End Users: Who are They?

End Users: Who are They? Chittibabu Govindarajulu End users have come a long way—from the little known users of the late 1970s to the “knowledge workers” of today. Fueled by enormous growth in computing technologies and falling hardware prices, end-user computing (EUC) has been crucial for increasing productivity in many firms. End users not only develop and operate applications for themselves and others, they also control the EUC activities around them. Understanding the depth of the roles played by end users can be immensely useful to the practitioner. Cotterman and Kumar [1] developed a little known classification scheme called the end user cube, which has a focus on EUC dimensions that can increase understanding of the contemporary end user. They identified three dimensions: operation, development, and control. This is a rational approach that is reflective of the contemporary end user, since today’s end users can play the roles of operator of the applications developed by them or by others, developer of applications, and finally controller of the EUC environment. Understanding the depth of these roles played by end users can be immensely useful to the practitioner. The main focus of this article is to operationalize the user cube to classify today’s end users, with the help of data collected from nearly 300 end users. Popular EUC applications, levels of application development, and end-user support are also analyzed. Despite the relevance of Cotterman and Kumar’s method of classifying users according to dimensions, most academic researchers have classified users by their knowledge of computing technologies. Rockart and Flannery proposed the most popular of such classifications, identifying the following six user types [3]: • • •

Nonprogramming end users, who neither program nor use report generators. Access to computerized data is through a limited, menu-driven environment or a strictly followed set of procedures. Command level users, who perform simple inquiries, often with a few simple calculations such as summation, and generate unique reports for their own purposes; End-user programmers, who utilize both command and procedural languages directly for their own personal information needs. They develop their own applications, some of which are used by other end users.

Chittibabu Govindarajulu ([email protected]) is an assistant professor of MIS in the Department of Management at LeBow College of Business, Drexel University, Philadelphia, PA Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. © 2003 ACM

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Functional support personnel, who are sophisticated programmers supporting other end users within their particular functional areas. These are individuals who, by virtue of their prowess in EUC languages, have become informal centers of systems design and programming expertise within their functional areas. These individuals are early adopters willing to try new software and hardware. End-user computing support personnel, who are most often located in a central support organization such as an information center. DP programmers, who are similar to traditional COBOL shop programmers except that they program in end-user computing languages.

Clearly the last two types of users are IT staff and hence are usually ignored. The first four types represent end users of varying skills. Functional support personnel are early adopters who would like to try new software and hardware and usually are the informal source of support for other users within the department. A closer look at these types reveals that they do not give any indication as to whether users have control over end-user computing activities or not. Although this classification served its purpose while EUC was in its infancy, it fails to include contemporary dimensions of EUC that appear to have reached maturity. A clear classification of end users is absolutely necessary for practitioners to devise strategies for better management of end-user computing in their organizations. For researchers, it gives a clear direction of study to understand the potential of various types of end users and their support needs. This study focuses on the application of the user cube approach to end-user classification. Although user cube is an excellent framework, researchers have largely ignored it because of the lack of an available instrument. A preliminary 10-item instrument was designed based on the Cotterman and Kumar’s definitions of the three dimensions: operation, development, and control. The 10-item scale is presented in Table 1. Based on the three dimensions the user cube identifies eight difTable 1. Instrument to classify end users. EUC Dimensions and Items on the questionnaire

Scale

Development Please rate 1. Your involvement in the design of end-user applications 2. Your involvement in the specification of end-user application requirements 3. Your involvement with respect to actual coding of end-user applications 4. Your involvement in the implementation of the applications developed by them and/or by others Operation Please rate the extent of your use of end-user applications 5. Developed by others in the department 6. Developed by others in the firm Control Please rate 7. Your decision-making authority to acquire hardware (hard disks, RAM etc) for the department 8. Your decision-making authority to acquire software (MS Office, Corel Suite etc) for the department 9. Your authority to initiate, manage, and implement new end-user applications 10. Your authority to collect, store, and use data for the end-user applications

No Involvement

Active Involvement

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

Low Extent

1 1

2 2

High Extent

3 3

4 4

5 5

No Authority

6 6

7 7

Complete Authority

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

3

4

5

6

7

Table 1. Instrument to classify end users. COMMUNICATIONS OF THE ACM September 2003/Vol. 46, No. 9ve

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Figure 1. The User Cube.

