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Af/xi flL 



press 

REVIEW 


The following articles are reprinted solely as items of interest for the independent evaluation by members of 
ATSU. The opinions, statements of fact, and conclusions expressed herein are not those of the Association. 


AN EXCERPT FROM .... 

All About Time-Sharing and 
Remote Computing Services 


Surveying the Users 


To evaluate the current level of user satisfaction with 
specific vendors of remote computing services and with 
remote computing techniques in general, Datapro 
Research Corporation, in conjunction with the Associa¬ 
tion of Time-Sharing Users, Inc. (ATSU), designed and 
conducted an extensive user survey. Reader survey forms 
on Remote Computing Services were mailed to our 
subscribers with the February 1976 supplement to 
DATAPRO 70, and were also included in ATSU’s 
February Newsletter to its members and associates. (For 
more details on ATSU, please address all inquiries to the 
association’s headquarters address: 210 Fifth Avenue, 
New York, NY 10010.) 


Qualified responses were received from 475 users of 
remote computing services in the United States and 
Canada. Many users commented upon their experiences 
with two or more vendors and services. The average 
number of companies mentioned was 1.56, reflecting a 
slight downward trend in the use of multiple vendors’ 
services relative to last year’s reported average of 1.74. 


The individual user ratings earned by the 25 remote 
computing companies that were rated by 5 or more users 
are summarized in the accompanying Users’ Ratings 
tables. 

A “Weighted Average of All Ratings” was calculated for 
each company by assigning a value of 4 to each user rating 
of Excellent, 3 to Good, 2 to Fair, and 1 to Poor. Among 
the 15 companies whose services were rated by 10 or 
more users, the highest average ratings were earned by: 

Company Overall Rating No. of Users 


Scientific Time Sharing Corp. 

3.33 

17 

On-Line Systems 

3.21 

12 

The Service Bureau Co. 

3.07 

80 

Cyphernetics 

3.05 

31 


Highly regarded companies with fewer than 10 user 
responses included: 


Company Overall Rating No. of Users 


It should be noted that the DATAPRO 70 subscribers and 
ATSU members who responded to our survey may not 
necessarily constitute a completely representative sample 
of “typical” remote computing users. Furthermore, the 
small sample sizes for some of the listed companies may 
make it unwise to draw firm conclusions about relative 
company performance from the indicated ratings. 
However, Datapro believes the survey results that follow 
can be of considerable value to users, prospective users, 
and vendors of the commercial remote computing 
services, provided the preceding caveats are kept in mind. 



Responding users were asked to rate each remote 
computing service they had used or were using by 
assigning a rating of Excellent, Good, Fair, or Poor to 
overall satisfaction, cost effectiveness, quality and 
availability of technical support, quality of sales personnel, 
training effectiveness, ease of use, manuals and documen¬ 
tation, applications packages, languages and compilers, 
reliability, and response time. 


Interactive Sciences Corp. 3.36 5 

University Computing Co. 3.30 9 

Standard Information Systems 3.25 6 

First Data Corp. 3.18 6 


The ratings assigned by all of the responding users can be 
combined to form the following overall picture of user 
satisfaction with the current remote computing services: 

Excellent Good Fair Poor 


Overall satisfaction 

26% 

56% 

17% 

3% 

Cost-effectiveness 

18% 

41% 

29% 

11% 

Technical support quality 

31% 

45% 

20% 

4% 

Technical support availability 

26% 

41% 

25% 

7% 

Sales personnel quality 

26% 

48% 

19% 

7% 

Training effectiveness 

14% 

50% 

27% 

9% 

Ease of use for experienced 

45% 

46% 

8% 

1% 

DP people 





Ease of use for inexperienced 

18% 

46% 

28% 

8% 


or non-DP people 












USERS' RATINGS OF REMOTE COMPUTING SERVICES (Continued) 


Company* 


APL Series, Inc. 

Boeing Computer Services, Inc. 
Compu-Serv Network, Inc. 

Computer Sciences Corp. 

Comshare, Inc. 

