the lower ranks, no longer have the traditional pyramidal
shape--instead
they are diamond-shaped, with the bulk of the employees in middle
management
or staff positions (Attewell & Rule, 1984). In terms of the
framework,
productivity increases in the third quadrant have been eaten up by the
fourth: the work on the third quadrant has shifted from doing the
transactions
to assisting the knowledge workers, mainly by input of more
information.
How these effects of information technology translate into business
value becomes a function of how well the information is used. May
Department
stores offers a good example: buying decisions are taken by top
management,
who knows by Monday morning how every product has sold compared to
budget
the week before (Pliner & Springer, 1990). This translates to
business
value because in retailing buying decisions are both extremely
important
and easy to centralize by computer.
Knowledge worker: a matter of personal learning
The fourth quadrant is where the bulk of the IT investments in the
1980s
were done, with PCs and new communication tools as the main investment
objects. At the same time, this is an area where each individual has a
relatively large say in how and when to use information technology,
coupled
with huge difficulties in measurement: both specification of what the
final
product is and determining its quality is often extremely difficult, if
not impossible.
There is little question that the ability for knowledge workers to
process
and communicate information has been vastly expanded because of
information
technology the last ten years. Portable telephones, fax, personal and
portable
computers have all meant that information can be sought faster and from
a wider range of sources than before. There is considerable doubt,
however,
about to what extent this has contributed to business value. Strassmann
(1990, pp. 117-120) argues that management is the real heavy user of
information
technology in most industries: "mission critical systems are few
and inexpensive as compared with costly management information
systems."
While a number of successful case stories are available11,
the overall picture is that of "staff infection" (Thurow, 1986).
Instead
of fulfil- ling the demand for information, computers instead create an
ever larger demand for data of dubious incremental value.
There are indications that many investments in IT are not
economically
motivated. Some organizational theorists have argued that organizations
make decisions based not on what is economically best, but what is
considered
good practice at the time (Meyer & Rowan, 1977). From this it can
be
argued that many IT investments are "me too"-investments, related more
to fad, fashion and available funds than crisp economic analysis. One
manufacturing
firm traced its IT spending over a decade and found that it was closely
correlated to what it called "spending appetite"--last years
profitability.
Since the use of information technology in many cases is a personal
decision for the knowledge worker, the impact on productivity often is,
too. Shelby Foote, historian, novelist and noted commentator of the TV
serial The Civil War, writes everything with an inkwell pen --
to
ensure that every sentence is thought out before it gets on paper and
that
there is no temptation to change anything once it is down there12.
On a smaller scale, this has been called the First Law of Word
Processing:
"Time saved in using a word processor is spent fiddling with layout and
fonts." While word processing and desktop publishing have made many
writers
more prolific, there are no indication that the quality of what is
written
is higher. Similarly, since information technology has produced a
tremendous
increase in the amount of readily available information, more
information
will be considered--with uncertain implications for decision quality.
It may be argued that a lax attitude to spending and profitability
of
the technology is necessary in a period of technology introduction:
since
many of the new technologies cannot provide business value until they
are
adopted by many users, adoption should be encouraged. The rapid
adoption
of PCs, for one thing, has had an effect of lacking interoperability13:
moving information between different kinds of computer systems has been
difficult and laborious. The result is a situation where IT is locally
efficient, but a lack of standards and planning results in "people
running
errands between machines" (Penzias, 1991).
Most executives are not terribly concerned about the productivity of
their white-collar workers (Erdmann, 1991), a finding consistent with
Lester
Thurow's attribution of the sagging white-collar productivity to an
incapacity
in the American managerial culture. According to Thurow, there can be
no
productivity gains until American managers shed some of their
entrenched
attitudes:
These [attitudes] have to do with power (American bosses
exist
to boss); style (a good boss should know everything and, in principle,
have the knowledge to make all decisions); institutions (most
middle-level
managers get paid based on the number of people who report to them);
peer
pressure (it is harder to fire those who directly work with you than
those
at a distance); and beliefs (if the system is based solely upon
individual
effort, there is no need for group motivation, voluntary cooperation,
or
teamwork). (Thurow, 1986)
In terms of the framework: IT may provide a beneficiary effect, as
illustrated
by numerous cases of "successful systems". However, the translation
into
business value is dubious, because we have not learned how to do this,
and because the main problems in doing it is organizational, not a
feature
of the technology.
