critical success factors revisited: success and failure cases of information systems for senior...

Ž .Decision Support Systems 30 2001 393–418www.elsevier.comrlocaterdsw

Critical success factors revisited: success and failure cases ofinformation systems for senior executives

PoPo Poon), Christian Wagner 1

Department of Information Systems, City UniÕersity of Hong Kong, 83 Tat Chee AÕenue, Hong Kong, People’s Republic of China

Accepted 1 April 2000

Abstract

Ž .The literature suggests the existence of critical success factors CSFs for the development of information systems thatsupport senior executives. Our study of six organizations gives evidence for this notion of CSFs. The study further shows aninteresting pattern, namely that companies either Aget it rightB, and essentially succeed on all CSFs, or Aget it completelywrongB, that is, fall short on each of the CSFs. Among the six cases for which data were collected through in-depthinterviews with company executives, three organizations seemed to manage all the CSFs properly, while two others managedall CSFs poorly. Only one organization showed a mixed scorecard, managing some factors well and some not so well. At thecompletion of the study, this organization could neither be judged as a success, nor as a failure. This dichotomy betweensuccess and failure cases suggests the existence of an even smaller set of Ameta-successB factors. Based on our findings, wespeculate that these Ameta-successB factors are AchampionshipB, Aavailability of resourcesB, and Alink to organizationobjectivesB. q 2001 Elsevier Science B.V. All rights reserved.

Keywords: Executive information systems; Critical success factors; Critical failure factors; Information systems success; Case study

1. Background

The successful development of information sys-tems for senior executives is not easy for any organi-zation. Information systems to support senior execu-tives have been available for well over a decade,

Ž .initially as Aexecutive information systemsB EIS ,and today more frequently as EIS components of

Ženterprise resource planning software such as. Ž .SAPrR3 , on-line analytic processing OLAP soft-

) Corresponding author. Tel.: q852-2788-9959.Ž .E-mail addresses: [email protected] P. Poon ,

Ž [email protected] C. Wagner .1 Tel.: q852-2788-7546.

ware, or data warehouse access software. EIS andtheir derivatives have always been high-risk systems,offering usually only one chance to successfullyimplement them in the organization. Consequently,

w xmany failures have occurred 5,14 , with estimatesbeing as high as 70%. Technological, organizational,psychological and educational issues all contribute tomaking the implementation of such systems difficultw x20,21 .

In addition, although EIS and their successors aresupposedly specifically tailored to top executives’information needs, few executives made significant

w xdirect use of them. Fitzgerald and Murphy 9 foundthat only 32% of users were at executive level.Furthermore, the majority of executives did not rate

Ž .EIS benefits very highly. The majority 68% of

0167-9236r01r$ - see front matter q 2001 Elsevier Science B.V. All rights reserved.Ž .PII: S0167-9236 00 00069-5

( )P. Poon, C. WagnerrDecision Support Systems 30 2001 393–418394

users was at middle management level. These middlemanagers were not using the systems on behalf ofexecutives but for their own information needs. Nord

w xand Nord 18 confirmed that vice-presidents andmiddle managers exhibited higher system usage thantop executives.

Taken together, these facts illustrate that imple-mentation success cannot be taken for granted, andthat even successful implementations might not beused as intended. Furthermore, critical success orfailure factors applicable to other types of informa-tion systems may not necessarily apply to informa-

Žtion systems for executives compare for instancew x.critical failure factors in Flowers 10 . Hence, as

EIS and their derivatives are offered by an increasingnumber of vendors and supposedly used by more andmore organizations, understanding the determinantsfor their successful implementation and use becomesincreasingly important. Interestingly enough, littleresearch has been carried out concerning this subject

w xmatter. Although Rockart and DeLong 22 proposedŽ .a model of critical success factors CSFs for EIS

over 10 years ago, little additional research of thecore concepts and theoretical foundations was con-

w xducted in subsequent years 27 . The few studies thatŽ w x.followed e.g., Turban 25 , largely confirmed

Rockart and DeLong’s factors through one or morecases.

Hence, to date, it has yet not been determined ifthe CSFs are universal in their application to differ-ent organizations, business environments and culture,or if they are an artifact of prevailing company andcountry cultures. A recent article by Bensaou and

w xEarl 3 for instance hints at interesting differencesbetween Western and Japanese IT management, withrespect to the ways in which requirements should bedetermined or success should be measured. To shedmore light on the critical link between CSFs andsystem success, six cases of information systems forsenior executives from organizations in Hong Kongwere analyzed over a time frame of 18 months.