Control Data Corp. 

Cyphernetics 
Data Resources, Inc. 

First Data 

General Electric Co. 

Honeywell Information Systems 
Interactive Data Corp. 

Interactive Sciences Corp. 
McDonnell Douglas Automation Co. 
National CSS, Inc. 

On-Line Systems 
Rapidata, Inc. 

Remote Computing Corp. 

Scientific Time Sharing Corp. 

The Service Bureau Co. 

Standard Information Systems 
Time Sharing Resources, Inc. 
Tymshare, Inc. 

United Computing Systems, Inc. 
University Computing Co. 

All others 


No. of 
User 
Replies 


7 

19 

24 

40 

23 

21 

31 

5 

6 

134 

7 

6 

5 

13 

36 

12 

15 

5 
17 
80 

6 
5 

46 

23 

9 

131 


Weighted 
Average 
of All 
Ratings** 


2.73 

2.75 

3.04 

3.02 

2.85 

2.92 

3.05 

2.55 

3.18 

3.00 

3.13 

2.75 

3.36 

2.88 

2.92 

3.21 

2.70 

2.83 

3.33 

3.07 

3.25 

3.16 

2.96 

3.01 

3.30 

2.85 












Users' Ratings* 

* 







Languages 

and 

Compilers 

Application 

Packages 

Manuals 

and 

Documen¬ 

tation 

Availability 

of 

Technical 

Support 

Quality 

of 

Technical 

Support 

c 

P( 

iuali 

of 

Sale 

irsor 

ity 

is 

inel 


E 

G 

F 

P 

E 

G 

F 

P 

E 

G 

F 

P 

E 

G 

F 

P 

E 

G 

F 

P 

E 

G 

F 

P 

3 

3 

1 

0 

1 

1 

4 

0 

0 

4 

2 

0 

1 

2 

3 

1 

3 

3 

1 

0 

2 

3 

2 

0 

9 

5 

3 

1 

4 

7 

5 

1 

2 

12 

5 

0 

5 

9 

4 

1 

5 

9 

5 

0 

3 

12 

4 

0 

8 

14 

2 

0 

4 

13 

4 

0 

4 

14 

5 

0 

8 

11 

2 

1 

10 

8 

5 

0 

4 

15 

3 

1 

16 

21 

3 

0 

8 

19 

8 

1 

10 

14 

15 

1 

9 

18 

12 

1 

13 

19 

7 

1 

8 

24 

7 

1 

4 

15 

2 

0 

3 

11 

5 

1 

7 

12 

3 

1 

4 

10 

4 

5 

4 

12 

5 

2 

4 

14 

4 

0 

7 

11 

1 

0 

6 

9 

2 

1 

3 

14 

4 

0 

2 

6 

12 

1 

3 

13 

5 

0 

4 

14 

1 

2 

5 

19 

5 

0 

8 

14 

8 

0 

14 

12 

5 

0 

12 

11 

8 

0 

11 

13 

7 

0 

9 

22 

0 

0 

0 

2 

3 

0 

0 

4 

1 

0 

0 

2 

3 

0 

0 

3 

1 

1 

2 

2 

0 

1 

2 

2 

0 

1 

2 

3 

0 

0 

2 

1 

3 

0 

0 

2 

3 

0 

3 

2 

1 

0 

2 

3 

0 

1 

2 

4 

0 

0 

51 

65 

8 

0 

20 

73 

29 

2 

35 

71 

21 

5 

32 

53 

34 

8 

27 

60 

37 

5 

21 

61 

33 

17 

4 

2 

1 

0 

2 

2 

3 

0 

1 

3 

2 

1 

4 

2 

0 

0 

4 

2 

0 

0 

2 

2 

0 

1 

1 

3 

2 

0 

1 

2 

1 

1 

0 

2 

4 

0 

1 

3 

2 

0 

3 

1 

2 

0 

3 

0 

2 

1 

3 

2 

0 

0 

1 

3 

0 

0 

0 

4 

1 

0 

2 

3 

0 

0 

4 

1 

0 

0 

0 

5 

0 

0 

7 

3 

2 

0 

4 

5 

2 

1 

5 

