Current and Future Uses of the Computer:
Industrial R&D in the United States
Alan L. Porter
School of Industrial & Systems Engineering
Frederick A. Rossini
Office of Interdisciplinary Programs and School of Social Science,
Georgia Institute of Technology, Atlanta GA 30332, USA.
Abstract
This study of 158 organizations sought to
depict current uses of computers in R&D. A
survey of senior R&D management by the
Industrial Research Institute identifies a number
of salient features. Routine computer use is
becoming a characteristic of scientists, engineers, and managers. Yet characteristics of
usage differ markedly by size of R&D unit and
by line of business. Moreover, patterns of
responses suggest on-going changes toward
the time when R&D will be strongly coloured
by the context of an integrated, intelligent
computer environment. This implies new roles
and skill requirements for R&D managers,
professionals, and support staff.
Keywords:
computer use, computer application, R&D,
scientists, engineers, managers, industrial,
future
The expanding capabilities of the computer
have prompted its application in almost
every work environment. One of the most
important and intriguing areas of application
is Research and Development. In this
domain, scientists and engineers create new
knowledge in their subject areas. In so doing,
they not only make use of stateof-theart
technology, but they also push those technological frontiers ever outward. Today,
computers constitute the technology doing
most to change the nature of how science
and engineering are done. In turn, the way
R&D uses computers and its demands for
future capabilities influence computer
developments disproportionately to its size
as a computer market.
Information on the use of computers in
R&D Management 16,4, 1986
R&D is surprisingly scarce. Computerized
search of a half-dozendatabases on this topic
turned up no systematic surveys and little
else (it missed the study by Morse et al.,
1984). However, we did piece together a
chronology of computer applications and
concerns in chemicaVbiochemicaVbiomedical research over the past twenty years
(includingone short-livedjournal, ‘Computers
in Chemical and Biochemical Research’):
1965 - ‘Biomedical computing, . . repre
sents one of the major contributions to
biomedical science in this century’ (Stacy
and Waxman, 1965). Chapters in this edited
volume emphasize analysis, along with early
efforts at modelling with the computer:
* Statistical packages in biomedical computation
* Computers in multiphasic screening
* Computational methods in protein structure analysis
* Computer analysis of the electrocardiogram
* A neural network model.
1972 - Computer applications in chemical
research are classified into passive (e.g., data
acquisition and processing, file searching,
and display) and active (e.g., automated
control, real-time computer interaction with
experiments, and computer-user interactive
experimentation). The keynote speaker at
this symposium points out that laboratory
computing systems have tended to be ‘highly
individual systems,’ and notes that ‘Some
users advocate the use of small dedicated
computers rather than large central computers’ (Powell, 1972).
1974 - Clinical applications have become
significant as ‘the laboratory workload about
doubles every five years’ (Toren et al., 1974).
279
ALAN L. PORTER AND FREDERICK A. ROSSIN1
280
Specific topics include automation of
laboratory test procedures, their analyses
(e.g., glucose determination), and data
reporting.
1978 - In the industrial setting, concerns
are raised about dependence of R&D on
data processing with its business oriented
systems, whereas R&D want ‘to have their
processes automated with dedicated computer systems. In an overall view, minicomputers appear to be a logical way out of
this compounded dilemma’ (Hornisch, 1978).
1983 - Another column on ‘Computer
Applications in Chemistry’ raises issues
qualitatively advanced from earlier concerns
(Heller and Potenzone, 1983):
Chemical inf rmation systems
A centralize computer system for the
acquisition d interpretation of analytical
data
Local area networks, fourth generation
languages and microelectronics in the
research lab
Computer-assisted structure elucidation
system
Application of pattern recognition methods
in chemistry
Computer-assisted drug design.
In sum, computer use in R&D is changing
on many dimensions. Not only is usage
becoming more pervasive, it is involving
different individuals, accomplishingdifferent
aims.
The Industrial Research Institute (IRI),
the consortium of industrial research directors, perceived the importance of computers
to modern R&D. They mailed a survey to
their member companies on August 24,1984,
concerning the state of the art in computer
application. We believe the results of that
survey give the most complete profile of
computers in R&D yet reported (Rossini and
Porter, 1985).