IT and movement between quadrants: the loss of measurability
Although it is difficult to determine how much of the movement between
quadrants is due to information technology, at least we can say
something
about changes in content of jobs and who occupies them. The last 100
years
has seen a transformation of the economy of the US (as well as all
other
developed countrires) from agriculture via manufacturing to information
services (see exhibit 3). In the 70s and 80s, the main movements in
terms
of economical importance (rather than in numbers of employees), seem to
be
-
from the manufacturing quadrant into the back office and, to a certain
extent, into the design quadrant.
-
from the back office quadrant into the knowledge worker quadrant
-
to a certain extent, from the design quadrant to the knowledge worker
quadrant
Roach found that almost all new jobs created in the seventies and
eighties
were in the service industries, and of those, most of them were
"support"
jobs (as opposed to knowledge workers). From 1982 to 1988 the number of
"support" jobs has been reduced relative to knowledge workers, from
1.34
information support workers per knowledge worker to 1.2 in 1988 (1988).
Although the framework does not exactly fit these definitions, the
informating
movement towards the knowledge worker quadrant is obvious (although it
is unclear to what extent this is due to IT).
The movement from the design to the knowledge worker quadrant is
merely
a deduction from the fact that a lot more is done on electronic
representations
of reality than what is done with physical representations of
information.
The movement from manufacturing to design/diagnosis is due to the
quality
movement: since products are getting more complex, more knowledge is
required
by the individual worker.
There are other movements, of course, automation still being a key
reason
for introducing information technology into tasks. Pure automation of
existing
tasks, however, is no longer a very attractive alternative for IT
introduction:
most of what could be automated now is. Although there are many ways to
increase the efficiency of these automated solutions, I will hold that
it is unlikely to move many tasks over from the fourth to the third
quadrant.
Conclusions -- a CIO's strategy of defence
If you don't know where you are going,
computers will take you there faster
and more expensively.
Arno Penzias14
From what we have seen so far, what conclusions should a CIO draw,
and
what can he or she do about the situation? Possible measurement errors
aside, the discrepancies between what IT has promised and what it has
delivered
so far seems substantial.
The best strategy would probably be to acknowledge that, yes, there
is a discrepancy, but that there are good reasons for it. These reasons
are:
-
The difficulty in measuring the contribution of IT. Since
the quadrants
where measurement is most difficult is increasing in size and economic
importance, the contribution of IT gets lost, not because IT does not
produce
the effect it has been asked, but because the effect of IT does not
translate
into business value. This is partly due to the fact that use of IT
alone
is not a sustainable competitive advantage, making IT a necessity
instead
of an advantage.
-
Underestimating the time it takes before IT has an effect.
IT vendors,
and often IS departments, posit unrealistic expectation about
productivity
increases. Richard Nolan, professor at Harvard Business School, says
that
companies go through four distinct learning curves when acquiring new
information
technology. First, they become proficient in using the technology.
Second,
they use it to make existing tasks more efficient. Third, they start
thinking
about changing the way they work, given the new technology. Fourth,
they
use their understanding of the technology to gain a strategic
advantage.
The problem is that IT vendors sell information systems promising the
savings
and advantages of the fourth step, neglecting the long process needed
to
really make systems useful. Organizations expect results quickly,
usually
within two years. If the results are slow to come, the system may be
abandoned,
replaced by a new system touted by the IS vendor as the ultimate
solution.
And the process repeats itself (Nolan, 1986). James McKenney found that
truly strategic systems took at least 7 years from first initiative to
full implementation (McKenney, 1991). Standardization, open systems and
new development techniques like Object Oriented Programming should
help,
but there is still a long way to go before information technology is a
help rather than a hindrance in integrating systems.