3 

4 

1 

2 

5 

3 

3 

2 

7 

3 

1 

5 

2 

4 

2 

14 

16 

1 

3 

12 

15 

6 

1 

11 

17 

7 

0 

8 

13 

13 

2 

12 

18 

5 

1 

7 

21 

4 

4 

7 

3 

2 

0 

6 

4 

2 

0 

4 

4 

3 

1 

4 

5 

3 

0 

6 

4 

2 

0 

5 

4 

2 

1 

1 

10 

1 

0 

3 

10 

1 

0 

2 

8 

5 

0 

3 

7 

3 

2 

4 

5 

5 

1 

1 

5 

7 

2 

2 

1 

0 

0 

0 

2 

2 

0 

0 

1 

1 

2 

0 

2 

1 

1 

2 

1 

1 

0 

2 

0 

2 

0 

11 

5 

0 

0 

1 

9 

4 

1 

1 

12 

3 

0 

9 

6 

2 

0 

12 

4 

1 

0 

11 

5 

1 

0 

17 

45 

11 

3 

19 

37 

17 

2 

27 

38 

9 

6 

22 

36 

16 

5 

24 

38 

14 

4 

29 

30 

15 

6 

3 

3 

0 

0 

3 

3 

0 

0 

2 

2 

2 

0 

4 

2 

0 

0 

3 

3 

0 

0 

4 

2 

0 

0 

3 

1 

1 

0 

0 

3 

1 

0 

1 

3 

1 

0 

4 

0 

1 

0 

5 

0 

0 

0 

0 

4 

0 

1 

10 

29 

5 

0 

14 

23 

7 

2 

16 

19 

11 

1 

17 

18 

6 

4 

14 

20 

8 

3 

15 

22 

7 

1 

8 

10 

4 

0 

6 

10 

5 

0 

4 

14 

3 

2 

8 

8 

5 

2 

10 

8 

4 

1 

4 

12 

5 

1 

3 

2 

1 

0 

5 

4 

0 

0 

4 

4 

0 

0 

2 

6 

0 

0 

5 

3 

0 

0 

4 

2 

1 

1 

37 

65 

. 17 

1 

28 

45 

|32 

16 

16 

66 

32 

I 15 

22 

53 

40 

15 

30 

61 

|29 

122 

32 

55 

30 

10 


* Only the remote computing companies mentioned by five or more users are listed individually. The 57 companies rated by fewer than five users 
are combined in the "All others" entry. 

**Users' ratings are expressed in terms of user responses; the legend is E for Excellent, G for Good, F for Fair, and P for Poor. The Weighted 
Average of All Ratings" was calculated by assigning a value of 4 to each Excellent rating, 3 to Good, 2 to Fair, and 1 to Poor. 


23% 

50% 

22% 

5% 

23% 

48% 

22% 

5% 

34% 

53% 

11% 

1% 

36% 

47% 

13% 

4% 

35% 

48% 

13% 

1% 


Excellent Good Fair Poor Terminal Type 

Manuals and documentation 23% 50% 22% 5% Interactive 

Application packages 23% 48% 22% 5% Remote batch 

Language and compilers 
Reliability 

Response time adequacy 

As you can see, the users made it quite clear that they 
were generally well pleased with the current services in 
terms of overall satisfaction, case of use (for experienced 
or DP-oriented people), languages and compilers, reli¬ 
ability, and response time. At the same time, the users’ 
overall ratings show plenty of room for improvement in 
the areas of cost-effectiveness, technical support, training, 
documentation, application packages, and case of use for 
inexperienced users. 