Ž .Some of the systems were new 2 years or less ,whereas others had been in use for up to 6 years. Theorganizations chosen represent a number of differentindustries ranging from education, hospital, shipping,electric supplies, to railways and airways. Withineach organization, several members were inter-viewed, to assess success from several perspectives.

The article is organized as follows. We will nextbriefly describe the meaning of system success andsuccess characteristics. This will be followed by areview of CSFs and the selection of CSFs to befurther considered within this study. We will thendiscuss research methodology, followed by results,and discussion. The manuscript ends with conclu-sions and suggestions for future research.

2. System success

ŽIt has been known for a long time that EIS and.their derivatives are usually developed with high

w xexpectations, yet often end in failure 21,30 . So howcan we define system success? Unfortunately, sys-tems that support decision making are difficult orimpossible to justify using standard economic evalu-

w xation methods. Keen 12 showed that defining andquantifying the benefits of a decision support systemis very difficult. While the cost of an EIS can beestimated, putting a dollar value on the benefits isdifficult since the benefits of EIS can be intangible

w xand transient 22 . Nevertheless, Rockart and De-Long suggested that there is a hierarchy of fourissues to consider when evaluating an EIS. In addi-tion, other researchers, such as Cottrell and Rapleyw x w x6 or Rainer and Watson 21 have put forwardadditional criteria that can be used to determine EISsuccess. Based on their combined suggestions, wechose five evaluation criteria, which are introducedbelow together with the explanation for their choice.

2.1. Access: the EIS is made aÕailable and users aregiÕen access to the system

It is obvious that if the development team cannotmake the system available to users, the users cannotaccess the system and the system, in this case, thesystem is unsuccessful. Even a seemingly availablesystem can be difficult to access, if it requires com-plicated log-in procedures, or access from only a fewdedicated terminals.

2.2. Use: the EIS is used by the intended users

It is logical that if the system ceases to be used, itcannot provide any benefit to users and then cannot

( )P. Poon, C. WagnerrDecision Support Systems 30 2001 393–418 395

be seen as successful. Therefore, there is a need toensure that the EIS is actually used by its potential

w xusers. As Rockart and DeLong 22 mentioned, howmuch time executives spend using the system canindicate the success of the EIS. Moreover, Leidner

w xand Elam 13 realized that the frequency with whichsystem is used is also one of the factors that reflectthe success of EIS.

2.3. Satisfaction: users are satisfied with the EIS

User satisfaction is one of the most widely usedindicators of success in information system researchw x15 . The level of users’ satisfaction will also havedirect impact on whether or not the system is usedw x2 . So, if the EIS cannot satisfy its users, the userswill not use the system anymore. As a result, thesystem will not be successful.

2.4. PositiÕe impact: the EIS has positiÕe impact onthe executiÕes and the organization

An EIS is successful if it has a beneficial impacton the executives and organization. As indicated by

w xRockart and DeLong 22 , a successful EIS canimprove the manager’s mental model of the com-

w xpany and Mintzberg 16 proposed that better deci-sions result from better mental models. Once theexecutives can make better decisions, a positive im-pact on the organization is obtained.

2.5. Diffusion: the EIS tends to spread

Another feature to indicate successful EIS is thatthe number of people using the system increasesafter the initial users have tried to use the systemw x22,29 . Once the non-users perceive the system canprovide benefits to them, they may request access tothe system. In addition, once EIS users found thattheir colleagues gain positive impact from the sys-tem, they may promote the system to other col-leagues. As a result, the number of EIS users will

w xsteadily rise. Santosus 23 describes this phe-nomenon for a successful EIS implementation atMotorola, where success meant an increase in thenumber of users, applications, and platforms through

Ž .which the EIS was delivered spread and growth .

Absent from our success criteria list are factorsthat refer to implementation issues. Of course, themost basic level of success for any EIS is whether itis completed in the first place vs. its remaining inanalysis design or prototyping stages. In fact, severalfailure cases in our study failed early, never gettingbeyond the prototyping stage.

3. CSFs reviewed

In the previous section, we introduced successŽcriteria, the measures of success for systems and

.operationalizations of our dependent variable . Ourfocus will now move to what is frequently calledAcritical success factorsB, namely the conditions thatneed to be met to assure success of the system. Inother words, they are operationalizations of our inde-pendent variable.

The most comprehensive investigation of successfactors for EIS implementation is still the work by

w xRockart and DeLong in 1988 22 . Prior to it, therewas no clear agreement on the factors that are mostsignificant in making the implementation processsuccessful or to identify the best development pro-

w xcess to follow. Rockart and DeLong 22 observed 30cases, where attempts were made to implement EIS.From these, they extracted eight areas that appearedto be the most important to EIS success. Both execu-tive users and developers also deemed all eightfactors most important.