Figure 1. The User Cube [1].

ferent types of end-users: user-consumer, user-operator, user-developer, user-controller, user-operator/developer, user-developer/controller, user-operator/controller, and user-operator/developer/controller, representing eight corners of the cube. The user cube is presented in Figure 1. Note that finer classifications are possible if points on the surface and within the cube are considered. Because of variations in end user knowledge level, applications they develop range from simple spreadsheets to complex GUI based programs and dynamic Web pages (with database connectivity). To better understand the types and complexity of applications developed by end users, definitions for different levels of applications were provided to the respondents, as follows: Level 1. Simple applications including presentations using PowerPoint or Harvard Graphics, and static Web pages created with MS Word or other editors. Level 2. Medium-sized applications, including spreadsheets with financial or statistical formulas, and the use of macros in spreadsheets or statistical package such as SAS/SPSS. This level also includes database applications using SQL type queries, dynamic Web pages using Java, Perl, VB scripts, CGI, or Applets, and simple programs using COBOL or GUI-based languages such as Visual Basic, Visual FoxPro, and Visual C++. Level 3. Complex programs involving extensive use of advanced features of COBOL or GUI languages, and substantially more lines of executable code. Applications involving CAD/CAM can be included here. Finally, since end-user applications pose potential threats to data integrity and security, end user support is crucial to educate users on avoiding risks. End users traditionally used help desks (information centers) as their main support source. To confirm this, respondents were asked to rank the given support sources: information center, local MIS staff, and informal support. To collect this data in addition to demographic information, a structured questionnaire was designed. The questionnaire was then converted to an HTML file and posted on the Internet. The site address was widely advertised in various Usenet 154


groups and list servers. Once a respondent completed the survey, the response was written to an MS Access file using active server page (ASP) technology. To prevent duplicate responses, an algorithm was used to ensure that only one response was received from each respondent.

Data Analysis After eliminating incomplete and duplicate responses, 292 useful responses were received from a wide variety of industry sectors, as shown in Figure 2. Although finer classifications are possible, we assigned respondents to a dimension if their average score for that dimension was above 3.5. Figure 3 illustrates the incidence of each end user type among the study participants in a bar graph format. It is interesting to note that 26% of respondents develop applications, use them, and control EUC activities in their departments. At the other end of the spectrum, 17% of respondents did none of these things, but as information consumers, merely

Figure 2. Respondents by industry type.

Figure 3. End-user types (D=developer, O=operator, C=controller). COMMUNICATIONS OF THE ACM September 2003/Vol. 46, No. 9ve

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used information such as printed reports. About 14% of respondents represent both the development and control dimensions. Since end users develop applications mainly for use by themselves or for use by others, it is understandable that pure developers represent only 3%. To better understand how each dimension is represented, a Venn diagram approach is used (see Figure 4). The Venn diagram clearly shows that approximately 47% of respondents represent the developer dimension, while 53% and 63% of respondents represent the operator and controller dimensions respectively. End user computing gained momentum as users learned to develop applications. It is understandable that more respondents represent the operator dimension than the developer dimension since not all users have the knowledge to develop applications. But it is surprising that 63% represent the controller dimension; that finding has not been previously reported by academic researchers. Understanding how each dimension is represented is crucial to effectively manage end users. Under representation of the developer dimension means that EUC is still in infancy. To enhance user productivity, suitable training programs can be designed to educate end users on development. If development and control dimensions are predominant, it may mean that EUC is at an advanced level. In such a scenario, EUC management is crucial to have appropriate policies regarding access rights to corporate data. In order to determine the validity of these findings, the data was analyzed to determine whether developer respondents produced more applications than others, and the findings are presented in Table 2. More developers designed and created more

Venn diagram of EUC dimensions. Figure 4. Venn diagram Figure of EUC 4. dimensions. Type of Applications No. of Applications

Developer (%) (N = 136) 10

Non-Developer (%) (N = 156) 10

Level-1 Applications

14.0

27.2

15.4

37.5

42.3

22.4

14.1

16.0


25.0

25.7

16.2

25.0

64.7

18.6

4.5

6.4


58.1

9.6

14.7

6.6

84.0

6.4

1.3

0.6

Table 2. Number of applications developed by developers and non-developers. Table 2. Applications developed by developers and non-developers.