Determining the most popular communications terminals Language 

from the survey proved to be rather cumbersome due to 
the proliferation of terminals being used arid the frequent FORTRAN 

use of more than one commercial service. Consequently, BASIC 

avoid bias in the results, Datapro categorized the com- COBOL 

municat ions terminal population by I unction only, result APL 

ing in the following data: 


No. of Terminals % of Total 


1137 

159 


88 

12 


Thus, the survey results clearly demonstrate that 
interactive terminals are still far more widely used than 
remote batch terminals for remote computing applica¬ 
tions. The Teletype Model 33 continues to be the most 
popular terminal for remote computing use. However, 
other terminal manufacturers such as GE, Texas 
Instruments, and Univac are winning a significant market 
share. 

The programming languages used by the survey 
respondents were as follows: 


No. of Users 

354 

216 

98 

41 


% of Total 

75 

45 

21 

9 




2 













































































USERS' RATINGS OF REMOTE COMPUTING SERVICES 


Company* 

No. of 
User 
Replies 


Users' Ratings** 


Weighted 
Average 
of All 
Ratings** 

Overall 

Satisfaction 

Cost 

Effective¬ 

ness 

Response 

Time 

Adequacy 

Reliability 

Ease of 

Use 

(Inexperi¬ 

enced 

Users) 

Ease of 
Use 

(Experi¬ 

enced 

Users) 

Effective¬ 
ness of 

T raining 
Aids 

E 

G 

F 

P 

E 

G 

F 

P 

E 

G 

F 

P 

E 

G 

F 1 

P 

E 

G 

F 

P 

E 

G 

F 

P 

E 

G 

F 

P 

APL Services, Inc. 

7 

2.73 

1 

2 

4 

0 

1 

4 

2 

0 

2 

4 

1 

0 

1 

2 

2 

1 

0 

3 

2 

0 

0 

5 

1 

0 

0 

2 

2 

1 

Boeing Computer Services, Inc. 

19 

2.75 

3 

12 

3 

1 

0 

6 

10 

3 

5 

11 

3 

0 

4 

9 

4 

2 

1 

5 

11 

1 

5 

11 

1 

2 

1 

8 

4 

3 

Compu-Serv Network, Inc. 

24 

3.04 

5 

14 

5 

0 

5 

11 

5 

2 

7 

15 

2 

0 

9 

13 

2 

0 

5 

12 

5 

2 

12 

8 

2 

1 

0 

9 

10 

1 

Computer Sciences Corp. 

40 

3.02 

13 

22 

4 

1 

7 

24 

8 

1 

13 

18 

7 

2 

12 

19 

8 

1 

9 

15 

10 

4 

22 

13 

3 

0 

2 

24 

8 

2 

Comshare, Inc. 

23 

2.85 

2 

16 

5 

0 

2 

8 

11 

1 

4 

16 

3 

0 

6 

13 

3 

1 

1 

10 

7 

4 

7 

12 

2 

0 

2 

10 

5 

2 

Control Data Corp. 

21 

2.92 

3 

13 

4 

0 

5 

10 

3 

3 

5 

12 

4 

0 

5 

11 

3 

0 

3 

3 

8 

4 

7 

11 

2 

0 

2 

9 

4 

1 

Cyphernetics 

31 

3.05 

6 

19 

6 

0 

2 

9 

13 

7 

11 

16 

3 

0 

15 

15 

0 

0 

3 

17 

10 

1 

12 

12 

4 

0 

5 

15 

7 

2 

Data Resources, Inc. 

5 

2.60 

0 

4 

1 

0 

0 

1 

4 

0 

0 

1 

4 

0 

0 

2 

2 

1 

0 

3 

2 

0 

1 

3 

1 

0 

0 

3 

0 

0 

First Data Corp. 

6 

3.18 

3 

3 

0 

0 

4 

2 

1 

0 

2 

4 

0 

0 

2 

4 

0 

0 

1 

2 

2 

0 

4 

1 

0 

0 

0 

0 

5 

0 

General Electric Co. 

134 

3.00 

28 

78 

21 

6 

13 

66 

44 

8 

55 

63 

11 

2 

58 

57 

13 

2 

22 

80 

22 

5 

64 

54 

8 

1 

19 

71 

26 

4 

Floneywell Information Systems 

7 

3.13 

3 

3 

1 

0 

2 

4 

0 

0 

4 

2 

i 

0 

2 

4 

1 

0 

1 

3 

1 

2 

4 

2 

1 

0 

0 

3 

1 

0 

Interactive Data Corp. 