Ž w xSeveral other researchers Paller and Laska 19 ,w x w x w xBird 4 , Watson et al. 30 , Whymark 31 , Rainer

w x w x w x.and Watson 21 , Turban 25 , McBride 14 havesubsequently reconfirmed the factors observed byRockart and DeLong. Follow-up research has shownconsiderable agreement on two additional factors.Each of the factors is described below in some detail.

3.1. Committed and informed executiÕe sponsor

Most studies recognize the importance of an exec-utive sponsor who is both sufficiently committed tothe system to invest time and effort in guiding itsdevelopment, and has a realistic understanding of thecapabilities and limitations of the system. A detaileddiscussion of the importance of commitment and


factors influencing commitment for IS projects canw xbe found in Newman and Sabherwal 17 .

3.2. Operating sponsor

To leverage the time of the executive sponsor, itis necessary to have an operating sponsor designatedto manage the details of implementation from theuser’s side. This sponsor should be well acquaintedwith the executive sponsor’s way of working.

3.3. Appropriate IS staff

The quality of the staff that support an IS forsenior executives is important. The project managershould have technical as well as business knowledge,and the ability to communicate with senior manage-ment. Support staff must be sophisticated enough tointeract with top management and be able to masterthe technologies required for the system.

3.4. Appropriate technology

The choice of hardware and software has a majorbearing on the acceptance of a system. In the past, abarrier to executive support was the lack of hardwareand software that fit with the demands of highlyvariable work styles and environments of executives.As more specifically designed products have becomeavailable, this problem has diminished. Developmentis now often replaced by selecting the most appropri-ate system on the market.

3.5. Management of data

The ability to provide access to reliable data fromboth internal and external sources, is a major issue inthe system development. Aggregating, accessing andextracting data from a number of subsidiary databasescan be a stumbling block to the implementation of anIS suitable for executives.

3.6. Clear link to business objectiÕes

The system must solve a defined business prob-lem or meet a need that can be addressed effectivelywith IS technology. There should be a clear link to

business objectives and clear benefits in using thetechnology. The system must provide something thatwould not otherwise be available and add value tothe data.

3.7. Management of organizational resistance

Political resistance is a common cause of imple-mentation failure. Because an IS for executives canalter the information flow in an organization andshift the power relationships within a company, theremay be resistance to its introduction and operation.Handling of this potential conflict source will remainan issue throughout the life of the system. Dragoonw x8 , for instance reports on the case of Eli Lilly,where a AstandardizedB EIS needed to be imple-mented against the resistance of individual groupswho insisted on keeping their own data collectiontechniques.

3.8. Management of system eÕolution and spread

An installation that is successful and used regu-larly by the executive sponsor will almost inevitablyproduce demand by peers or subordinates for accessto a similar system. Managing this process ofAspreadB means identifying the specific job function,technical orientation, work style, and specific infor-mation support needs of each potential user, andtaking that into account when expanding the system.

3.9. EÕolutionary deÕelopment methodology

An evolutionary development methodology iswidely acknowledged as a key factor for system

w xsuccess 11,22 . The most common way of findinghow the technology can provide value for the execu-

w xtive is through prototyping 22 . This also keeps theexecutives aware and hopefully enthusiastic concern-

w xing the project 1 .

3.10. Carefully defined information and system re-quirements

A key design issue is identifying the executivew xuser’s information requirements 28 . A successful

system can only be delivered when the executives’


needs are understood. Getting executives to specifywhat they want is not an easy task. Paller and Laskaw x w x19 and Bird 4 also pointed out that identifyingexecutives’ information requirements was the biggestchallenge faced by the development team. Vanden-

w xbosch and Huff 26 identified differences in execu-tive information needs based on different informa-

w xtion search behavior. And Davenport 7 points outthat even experienced IS consulting firms may find itdifficult to identify executive information needs.

In order to investigate the CSFs involved in im-plementing an EIS in Hong Kong, all 10 factors wereused to predict the success of EIS development inthis research.

4. Methodology

4.1. Research model

Using the above defined concepts of EIS successand CSFs, the study considered a basic EIS successmodel, as illustrated in Fig. 1. The model postulatesthat the presence of the 10 CSFs would result in the

Žsuccess of the information system as measured by.the five success factors , while the absence of the

CSFs would lead to failure of the project. This is astrong interpretation of the CSF concept, treating theCSFs as both necessary and sufficient conditions forsystem success.

Thus, we expected that organizations that did notmanage all CSFs right would incur project failure, orat least a project outcome below company expecta-

Ž .tion Anon-successB .