This paper synthesizes information from
that survey of computers in industrial R&D
in the United States. After describing the
survey, we consider (1) profiles of computer
application, and (2) for what those computers are being used now and will be used
in the future. We then offer observations on
what this portends.
s
THE SURVEY
IRI, through its Research on Research
Committee, administered a survey covering
over a hundred discrete aspects of computer
use. Completed surveys from 158 R&D
organizations reflect the computer use by
some 43,000 industrial scientists and engineers in the U.S. plus an equal number of
support personnel. Rossini and Porter (1985;
1986), with guidance from the Research
on Research Committee, analyzed the
responses and reported these to the IRI.
In a small number of cases, more than one
research unit responded for a given company.
These multiple responses represented R&D
units of diverse character (e.g., a central,
basic chemical laboratory and an applied
geosciences unit of an energy company).
Hence, we decided to include each survey
as a separate entity.
The preponderance of the items yielded
discrete responses (e.g., counts, percentages,
yes/no answers - c.f., Tables 1 and 2). Some
open-ended items allowed respondents to
list issues of concern. We consolidated
variations in responses to generate more
usable categorizations (c.f., Tables 3 and 4).
We first processed responses for the 158
R&D units taken together. We then explored
potential distinctions among the firms,
settling on two dimensions as particularly
important. Table 1 shows how selected
computer characteristics vary by size of the
R&D organization measured in terms of
number of professional employees. The
scaling was chosen on the basis of organizational function and the distribution of
responses. Table 2 breaks out these characteristics according to the line of business
involved. The authors and Michael R.
Waller, representing the IRI Research on
Research Committee, determined a set of
categories and placed each unit in the most
suitable one. (Standard Industrial Codes
were not employed because of the multifaceted nature of the business of many of
these firms and differences among units
within those firms.)
This survey of industrial R&D computerization yields valuable insights into current
operations and future needs. Nonetheless, it
should not be taken as precisely representative of all American industrial R&D. The
R&D Management 16.4.1986
Current and future uses of the computer
281
IRI membership is somewhat skewed toward
chemical and consumer products. These two
lines of business constitute just over half of
the respondents (Table 2). This accentuates
the utility of considering differences among
types of firms.
k
COMPUTERS IN R&D
Computers are used regularly (as opposed
to rarely or never) by 42 per cent of the
engineers and scientists encompassed in the
survey. That same figure describes the
number of interactive terminals in use per
professional employee (Table 2). Incidentally, or perhaps not, of the senior R&D
managers responding to the survey, 42 per
cent had terminals on their desks. We will
consider this ‘42 per cent’ computerization
again in our ‘Implications’section.
Setting aside that image of consistency,
the data also indicate substantial variation.
For instance, interactive terminals in use per
100 R&Dprofessionals (Table 2) range from
28 in Chemical laboratories (or an even
lower 21 in the ‘Other’ category) to a
resounding 82 per 100 professionals in energy
R&D operations. Figure 1 elaborates further.
This ‘box and whisker’ diagram presents
measures of central tendency and dispersion
for micros, minis, mainframes, and terminals.
The ‘x’ in the box shows the mean (42 per
cent for terminals) while the middle line
indicates the median (the 50th percentile 30 per cent in this case). In each instance the
mean is larger because the data are not
distributed evenly - the high values are
more extreme than the low values. The limits
of the boxes are the 25th and 75th percentiles; in other words, half the respondents
fit inside the box. Terminals per 100
professionals show a tremendous range: o n e
quarter of the organizations have on the
order of 1 terminal for 10 professionals and
one-quarter have more than 1 terminal for
each 2 (also shown in Table 1). Even more
striking, observe how distant the outliers
Table 1 Selected Computer Characteristics: Overall and by Size of R&D Organization
Overall
Percentile
Characteristics
25th
50th
By Size (Number of R&D Professionalsin Unit)
75th
Number of organizations
represented
21-50
51-100
101-200’201-400
400
26
34
39
26
32
Size (N of R&D professionals degree or equivalent)
% of R&D capital budget devoted
to cumputer hardware
65
148
345
2.4
7.5
17.4
8
8
14
13
17
Interactive terminals/ 100 R&D
professionals
13
30
56
32
36
35
46
64
0.2
0.7
1.5
2.3
1.2
1.2
0.7
0.5
NA
NA
NA
31
41
61
76
90
20
37
59
39
31
39
50
54
2
4.3
7.9
8.4
6
7
6.2
7.3
NA
NA
NA
46
41
62
65
78
Mainframe/ 100 R&D
professionals
% Planning major (over $25K)
software purchase within year
% of R&D Scientists & Engineers
using computers routinely
Computer support personnel/
1 0 0 R&D professionals
% with Local Area Network
in use
NOTE: Values ‘Overall‘ reflect those of the 158 R&D units which responded (usually virtually all did 80). The 50th
percentile is the median. The 25th-75th percentile range (the interquartile range) indicates the middle half of those
responding. Values ‘By Size’ are means for the respective groupings of R&D organizations.