-
Using IT as a panacea for organizational problems. Not only
has
IT vendors and enthusiasts promised quick results from IT, but they
have
promised solutions to all kinds of dysfunctional behavior to.
Installing
a new information system to create order out of chaos or to stop
conflicts
is what Chris Argyris calls structural solutions to behavioral
problems
(1990 pp. 75ff.). It is far easier for managers to implement a new
system
than to address the underlying problems, such as insufficient education
or a dysfunctional organizational culture.
The CIO should not despair, however--the current debate about
productivity
can be used to advantage. The situation can be mitigated by
-
Using contribution to business value as evaluation criterion.
Measures
of contribution to business value are both difficult to observe and
specify
in advance: often one does not quite know which effect a system will
have.
This does not mean that they should not be attempted: the problem lies
in the reliance on overly simplistic measures. The frequency of use,
for
instance, is a commonly used measure for success, at least in the
knowledge
worker quadrant. Used simplistically, this measure can be both
misleading
and open to manipulation15. Instead it
is important to find out who is using the system, what they are using
it
for, and how this affects the business value. In other words: it is
time
to think about the link between effects and value rather than between
IT
and the effects it produces.
-
Try to force the learning curve. This is simply nothing else
than
following the call to continuous innovation for tasks that
traditionally
have not been subject to productivity thinking. This is a matter of
personal
learning: As a consultant and as an IT user, I am constantly amazed how
few of the possibilities offered by personal computers and personal
communication
devices that are being exploited by knowledge workers: of course a lot
of the software available today is complicated to use and have to many
features. But at some point, people should be held responsible for not
shedding old ways of working, if it inhibits the effectiveness of
others.
-
Start taking responsibility for outcomes rather than
specifications.
This is both the most difficult action to take and the most important.
Since information technology is often regarded as a panacea, IS
personnel
has often, defensively, insisted on delivering services specified down
to the last detail. When things fail because of factors external to the
technology, the person responsible for the technology can point to the
specifications. Although this approach may seem smart from a personal
defensiveness
position, it does not do much for the business value of a company, or
the
possibility that the CIO ever will become the CEO.
This is a time when demand for results are higher than ever before and
the potential of information technology still largely untapped. The CIO
should be uniquely positioned to take on this challenge.
Appendices
Exhibit 1: Some characteristics of each quadrant
Quadrant |
1 |
2 |
3 |
4 |
Short name |
manufacturing |
design |
back office |
knowledge worker |
Product |
Physical |
Physical |
Information |
Information |
Process |
Structured |
Unstructured |
Structured |
Unstructured |
Productivity measures |
quantity, quality of output |
time in process, quality of design, successful final outcome |
quantity of tasks performed, accuracy, time in process |
quality of outcome |
Necessary skill level |
low to medium, fairly specialized |
high, specialized |
low to medium, fairly general |
high, both specialized and general |
Compensation level |
low to medium |
medium to high |
low |
medium to high |
Measurability of output |
high |
low in the short run |
medium |
low |
Measurability of activity |
high |
low to medium |
high |
medium to high |
Size and growth (Based on Roach (1988) and Drucker (1991)). |