4.2. Research sites

To assess the importance of the 10 previouslyidentified CSFs, we studied six Hong Kong organiza-

Fig. 1. Research model.

tions that had implemented information systems forsenior executives. The organizations included bothprivate and public companies and government insti-tutions. The six organizations are labeled here by analias, describing their principal business:

1. Major Railway Corporation,2. International Airline,3. Health Care Provider,4. Large University,5. Utility,6. Shipping Company.

4.3. Data collection

The research was conducted through a series ofpersonal interviews with several key personnel ineach organization. While many questions wereopen-ended, questionnaires were sent before the in-terview, thus ensuring that all interviews followedthe same general format and that interviewees couldprovide more informative data.

Interviewees were asked to complete the question-naires before interviews were held. There were twosets of questionnaires, one for companies still usingthe system, another one for those who had stoppedusing the system. The questionnaires are shown inAppendices A and B, respectively. Interviews wereconducted with internal developers who developedthe systems in-house, external consultants who helpedguide the development process, software vendorsEIS, and users. The face-to-face interview protocolfollowed the questionnaire questions in order to fo-cus on the aspects that were the most relevant tosystem success and failure. Both developers andusers were interviewed. Developers included boththe internal IS department in each organization andexternal consultants. System users were executivemanagers and middle managers. Observational visitsof the organizations were also conducted to watchthe systems in use.

The study did not produce quantitative data, norwas any attempt made to quantify essentially qualita-tive data. In many cases, we were simply looking for

Žthe absence or presence of a particular factor e.g.,.was there an operating sponsor? , while at the same


time checking whether that characteristic was ful-filled only superficially, or in a meaningful way.

5. Results

5.1. EIS success

After questionnaire and interview results for allsix organizations were analyzed, three success casesemerged, two failure cases, and one unresolved case.The two failure cases were identified both by a lackof benefits derived by the firm, and by the decisionto discontinue the use of the EIS in both cases. Inother words, they were true failures. The unresolvedcase was identified by a situation where the systemwas actually used, but only at a small fraction of itsfunctionality, benefits had not yet been clearly real-ized, and that no future expansions were planned atthe time of the study. While this was not an aban-

Ždoned system, it had not met expectations and thusmet our definition of a Anon-successB, given in the

.previous section . Table 1 shows in more detail howthe six cases measured up against the previouslyintroduced list of success measures. Each case re-ceived a qualitative summary rating for every suc-cess measure. A measure rated as AGoodB meansthat most of the users agreed the measure was wellachieved. An AAcceptableB rating indicates marginal

performance of the relative success measure, withsome signs of success. For example, system use wasmarginal at Large University. Some users consid-ered the system to be successfully employed whileothers did not. The underlying issue was that systemuse was optional, and that executives were able toobtain the data through other means as well. Hence,the system did not play a strategic, but merely asupport role. A case rated APoorB reflect high agree-ment among users that the success measure was notwell achieved.

5.2. CSFs obserÕed

To demonstrate how EIS successes and failuresstacked up against the management of CSFs withinthe six organizations, we compiled summaries ofrelevant CSF performance data in Table 2. For eachorganization, management of each CSF is ratedthrough a summary rating of U for ACSF welladdressedB, or > for ACSF ignoredB. In addition, thesummary ratings are supported through factual datafrom each case.

The results emphasize the importance of CSFs.When all factors were present, the system succeeded;when they were absent, the system failed. In oneunresolved case, some factors were present and oth-ers not, with the result being undecided.

Table 1Success criteria for the six case studies


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cont

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don

next

page


Ž.

Tab

le2

cont

inue

d

ŽŽ

ŽŽ

ŽŽ

.C

riti

cal

succ

ess

Maj

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5.M

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data

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proj

ect.

fine

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()

cont

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don

next

page


Ž.

Tab

le2

cont

inue

d

ŽŽ

ŽŽ

ŽŽ

.C

riti

cal

succ

ess

Maj

orra

ilw

aysu

cces

sful

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iona

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case

case

7.M

anag

emen

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UU

UU

>>

orga

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8.M

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6. Discussion

Our study clearly supported the importance ofCSFs for system success. However, it also showed avery interesting pattern related to the absence orpresence of CSFs. Simply stated, the three successcases seemed to manage all CSFs right, while thetwo failure cases seemed to manage all of themwrong. This suggests two things.

First, there might exist a smaller number ofmeta-CSFs, which, if managed correctly, result in allothers to go right as well, or vice versa. Why so? Inessence, without the presence of such meta factors, itwould require a high level of coincidence for us tosee the very clear patterns of success and failure.Furthermore, previous research, including the study

w xof EIS at British Airways 6 suggests a smallernumber of very CSFs. Second, the failure cases areso drastic in their failure, one might suggest that theyhad been meant to fail. Apparently, there were forcesin the organizations that wanted the EIS to fail, andpursued this goal in a very systematic way.