Variables reported as #/lo0 R&D professionalsare computed by dividing the respective entity as reported for each
organization by the number of professionals in that R&D organization (degree or equivalent, not including technicians).
R&D Management 16,4, 1986
282
ALAN L. PORTER AND FREDERICK A. ROSSINI
are. Two companies reported 2 terminals
per professional, implying many in use by
support staff and/or a variety of dedicated
terminals with distinct functions.
R&D organization size relates to computer
use, but not in a uniform fashion. Both
capital budget for computers and local area
networks in use step up at about 100
professionals; both terminal density and
routine use of computers go up sharply at
200. In fact, highly significant linear relationships show up in the form of correlations
between the number of professional R&D
employees and these factors.
Is this an economy of scale operating? In
terms of major software purchases and
mainframes, such appears to be the case.
Software can ‘be used by proportionately
more people in a larger facility, reducing the
expense per user. A mainframe can likewise
serve many users. Proposed software purchases increase (as do actual purchases for
the past W o years, not shown), and mainframes per 100 professionals decrease sharply
with increasing size (Table 1). Interestingly,
the drop in mainframes per 100 professionals
is less than 1:l with increasing size and the
intensity of terminal use increases with size.
LEGEND
Outliers
O
O
108
100
I
O
Outer Fence
200 (2)
75th Percentile
182.1
25th Percentile
The scale to the outliers may
be discontinuous.
The ‘Outer Fence’ is a measure of
dispersion = 3 x (distance between
the 25th and 75th percentiles)
beyond the 75th (or 25th) percentile
77.8
76.9
NOTE:
I
*
72.8
50
4
x-
40
39.5
C
._
I
--
r
g
30
0
a
U
8
23.7
3
20
k.
P
X
L
7
18.8
18.3
18.0
-
4
5
z
10
i 3 6’4
0
Figure I
Ratio of Computers to R&D Professionals
R&D Management 16.4, 1986
Current andfuture uses of the computer
suggesting that larger laboratories are more
involved with mainframebased interactive
computing. Measures not tabulated in Table
1 elaborate on this differentiation in computer
use by organization size. For example,
responses to whether they have a ‘mainframe
with hardwired terminals and local network
to specified (or to all) minis/micros’ shows
the two smaller sizes of organization
averaging 36 per cent with such hardware,
but the three larger sizes (i.e., those over 100
professionals) averaging 89 per cent. Larger
organizations demonstrate the highest proportion of the more advanced architectures.
The percentage of computing done on an
interactive basis tracks this same sort of
pattern - here the breakpoint comes for
the smallest (50 or fewer professionals)
averaging 48 per cent interactive vs. the
larger R&D units, with all four sizes at about
70 per cent. This suggests a progression,
with the larger R&D organizations leading
in the adoption of interactive network
computing.
Other data support this interpretation.
While terminals per professional are more
prevalent and mainframes per professional
are less prevalent in larger R&D units,
micros and minis per professional do not
show significant deviations. This implies that
the increased use of computers by scientists
and engineers in the larger units reflects
more interactive computing.
Computer support personnel per 100
professionals vary dramatically across our
respondents. The ‘E operations in Table 2
- energy, engineering, electronics evidence markedly more support personnel
than the ‘C operations - chemicals and
consumer products. The overall distribution
(Table 1) shows a factor of 4 spread for the
interquartile range. In separate tabulations
per 100 R&D professionals, the median was
1 each for programmers, computer operators,
and other computer specialists (not shown).
More striking, at least a quarter of the
responding organizations reported ‘none’ for
each of the computer support personnel
categories. At the other extreme, a handful
of organizations were in double figures on
each (presumably engaged in computerrelated R&D). The variability in computer
support personnel suggests great diversity in
how the respondents deal with their comR&D Management 16,4, 1986
283
puting needs.
Levels of computer support personnel,
though highly variable, do not vary systematically by organization size (Table 1). We
probed the patterns for programmers,
operators, and other computer specialists
taken separately. Only one difference stood
out as statistically significant, and it appears
interpretable along the lines just developed.