substantial but declining |
small, stable |
large, stable after high growth |
substantial, growing |
Effect of IT |
Increasing capacity and flexibility |
Increasing quality of product |
Increasing detail capacity and information overview |
Increasing information availability and communication capacity |
Exhibit 2: Information technology investments, by
industry
Industry |
IT %
1960-69 |
IT %
1970-79 |
IT %
1987 |
Capital
1987
($mill.) |
IT
1987
($mill.) |
Manufacturing |
1.6% |
2.8% |
10.1% |
763.30 |
77.25 |
|
Nonmanufacturing |
4.4 |
6.7 |
16.2 |
2810.00 |
454.07 |
..Mining |
0.1 |
0.1 |
0.1 |
256.80 |
0.18 |
..Construction |
0.7 |
0.5 |
4.3 |
50.10 |
2.15 |
..Transportation |
0.5 |
0.6 |
1.1 |
254.34 |
2.88 |
....Rail |
0.5 |
0.7 |
0.5 |
96.18 |
0.50 |
....Nonrail |
0.7 |
0.5 |
1.5 |
158.16 |
2.38 |
......Air |
0.7 |
0.4 |
2.3 |
36.69 |
0.86 |
......Trucking |
0.5 |
0.1 |
0.4 |
48.20 |
0.17 |
......Other |
0.8 |
0.8 |
1.8 |
73.27 |
1.34 |
|
..Communications |
30.6 |
40.8 |
54.4 |
317.66 |
172.73 |
..Public utilities |
0.6 |
1.1 |
4.4 |
448.86 |
19.74 |
..Total trade |
0.9 |
2.5 |
12.8 |
413.48 |
52.82 |
....Retail |
0.5 |
1.1 |
3.8 |
237.59 |
9.02 |
....Wholesale |
1.8 |
4.9 |
24.9 |
175.89 |
43.80 |
|
..FIRE |
5.7 |
6.0 |
20.0 |
719.78 |
143.94 |
....Finance and insurance |
3.5 |
4.7 |
38.6 |
234.73 |
90.51 |
......Banks |
1.9 |
3.9 |
34.1 |
109.15 |
37.17 |
......Credit agencies |
3.1 |
3.3 |
26.5 |
68.61 |
18.19 |
......Securities |
3.9 |
8.3 |
58.7 |
6.61 |
3.88 |
......Insurance carriers |
4.4 |
7.2 |
63.8 |
47.24 |
30.12 |
......Insurance agents |
15.6 |
12.0 |
37.2 |
3.12 |
1.16 |
......Holding companies |
8.0 |
10.2 |
53.8 |
16.90 |
9.10 |
....Real estate |
6.1 |
6.3 |
9.5 |
468.15 |
44.32 |
|
..Services |
6.5 |
8.3 |
17.1 |
348.98 |
59.63 |
....Hotels |
0.1 |
0.2 |
2.2 |
61.34 |
1.36 |
....Personal |
9.3 |
13.6 |
13.8 |
13.00 |
1.79 |
....Business |
7.9 |
10.9 |
27.9 |
92.04 |
25.68 |
....Auto repair |
0.5 |
0.2 |
1.7 |
60.34 |
1.01 |
....Miscellaneous repair |
0.4 |
0.5 |
3.7 |
7.53 |
0.28 |
....Motion pictures |
15.0 |
31.5 |
47.0 |
6.32 |
2.97 |
....Amusement |
9.7 |
12.3 |
21.5 |
21.65 |
4.65 |
....Other |
12.2 |
13.3 |
26.8 |
81.76 |
21.89 |
......Health |
16.0 |
19.2 |
31.3 |
52.37 |
16.39 |
......Legal |
2.9 |
4.0 |
18.7 |
7.06 |
1.32 |
......Educational |
9.5 |
12.2 |
57.8 |
2.06 |
1.19 |
......Other |
10.0 |
6.6 |
14.7 |
20.27 |
2.98 |
Source: Baily & Gordon (1988)
Exhibit 3: U.S. Work Force Distribution
|
1880 |
1920 |
1955 |
1975 |
2000(est.) |
Agriculture & extractive |
50% |
28% |
14% |
4% |
2% |
Manufacturing, commerce, industry |
36 |
53 |
37 |
29 |
22 |
Other services |
12 |
10 |
20 |
17 |
10 |
Information, knowledge, education |
2 |
9 |
29 |
50 |
66 |
Source: Boettinger, 1984
Endnotes
-
Productivity means output (value, volume)
relative to
input (labor, capital). In general, productivity is productivity of
labor,
that is, output per person (or even more precise, output per
person/time
unit). Productivity of capital is the same as return on investment
(ROI)
over a given period.
-
Information technology is not the only potential
culprit
for the sagging productivity. Some even argue that information
technology
may well be the one thing keeping productivity up: that the lacking
productivity
is a result of external factors that counterbalance the productivity
gained
by use of information technology (Bowen, 1986). These "other things"
include
increases in government-related paperwork, changes in labor
requirements,
increasing danger of litigation which necessitate use of more lawyers,
and international competition. Lack of competition in the service
sector
has also been held up as a reason for lacking productivity growth
(Julius,
1992). And some economists are quietly beginning to suspect that the
whole
productivity slump of the 80s is just measurement error.