6 

2.75 

0 

4 

2 

0 

1 

2 

3 

0 

3 

2 

0 

1 

2 

3 

1 

0 

0 

1 

3 

2 

2 

3 

1 

0 

1 

2 

2 

1 

Interactive Sciences Corp. 

5 

3.36 

3 

2 

0 

0 

3 

2 

0 

0 

4 

1 

0 

0 

3 

2 

0 

0 

1 

2 

2 

0 

3 

2 

0 

0 

0 

4 

1 

0 

McDonnell Douglas Automation Co. 

13 

2.88 

3 

10 

3 

0 

2 

5 

4 

2 

3 

6 

3 

1 

6 

5 

2 

0 

1 

5 

6 

1 

7 

6 

0 

0 

1 

4 

4 

2 

National CSS, Inc. 

36 

2.92 

10 

15 

10 

1 

8 

8 

15 

5 

10 

15 

8 

3 

9 

14 

8 

4 

7 

9 

13 

5 

5 

17 

0 

0 

4 

17 

8 

2 

On-Line Systems 

12 

3.21 

8 

1 

2 

1 

3 

5 

3 

1 

9 

2 

1 

0 

9 

3 

0 

0 

1 

8 

3 

0 

9 

2 

1 

0 

2 

5 

2 

3 

Rapidata, Inc. 

15 

2.70 

1 

7 

6 

1 

1 

6 

5 

3 

3 

8 

1 

2 

2 

10 

1 

1 

1 

8 

3 

1 

1 

9 

4 

0 

1 

4 

5 

2 

Remote Computing Corp. 

5 

2.83 

1 

1 

2 

0 

1 

0 

2 

1 

1 

2 

1 

0 

2 

1 

1 

0 

2 

0 

1 

0 

2 

2 

0 

0 

0 

0 

3 

0 

Scientific Time Sharing Corp. 

17 

3.33 

7 

8 

1 

0 

7 

6 

3 

0 

11 

6 

0 

0 

10 

7 

0 

0 

4 

6 

4 

2 

8 

7 

1 

0 

5 

10 

0 

0 

The Service Bureau Co. 

80 

3.07 

16 

49 

13 

1 

7 

41 

25 

6 

37 

38 

4 

1 

36 

35 

7 

2 

19 

44 

15 

2 

36 

34 

3 

0 

22 

47 

9 

2 

Standard Information Systems 

6 

3.25 

3 

3 

0 

0 

2 

3 

1 

0 

0 

3 

1 

1 

2 

2 

2 

0 

2 

2 

2 

0 

3 

3 

0 

0 

2 

3 

1 

0 

Time Sharing Resources, Inc. 

5 

3.16 

1 

4 

0 

0 

1 

1 

2 

2 

2 

3 

0 

0 

0 

5 

0 

0 

1 

4 

0 

0 

2 

3 

0 

0 

0 

3 

0 

1 

Tymshare, Inc. 

46 

2.96 

8 

30 

6 

2 

5 

18 

14 

9 

8 

23 

11 

4 

18 

17 

7 

4 

13 

13 

16 

4 

18 

23 

3 

2 

7 

15 

16 

2 

United Computing Systems, Inc. 

23 

3.01 

5 

15 

3 

0 

10 

7 

6 

0 

5 

15 

2 

1 

6 

14 

3 

0 

4 

13 

2 

2 

9 

13 

1 

0 

1 

7 

8 

3 

University Computing Co. 

9 

3.30 

5 

3 

1 

0 

2 

5 

1 

0 

3 

5 

0 

0 

3 

4 

1 

0 

3 

4 

0 

1 

2 

4 

1 

0 

2 

4 

1 

0 

All others 

131 

2.85 

31 

66 

23 

11 

40 

45 

31 

14 

48 

57 

16 

11 

36 

65 

22 

8 

20 

48 

43 

13 

55 

56 

15 

1 2 

11 

40 

38 

23 


* Only the remote computing companies mentioned by five or more users are listed individually. The 57 companies rated by fewer than five users 
are combined in the "Ail others" entry. 