The concentration of computer operators is
high by a factor of 2-3 for the smallest size
labs, those with the highest concentration of
mainframes and batch operations.
Another issue is whether .the computer
substitutes for R&D support personnel in
general (not just computer support personnel). We correlated totdprofessional employment in R&D with computer usage and
found no correlation ( r = .01). We see no
evidence of computers saving labour.
A policy issue of considerable relevance
to the computer industry concerns who
decides on purchases. In almost half the
cases (45 per cent), the individual researcher
determines the piece of hardware to be
purchased. But the issue gets complicated
48 per cent of the R&D organizations have
rules restricting the choice of hardware to a
specific manufacturer. Concerning microcomputers explicitly, 59 per cent of the firms
have some policies in place. The most
common element in such policies (90 per
cent) is approval of hardware selection,
followed by restrictions on approval or
support of communications (68 per cent)
and software (62 per cent). Authority over
computer purchases is shared by corporate
officials, R&D managers, and individual
researchers. At one pole, R&D must mesh
its needs with those of the company in
general. At the other pole, R&D management balances its concerns for coordination
against individual scientist/engineer hardware and software preferences.
Shifting attention to Table 2, the ordering
from the ‘C‘ industries to the ‘E’ industries
reflects increasing general emphasis on the
use of computers. Budget, terminals, software purchases, and routine usage share this
pattern.
Within the ‘Fs,’
emphases vary. The
electro-mechanicallelectronics Organizations
show the greatest proportion of their
scientists and engineers using computers
284
ALAN L. PORTER AND FREDERlCK A. ROSSINI
Table 2 Selected Computer Characteristics by L i e of Business
Characteristic
Metal
Engy
Engr
dlec
53
16
11
27
11
5
287
157
492
286
358
53
Total
Chem
Cons
Number of organizations represented
158
35
Size (N of RBD professionals-degreed
or equivalent)
272
227
% of R&D capital budget devoted to
computer hardware
Interactive terminals/ 100 R&D professionals
Mainframes/100 RBD professionals
Other
12
5
9
13
13
19
28
6
42
28
36
46
82
52
63
21
1.2
1
0.9
1.5
1.5
1
0.6
5.2
60
46
56
50
64
81
91
40
% Planning major (over S25K) software
purchase within year
% of MID Scientists & Engineem using
computers routinely
Computer support personnel/ 100 RBD professiorials
42
37
39
41
45
48
6.9
3.4
5.1
6.6
8.6
11.1
65
14.8
8.4
59
60
64
4 4 6 4
52
64
60
96 with Local Area Network in use
28
NOTE: Organizationscategorid under the guidance of the Industrial Research Institute’s Research on Research
Committee as:
Chem = Chemicals
Cons = Consumer Products
Metal = Metals
Engy = Energy
Engr = Engineering (mostly mechanical)
Elec = Electro-mechanical/Electronics
Other = Other (includes forast products)
Values are means.
Variables reported as #/ 100 R%D professionalsare computed by dividing the respective entity as reported for each
organization by the number of profubsionetsIn that organization (degread or equivalent, not including technicians).
routinely. Relatively few mainframes and
many terminals, along with the most micros
per professional (mean of 34 per 100
compared to 20 per 100 for engineering and
10 per 100 for energy) suggest highly
decentralized computing in operation in
these firms. The relatively larger energy
R&D laboratories are more heavily into
interactive computing linked to mainframes.
within a firm? Such concerns, expressed in
various guises, pose the great current
challenge for industrial computerization. We
consider an approach to the integration issue
in the ‘Implications’ section.
APPLICATIONS: PRESENT AND FUTURE
Their number of terminals greatly exceeds
To this point we have focussed on computer
the number of regular professional users of
computers.
Local area networks are in use in about 60
per cent of these R&D organizations, with
relatively little variation by line of business.
This, in conjunction with the other computerization features noted, suggests hardware
coming into place for a potentially ‘on-line’
professional staff. Shared databases, integrated software, electronic communications,
and so on loom as emerging issues. How can
one best tie together information within
R&D? Beyond that, how can one effectively
link across all the technical enterprises (e.g.,
R&D. engineering, and manufacturing)
capabilities in industrial R&D; now we direct
attention to their uses. Table 3 summarizes
what the senior research managers consider
to be the most important current and coming
applications. The list is ordered in terms of
current mentions as ‘the three most important application areas of R&D computer
usage, excluding administrative and accounting functions.’ Four dominate, being noted
by about half or more of the managers:
statistics, laboratory automation, database
handling, and modelling. A second tier might
be taken as professional support functions:
professional support and calculation; CAD/
CAE and graphics.