-
An alternative definition, could be concrete and
abstract:
concreteness in the sense that the product is identifiable and directly
comparable to others.
-
Alternative frameworks include the three (by
now, four)
economic stages: the agrarian, industrial, service and information
economy.
The problem with this framework is that although the preceding stages
do
not disappear, their importance in the economy diminishes, and to a
certain
extent their economic rationale changes (witness the large transfers of
resources from public to agricutlutre and traditional manufacturing in
developed countries. Strategic planning literature often focus on the
role
of IT in supporting layers in an organizational hierarchy (e.g.
strategic,
tactical and operational systems). While more operational from an
information
technology viewpoint, this framework presupposes a hierarchical
organizational
structure, traditionally determining which systems are which by which
organizational
level that uses them. An operational system (such as a POS system) may
very well provide a strategic advantage, making this framework less
useful.
-
As noted by Jonscher: a line worker (which is a
physical
production job) might spend time filling out a time card (which is an
information
task).
-
An alternative division, at least for physical
products,
is where the knowledge of the task resides: in the body (that is,
gained
through physical training) or in the head (that is, achieved through
systematic
education) of the person performing it (Zuboff, 1988).
-
"Hamburger flipping", most often considered a
service
task, belongs in this quadrant.
-
In fact, most of the work (in terms of time
etc.) may
be routine, but the tasks most important to the job is unstructured and
requires information processing.
-
At University of North Carolina Chapel Hill,
researchers
are using a robotic arm which gives tactile feedback to construct
models
of molecules. The idea is that the construction of molecules is so
complex
mathematically that it is easier to model the different forces in a
computer,
and then have the researcher try to manipulate a model, projected out
in
the room, and receive feedback on the feasibility of his constructions
via how hard it is to put the individual atoms in place.
-
Zuboff notes how, in the process, the
distinction between
manager and worker changed: the managers were the ones that previously
had the systemic knowledge of how the plant worked. When the workers
started
gaining systemic knowledge, many managers tried stopping this by
imposing
standard settings for each machine, even though the workers in many
cases
managed to increase the output of the factory by experimenting. It
could
be argued that this example is not "pure": no one asked or expected the
workers to start experimenting. Had it been done consciously, it would
have represented a "pure" diagonal move, not a movement via the third
quadrant.
Nothing in the example suggests it could not have been done
consciously:
as an example of an alternative use of IT it is still valid.
-
A well known example is the Phillips 66 oil
company,
which survived a 40% cut in its managerial personnel through use of an
Executive Information System (Applegate & Osborn, 1988).
-
As noted in interview in People, October 15,
1990,
pp. 60-62.
-
Interoperability: the extent to which
information systems
can exchange data directly. A good example of interoperability are word
processors like Word Perfect and Microsoft Word: these programs are
available
on a number of different kinds of computers, but they can exchange
files
directly.
-
From Keynote Address at the International
Conference
on Information Systems, New York, December 17, 1992. Arno Penzias is VP
of Research at AT&T Bell Laboratories, and a Nobel Laureate.
-
An example: An electronic mail system at an
educational
institution was used a lot, partly because top management endorsed it
and
demanded that communication to them should go through the system. The
frequency
of use went up dramatically, and the system became a communication
backbone
in the organization. As seen from the point of measurement: frequency
of
use went up because top management was involved, and since the use of
the
system by many people made it more valuable to all of them, this was
effective.
On the other hand, when the users of the IBM 438L expert system
used
by the Strategic Air Command in the 1960s turned out not to be used,
top
managment solved this by ordering personnel on duty to ask at least two
questions of the system on each shift. The number of questions asked
consequently
rose to twice the number of officers on duty (Earnest, 1990). In this
case,
frequency of use went up because of top management involvement, making
the system seem more successful.
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