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end-user applications than the non-developers, a finding that lends credibility to the accuracy of the instrument. The finding that 64.7% and 84% of the non-developers created less than two Level 1 and 2 applications should be interpreted carefully, since it includes those who developed no applications. Although it may be surprising to see respondents classified as non-developers have developed applications, remember that those scoring less than 3.5, and not zero, were classified as non-developers. In general, these numbers suggest a high level of development activity among respondents. Practitioners should find this instrument useful to ascertain the level of development activity in their organizations. Popular applications among respondents included spreadsheets (74%), database-related (54.5%), GUI-based (19.5%), presentations (60.6%), static Web pages (40.1%), dynamic Web pages (25.0%), and graphical (37.3%). The next task is to verify whether respondents classified as controllers tend to hold higher management positions. As Table 3 illustrates, controllers arise mainly from middle or upper management, which is expected since they have more authority and responsibility than lower management users. But a surprising 13% of respondents at the lowest management levels control end user computing activities. While this is not necessarily a negative finding, individuals with the least training have a greater potential to put corporate data at risk. Among non-controllers, about 10% of middle managers and 3% of upper managers who responded to the survey reported minimal or no control over departmental end user computing activities. This finding is not encouraging since these individuals are accountable for the activities and performance of their departments. Control is a critical dimension of EUC and it should be exercised with care mainly by the middle to upper levels of management, who are the best qualified to maximize benefits such as increased productivity, employee satisfaction and morale, and to curtail the risks arising out of end user applications, such as redundancy, and threats to data integrity and security. Finally, to understand the trend in end user computing support, respondents were asked to rank their support sources: information center/help desk, local MIS support, and friends/colleagues. The results of rankings for the five biggest respondent groups are presented in Figure 5. All the user groups ranked friends’ support as their top preferred support source, except for the controller group, which ranked information center as the preferred source. Among the formal support sources, information center support seems more popular than localized support for four of the five largest user groups. This is contrary to the belief that local MIS staff can provide betDesignation Operator/Technician

Controller (%) (N = 183) 13.1

Non-Controller (%) (N = 109) 10.10

Clerical Staff

3.80

16.50

Supervisor

4.90

5.50

Middle-level Manager

21.90

10.10

Upper-level Manager

14.80

2.80

CEO/CIO level Administrator

10.90

0.00

Table 3. Positions held by 3. controllers non-controllers. Table Positionsand held by controllers and non-controllers. COMMUNICATIONS OF THE ACM September 2003/Vol. 46, No. 9ve

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Figure 5. Respondents’ ranking of support sources.

ter end user support than the information center staff, since local support staff is well versed with the functioning of a specific department and applications used. Also, when rankings of all the respondents were considered together, information center support was preferred by respondents to local MIS staff support. It should be noted that the data presented in this study might not be a true representation of the population. The percentages of users representing each dimension may vary among organizations. However, this article gives a general idea of the state of end user computing as represented by a random group of participants.

Conclusion This article has clearly illustrated the many faces of end users, who can work as application developers, operators, controllers, or some combination of the three. Given the variance among end users, it is crucial to understand the “power users” and “power centers” among the end user population. Such an understanding will help in the formulation of policies regarding end user support issues. Adopting a policy to provide tailored education to the various groups of users, for example, would enhance user morale and satisfaction. Also, the respondents’ preference for information center support can be effectively used to manage support functions. Certain support functions, such as access to centralized corporate data, can be delegated to information centers, while others, such as application development support and hardware/software support can be assigned to localized support staff. Such strategies may results in productivity gains, and cost effectively minimize risks to data integrity and security. The classification discussed in this article is a useful tool for researchers to study the interaction between the types of users, support sources, and the different areas of 158


support end users might require. It is important to remember the instrument used in this study can also be used for finer end user classification than demonstrated here. EUC is on its way to achieving a mature state, and it must be effectively managed to achieve gains and to reduce the risks that come with the territory. The instrument presented here is a good starting place.

References

1. Cotterman, W.W. and Kumar, K. User Cube: a taxonomy of end users. Commun. ACM 32, 11 (1989), 1313–1320. 2. Govindarajulu, C. The status of helpdesk support: a survey. Commun. ACM 45, 1 (2002), 97–100. 3. Rockart, J.F. and Flannery, L.S. The management of end-user computing. Commun. ACM 26, 10 (1983), 776–784.

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End Users: Who are They?

End Users: Who are They?

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