R t D Management 16,4, 1986
Current and future uses of the computer
285
Table 3 Current Uses of Computers in Industrial R&D
Category
Statistical Analysis of Data
Laboratory Automation/Data Gathering/ Process Contr.ol
Data Barn Management, Storage, and Retrieval
Modelling and Simulation
Scientific and Engineering Calculations
CADlCAMlCAE
Professional Support
Graphics
Communications
Software Development and Engineering
Artificial Intelligence/Expert Systems
Hardware Development/Supercomputers/etc.
Robotics
Current
Uses
%
Future
Uses
%
71.52
65.82
53.80
48.73
28.48
19.62
17.72
14.56
6.96
5.06
1.90
24.68
53.16
36.08
39.24
16.46
22.15
20.89
12.03
20.25
5.06
25.95
3.80
3.16
0.00
0.00
% Future/
%Current
0.35
0.81
0.67
0.81
0.58
1.13
1.18
0.83
2.91
1.00
13.67
infin
infin
NOTE: % reflects the number of times item mentioned, divided by 158 R&D organizations surveyed.
Looking to the future (unspecifiedhorizon),
columns 2 and 3 provide complementary
perspectives. Column 2 suggests a broadening of computer functions in R&D areas.
Column 3 points to a relative explosion in
AI/expert systems use and communications
developments.
What do these future perceptions mean?
An application can be perceived as having
future importance, even though it is currently
only beginning to be developed. As initial
applications commence, prospective users
can see more uses and developers can
augment capabilities in those directions. As
the application matures, further improvements become incremental, and the area
may recede into the background consciousness of ‘routine’ activity. This sort of
perception seems to explain the ebbs and
flows of Table 3. Maturing, routine applications (e.g., statistical analyses, database
management, scientifidengineering calculation) fade in the listing of Future Uses.
(That does not mean they will not actually
account for major portions of computer use,
just that they are taken for granted.) Other
applications currently in use promise s u b
stantial future development (e.g., lab automation, modelling, CAD/CAE, graphics).
Most intriguing are the application areas not currently substantial, but nonetheless
perceived as important for the future (e.g.
communications and, especially, AI). On the
other hand, we were somewhat surprised at
R 1 D Management 16,4, 1986
the lack of interest in supercomputers and
robotics.
The two targets for massive future
expansion in R&D use, communications and
AI, certainly make sense. Expanded communication uses fit with our perception of
considerable interactive capability in place.
Moreover, while this survey presents data
from a single point in time, our sense is that
rapid build-up is taking place. Enhanced
communication also fits with our view that
serious integration of databases, analyses,
and needs - including R&D and all other
technical units of the firm - is rapidly
becoming highest priority. Expert systems
appear to be on the very brink of successful
applications in many domains. R&D offers
special promise in the coming together of
specialized knowledge, repetitive operations,
and strenuous analyses.
This report has emphasized scientific and
engineering applications. The survey also
addressed managerial uses of computers.
Most mentioned were budgeting uses (49
per cent of the units), followed by project/
programme management, communications,
and report preparation/graphics (each noted
by 27 per cent of the respondents). The
management computer use profile emphasizes relatively mature applications. Communications, however, appear to be the
exception, the area with great potential for
change. Managerial communication uses
would appear to complement scientific/
286
ALAN L. PORTER AND FREDERICK A. ROSSINI
engineering communications, and provide a
vital bridge to corporate integration efforts.
Table 4 tallies what R&Dmanagers see as
‘the three most burning issues with respect
to computing in R&D - for scientific
applications.’ Justification and control issues
predominate. Interestingly, over 98 per cent
of our respondents believed that computer
systems have been of value in research
operations. More striking than this ‘motherhood and apple pie’ response, half of the
organizations had conducted some form of
study to ascertain that value.
Several of the other hot items fit our sense
of increasing focus on integration: networkinglcommunications, documentation/
standardization of software, and R&D
databases, in particular. Note that other than
modest concerns with availability of computing capacity and centralized vs. distributed
processing, no hardware issue makes the
list. Neither does computing power seem to
be a priority issue.