**Users' ratings are expressed in terms of number of user responses; the legend is E for Excellent, G for Good, F for Fair, and P for Poor. The 
"Weighted Average of All Ratings" was calculated by assigning a value of 4 to each Excellent rating, 3 to Good, 2 to Fair, and 1 to Poor. 


Language 

Assembler 

PL/1 

MACRO 

RPG 


No. of Users 


17 

15 

5 

1 


% of Total 

4 

3 

1 


Thus, FORTRAN remains the clear leader in popularity, 
with BASIC and COBOL also boasting widespread 
acceptance among remote computing users. The survey 
respondents were using an average of 2.16 different 
programming languages each. 


The remote computing applications reported by the 
survey respondents spanned virtually the entire spectrum 
of business and scientific applications. The leading 
applications cited included the following: 


Application 

No. of Users 

% of Total 

Accounts payable 

48 

10 

Accounts receivable 

48 

10 

Banking 

16 

3 

Billing 

8 

2 

Communications 

4 

1 

Data base management 

60 

13 

Educational 

11 

2 

Engineering 

78 

16 

Financial 

167 

35 

General ledger 

21 

4 

Hospital administration 

3 

1 

Information retreival 

16 

3 

Insurance 

17 

4 

Inventory control 

34 

7 

Modeling 

68 

14 

Numerical control 

2 

— 


3 




































































Application 


No. of Terminals % of Total 


Operation research 3 

Payroll 21 

Personnel 10 

Production 20 

Project control 7 

Sales analysis 4 

Scheduling 7 

Scientific 27 

Simulation 28 

Statistical 83 

Text editing 6 


1 

4 

2 

4 

1 

1 

1 

6 

6 

17 

1 


In addition to the information previously requested, this 
year’s survey was expanded to cover other questions of 
possible interest to the industry. This data covers areas 
such as amounts spent monthly, changes in 1975-1976 
usage, length of use, user categories, and proportional use 
of time-sharing/remote batch services. The results are 
summarized in the following tables. 


Average Monthly Bill for 

Remote Computing Services No. of Responses % of Total 


Below $500 

199 

28 

$500 to $2,000 

239 

34 

$2,000 to $5,000 

123 

17 

Over $5,000 

148 

21 

Changes in Use of 



Services During 1975 

No. of Responses % of Total 

Increased 

430 

58 

No change 

161 

22 

Decreased 

116 

16 

Stopped 

27 

4 


Expected Changes in Use 
of Services during 1976 


Increase likely 
No change likely 
Decrease likely 
Will likely stop 

Type of Service Usage 

100% conversational 
time-sharing 

Over 50% conversational 
time-sharing 
Over 50% remote batch 
100% remote batch 

Length of Use 

Under 6 months 
Under 2 years 
2 to 5 years 
Over 5 years 

Extent of Communications 
Network Required 


Local only 
500-mile radius 
Nationwide 
International 

Categories of users 


Management 
Programmers 
Other data processing 
personnel 
All others 


No. of Responses % of Total 


236 

37 

218 

34 

135 

21 

49 

8 

No. of Responses % of Total 

371 

51 

221 

31 

96 

13 

37 

5 


No. of Responses % of Total 


61 

8 

215 

30 

288 

39 

164 

23 

No. of Responses % of Total 


416 58 

66 9 

177 24 

68 9 

%of Total 


1,435 15 

2,478 25 

2,117 22 

3,725 38 


No. of Users 






This excerpt was reprinted with permission from "All About Time-Sharing 
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THE CASE AGAINST CORPORATE PLANNING MODELS* 
Robert J. Allio, Canada Wire and Cable Limited 


Management interest in the use of models for business planning and 
forecasting has flourished in recent years. Much of this interest 
was stimulated by the easy access which time-sharing has provided 
to the computer and its ability to process large amounts of data 
quickly. However, the development of a variety of simple program¬ 
ming languages and computational subroutines also has facilitated 
experiments with planning models. 