Respondents were asked to generate
another classification of burning issues
concerning managerial uses of computers.
Justification and control concerns were an
overwhelminf:No. 1, followed by networking/
communications as No. 2 (same priority as
for the scientific issues). Training nudged up
to No. 3, followed by Security, No. 4, and
Documentatiodstandadaation as No. 5.
Software development did not make the list
for managerial applications (consistent with
Table 4
our earlier comment that managerial uses of
computers seem relatively mature).
Speaking of software, we also asked who
generated their own. Half of these organizations generate more than half of their
own application software. In the majority of
cases, the author of any such software is
responsible for documentation and maintenance. Training in software use, applications
packages, and programming is provided inhouse by a majority of these American R&D
organizations. About a third provide training
through outside contractors on various
topics. R&D is self-sufficient when it comes
to its software. That is consistent with the
model of the fiercely independent scientist,
but not with the well-integrated system. One
might speculate that the trend will be toward
use of more coordinated packages with
organized maintenance programmes.
IMPLICATIONS
The ‘bottom line’ to any study of computer
usage is to anticipate what is to come. A
severe handicap must be overcome in
seeking this information from the present
results - the survey reflects a single point in
time. To surmount this difficulty, we have
tried multiple approaches. First, the survey
tallies anticipated future uses and concerns.
Comparison of the present and future
applications suggests dramatic increases in
Burning lasue in Scientific Use of Computers in Industrial R&D
ISSM
Justificationf Cspkal/Control/Policy
Networking/Communieations
Documentation/Standardizationof Software
Training/Underutilizstkn of Computers
Software Development/Expanslon/lmprovemnt
Security
R&D Databases
Availability of Computing Capacity
Centralized vs. Datributed Processing
Over-relianceon Computers
Internal vs. Purchased Software
96
24.7
19.6
17.7
17.1
15.8
8.9
8.2
7.6
7.6
7.6
4.4
NOTE: Respondentswere aaked to nominate the three most burning issues
with respect to scientific use of computing in RBD. We compiled responses
to produce this ordering. % reflects the number of nominationsdivided by
158 R&D organizationssurveyed.
R&D Management 16,4, 1986
Current andfuture uses of the computer
287
communicating, integrated systems, and in personnel taken one year earlier (Morse et
use of A1 capabilities.
al., 1984). The European study also crossed
A second approach is premised on a industrial sectors, although 77 per cent of
general innovation model. The commercial- the responding organizations were governization of many technologies follows the ment departments or government owned
pattern of a logistic curve (the ‘S-shaped’ establishments. It, too, spanned different
growth curve). If we assume the temporal sizes of R&D unit, althopgh smaller on
dynamics of computerization of R&D will average - 37.5 per cent of their organizations
hold to this pattern, we then need to locate that denoted size had 50 or fewer qualified
the present state of computerization along scientists and engineers (QSEs) compared to
this curve. Ths most suggestive. data on our 16.5 per cent; only 21.6 per cent of their
penetration of computers into R&D cluster units exceeded 250 compared to our 33.1
at 42 per cent (i.e., per cent of scientists and per cent over that many professionals.
engineers using computers routinely, ratio
As a generalization, the present findings
of terminals to professionals, and per cent of seem to represent the step forward anticipated
senior managers with terminals). The logistic by Morse et al. T o what extent the
curve has an ordinate range from 0 to 100 differences represent a US lead over the UK
per cent. It begins slowly, then commences and/or the one year time difference is
an exponential increase to an inflection point uncertain. Nevertheless, the two studies
at 50 per cent, from which growth slows taken together point toward continued
toward the 100 per cent saturation value. At computerization of R&D:
42 per cent, or thereabouts, R&D computer1) The UK study found an average of 1
ization is undergoing its most rapid rate of micro for 8 Q S h , and it anticipated ‘in five
change. Unfortunately, in the absence of years’ time there will be fewer than 3 QSEs/
another data point in time, it is not possible micro.’ Our study finds 1 micro for 6 QSEs,
to predict when the curve will reach various but when combined with the separate
degrees of penetration.
category of ‘intelligent terminals’ (1 per 5
Third, we can extract a sense of ongoing QSEs, not shown in the tables), the net is
change from the survey differences among slightly fewer than 3 QSEs per micro. (One
organizations. Both Tables 1 and 2 yield interesting contrast deserves mention - in
interpretable patterns of leaders and lagers. the UK, chemical industries, along with
The large research organizations show electronics and engineering, are leaders in
substantially higher usage rates by pro- adoption of micros; in the US, electronics
fessionals and greater development of inter- and engineering lead in computerization, but
active computer capabilities. The ‘E indus- chemicals lag far behind - Table 2.)
tries, likewise, lead the ‘C‘ industries in
2) The UK respondents indicated growing
adoption of the computer into the daily life popularity of information handling applio
of the scientist and engineer. This suggests ations, including ‘using the microcomputer
that the laggards will follow in the footsteps as an intelligent terminal with access to a
of the leaders toward everincreasing reliance wider network of information.’ Some 49 per
on computers, in particular, interactive cent reported any form of interconnections
computing. It also suggests that a variety of among their computers, of whom only 2 per
different computer configurations will co- cent denoted a local area network (LAN)
exist at any given time.
per se. Again, the US respondents verify the
As a fourth source of information, we can change vector - 59 per cent reported LANs
reflect back on the literature scanned on the in use.
introduction of computers into chemical and
3) Uses seem to track the same develop
related research areas. While not quantit- ment profile. UK users emphasize manageative, this affirms a sense of change toward ment and experimentation, followed by
more extensive and sophisticated use of calculation, information handling, and modelcomputers. The hypothesis that computer ling. The US users were queried separately
use is static is untenable.
about administrative and technical uses.
Fourth, the present findings do compare Combining responses, one s e a management
directly with those of a sample of UK R&D uses (budget and project), calculations,
Rc%DManagement 16,4, 1986
288
experimental control, modelling, and information handling. The UK respondents perceive potential for graphical forms; the use
of CAD/CAM/CAE$ professional support,
and graphics packages shows significantly in
the US sampie (Table 3). While ‘few [UK]
respondents could envisage any impact of
application using the possibilities of artificial
intelligence,’ Morse et al. do anticipate ‘the
revolutionary technologies of knowledge
engineering and artificial intelligence will
enter the laboratory.’ Again, the US
respondents seem to bespeak the next stage
- no significant application yet, but growing
awareness of the potential (Table 4).
Taken together, these indicators point
toward computer use becoming increasingly
routine for researchers. The survey results
further point to software changes as more
vital than hardware. The hardware emphases
include networks and interactive capabilities, not more powerful processing. Above
all, two features of particular importance
emerge: integration and intelligence.
In the past, computer use in R&D has
been marked by independence. Individuals
adopted machines and wrote their own
programmes. Today, scientists and engineers
feel more constraints from coherent corporate policies and take advantage of off-theshelf software, although not in a wellcoordinated fashion. In the future, anticipate
increased demand by management, and by
professionals, h r integration. Interactive
computing promotes coordination of hardware and software. Integration within R&D
and eventually across all technical organizations within the company will be pushed.
Networks are largely in place and survey
respondents placed a high priority on
computer communications. Engineers elsewhere are voicing concerns about needs to
integrate the design process. Ways must be
found- to share databases, use common
analyses from development through production, and manage information throughout
engineering processes. The islands of
computerization must be joined to form
effective systems.
The complementary emphasis lies in
intelligence. Expert systems and other A1
type capabilities have much to offer in the
eyes of American R&D managers. The bases
for such anticipation are the progressive
ALAN L. PORTER AND FREDERlCK A. ROSSINI
sophistication of computer applications in
the laboratory plus the broad perception of
A1 being poised to deliver. Note that the
anticipation is not based on present ‘intelligent’ applications per se. It could therefore
be overly optimistic.
This all adds up to the suggestion that
computerization of R&D is moving on to a
new phase wherein research and development will be conducted in an integrated,
intelligent computer environment. In the
1960s the computer was a tool to aid in
performing the same old research processes
a little faster. It has now moved on to
become an integral part of the researcher’s
professional life. It is a tool providing
capabilities that otherwise would not exist.
In the future, it will be the system. The R&D
professional will be embedded in a fully
computerized environment. That means new
ways to perform research, new roles and
skill requirements for professionals and
support staff, and new organizational structures. It means new opportunities for
providers of computer hardware and software, but in a changed environment. There
will be less of a role for the stand-alone
programme, machine, or supplier. Laboratory automation, data handling, advanced
analytical routines, and various intelligent
adjuncts to the R&D process will all have to
attend to ‘the system.’ R&D managers and
professionals are entering a new era of
research in the Information Age.
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