The result has been a surge in model building. Seventy-three per¬ 
cent of those corporations queried in a recent survey** were active 
ly developing or applying computer models of their firms. Manage¬ 
ment scientists and econometricians also have constructed models 
of more complex phenomena, such as the national economy. 

Corporate management 3 unfortunately, has often been disappointed 
and disillusioned by the performance of computer models. Models 
have not increased our ability to contend with increasing uncer¬ 
tainty and some apparently irreversible trends. We desperately 
seek better decision-making tools. Why have models failed to meet 
our expectations? 

The failures of modeling do not derive from any single source. We 
must took instead to a variety of factors 3 including the following: 

(1) The_ data bas_e i_s flawed 

The data base for a model often contains inadequate 3 
inaccurate 3 or irrelevant historical information. As 
a result, the past may be as obscure as the future. 

Output from a model having such a data base will be 
unreliable and misleading. More input data may not 
improve either the quality or reliability of the output. 

Some corporations have been beguiled into the belief 
that re liabi titiy of descriptions 3 forecasts, or output 
in general increases the size of the data base or the 
number of equations in the model increases. In reality 3 
of course 3 it is often only the confidence_ of the modeler 
which increases as model size or complexity increases. 

Simple models may be more reliable than complex models. 

( 2 ) Causal rel^a/ti^nshi^^ have^ not been, e_sta^_lished. 

Models of business units are predicated upon either 
causality or strong correlations among the variables. 

The impact of changes in behavior by one function of 
the organization (e.g. 3 marketing, manufacturing 3 engi¬ 
neering) upon financial performance often is hard to 


-more- 


* Originally presented at NABE's The Use and Abuse of Econometric 
Models for Economic Forecasting and Business Planning Conference, 
Port Chester, New York, December, 1975. 

**Thomas H. Naylor, The Future of Corporate Planning Models, Social 
Systems, Inc., 1975. 







I 


define. The task of defining these impacts is even more 
difficult during a period of rapid change. Simple 
static systems may he easy to model--hut, the results 
have little interest to management. Ironically, it is 
the interesting systems (complex and dynamic) which are 
hard to model. 

Our knowledge of how to huild complex models has greatly 
surpassed our understanding of how a complex organization 
works. Skill in programming a computer is a poor substi¬ 
tute for understanding the behavior of the corporation. 

(3) Sif_stem behavior^ i_s ignored 

Most models tend to treat business units as closed sys¬ 
tems or make simple assumptions about the key exogenous 
variables. The contemporary corporation, however, is 
part of an open system. Actions by any of a multitude 
of stakeholders, including consumers, environmentalists, 
legislators, labor, and. suppliers, can have a profound 
effect on the organization. Few attempts have been made 
to couple the behavior of the firm to the behavior of 
the total system. Even the efforts to predict industry 
sector performance based on macromodels of the economy 
have been notoriously unsuccessful. 

Simulating the effect of business tactics or strategy is 
no easier. How will a change in price influence market 
demand for a product? How will competition respond to 
thi$ price change? Predictions based on the classic 
laws of the free economy have less and less validity as 
the environment becomes more regulated and monopolistic 
or oligopolistic. Political decisions on fiscal and 
monetary policy have been responsible for much of the 
variance in recent economic forecasts--have any models 
incorporated political variables into their structure? 

(4) Last i/ear'g motde_l is_ o^Sjolet^ 

despite Santayana's position on this issue, we are con¬ 
demned to repeat the past only if we believe the future 
to be an extension of the past. Models based on this 
premise tend to give unreliable output. Paradoxically, 
however, historical simulation is the standard method 
for validation of models. 

Surprise free scenarios have little value, because the 
future is no longer an extension of the past. We live 
in an era of rapid change. Many of these changes are 
caused by discontinuities and by definition are either 
unpredicted or unpredictable. Models must introduce 
new assumptions about the future--those models which 
ignore the future have not often been helpful to 
management. 

(5) Model vff 2 cmsf_ to qbancLf if t££. slow_ 

Models must be adaptable to changes in the environment. 
Rates of change, however, are often too rapid for models 
to accommodate--the reaction time of the model is too 





6 






slow. Even in a stable situation, the time required to 
collect data, process data, and provide output to the 
decision-maker is often incompatible with the needs of 
the decision-making process. 

The apparently high inertia of many models often is 
created by the model builder who falls prey to the 
Penelope web syndrome. Penelope, apparently abandoned 
by Ulysses, staved off her many suitors by promising to 
marry as soon as she completed weaving a tapestry. To 
the dismay of her suitors, the tapestry made little . 
progress towards completion. Although she wove dili¬ 
gently during the day, Penelope would arise each night 
and undo a portion of her day's work. The corporate 
model is always being refined by the model builder, and 
seems to approach completion no more quickly than 
Penelope's tapestry. To be sure, it is the client for 
the model who is the ultimate victim of this syndrome. 

The failures of models have contributed to a rapid deterioration 
in their credibility and the credibility of model builders. The 
isolation of model builders in many firms has not helped. Modelers 
talk mostly to other members of their own cult. All too often 
they fail to communicate effectively with their ultimate customer, 
the management of the firm. As a result, they may not understand 
the decision-making process of the organization. Strategic manage - 
ment decisions, as one example, are rarely made on the basis of 
quantitative data alone (although these data may be an important 
input to the decisions). These are some of the specific traps 
practitioners fall into: 

0 Promote or endorse multiple data bases (e.g., 
the financial data base vs. the planning data 
base). 

0 Insist that packaged programs are never as 
good as the unique program that can be 
designed for the organization’s allegedly 
unique needs. 

0 Build "complete" but high-inertia inflexible 
mode Is. 

Even if the model be defect-free, top management is often uncom¬ 
fortable with the process of modeling. As a consequence, they may 
be reluctant to accept the output from the model. The final 
criterion for the quality of any model must be its acceptability 
to the user. 


We cannot, however, hold the model builder entirely responsible for 
the recalcitrance of management. Most top executives have had 
limited exposure to management science. This has created a cultural 
gap between management and the model builder. All managers, more¬ 
over, rely heavily upon their intuition. This reliance creates an 
interesting paradox. Managers will believe the output from a simple 
model because it comports with their intuition--but, the output will 
be dismissed because it is usually trivial. Output from a complex 


7 



model on the other hand is often counterintuitive. 4s a result, 
although a manager's intuition may well he faulty, he or she tends 
to reject such output (even though it may he correct). 

Effectively designed and utilized models have high potential utility. 
What can he done to improve their value and acceptance? Here are 
some prescriptions: 

0 Give special attention to the accuracy and relevance of 
the data base; make sure that valid indicators are 
selected*. Examine carefully the assumptions of the 
model to assure that they will apply during the time 
period of interest. 

0 Make the response time of the model fast enough to meet 
the needs of the decision-makers and fast enough to 
sense any important external change. Consider the use 
of a system to provide early warning economic, techno¬ 
logical, social, or political discontinuities and 
turning points. 


0 Do not present the model as a tool for making accurate 
predictions. Do use the model to prepare alternative 
scenarios, i.e., to illustrate the future consequences 
of present decisions. 

0 Improve communications with management. Emphasize the 
benefits of the modeling process, e.g., in displaying 
information. Start with simple, short turn-around 
models which work (i.e., get management's confidence!). 
Models of well-structured decomposable problems provide 
the best entree to the later use of strategic models. 


Modeling has been abused and oversold. Despite their limitations, 
however, models have enormous potential to improve the decision¬ 
making process. Thus, while it is risky to rely blindly on models, 
not to utilize their power is equally risky. 


*Failures to properly forecast the 1974-75 decline in the U.S. 
economy were the result of using incorrect economic indicators. 


* * * * 


Reprinted with permission from NABE NEWS, 
Association of Business Economists, April 


published by The National 
1976, No. 8. 


8