Six cases are too few to identify meta-CSFs withany certainty. However, based on our analysis ofinterviews and questionnaires, and especially the fo-

Ž .cus on the yet unresolved case large university ,together with the data from the British Airwaysstudy, we can make several educated guesses. Largeuniversity did well on championship, having bothexecutive and operating sponsors. As the BA studysuggests as well, championship is a fundamentalfactor. For large university, it was one of few thathad gone right and that had given the system enoughimpetus to get well under way. Large university didnot do well on availability of resources, neither onpeople resources, nor appropriate technology, norfinancial resources. This seemed to be a fundamentalmissing factor. In the BA study, availability of re-sources, especially staff resources, played a major

Žrole. Furthermore, one of our success cases major.railway seemed to clinch success through very Adeep

pocketsB that allowed the company to obtain anyŽ .necessary technology and technology infrastructure ,

so that lack of resources never became an issue.Finally, the unresolved case suggests the importanceof one more factor, namely the tight link to businessobjectizes. This was a factor that was present in all

successful systems, also present in the unresolvedcase, but absent in the failure cases.

Clearly, executives will have a strong bottom-lineorientation, and very limited time to hunt for bene-fits. Thus, a system that can clearly demonstratebenefits, by being linked to business objectives, willhave a strong selling point with respect to useracceptance. Reflecting on the factors, we might alsosuggest a temporal consideration. Even before anEIS development is launched, it will require strongsponsorship to result in its initiation and seed re-sources. However, as the implementation continues,operational factors, such as resource availabilityŽ .people, technology and money become a necessarycondition. And finally, as the system moves into usephase, while continued executive sponsorship andresources are required, a system will receive littleuse if it cannot establish clear benefits.

The two failure cases and their peculiarcomplete-failure condition, offer some evidence forthe presence of additional critical failure factors.Apparently, the two organizations did not want anEIS to succeed. Comparing the two failures with theother cases in our set, interestingly, they also repre-sented the only two organizations with a Chinesemanagement system in place. In the Chinese man-agement system, the owner typically makes allstrategic and major personnel decisions and the dele-

w xgation to middle management is low 32 . Directsupervision of work and personal reporting relationsare more important forms of control, and the formalinformation system is often ignored and bypassed in

w xthe Chinese management system 32 . Therefore, atUtility, the top management preferred to receive datathrough informal personal reporting rather thanthrough an information system. On the other hand,support staff members at Utility wanted to maintaintheir influence by providing critical data for the topmanagement. Therefore, they were unwilling tochange, fearing of loss of influence once top man-agement would be able to circumvent them by ac-cessing the information system. Hence, it was no

Žsurprise that the staff of Utility as well as the staff.of Major Shipping was unwilling to supply data for

the system. At Major Shipping, the data providersand middle management did not co-operate with theEIS project manager. At Utility, the IT manager


reported that the corporate culture was not ready forthe system’s development.

This factor is different from the CSFs Aclear linkto business objectivesB and Amanagement of organi-zation resistanceB. The management system, whichmight not be based on formal written rules, but onpeople’s experiences and beliefs of what it takes toget ahead in the organization, may be opposed tobusiness objectives. Consequently, if strong enough,the management system may cause initiatives to failŽby delaying them, or denying them some of their

.benefits that otherwise could have been beneficialw xfor the business 24 .

Mismatch of the information system with theorganization’s management system should also bedifferentiated from AnormalB organization resistance,which might be considered a generic fear of theunknown, or the Afear based cultureB, which illus-

w xtrated by Flowers 10 . In our failure cases, thereseemed to exist an interest in letting the system failrather than a lack of interest in system success.

7. Conclusions

With the growing influence of information sys-tems for executives, OLAP, and EIS components ofERP software, understanding system failure and suc-

cess is becoming more important as well. AssociatedŽwith EIS is a trend that is OLAP on-line analytical

.processing . In contrast to on-line transaction pro-Ž .cessing OLTP , which focuses on order entry and

other transaction-processing systems, OLAP includesdecision-making systems for marketing, sales, andfinance. OLAP is a way of looking beyond transac-tions to forces driving them. It can help companiesaccurately forecast sales in order to better plan in-ventory and production levels, know where advertis-ing is working and where they are wasting millionsof dollars, and determine if their products are cor-rectly priced.

In our study, we were able to confirm the applica-bility of all of Rockart and DeLong’s original eightCSFs, as well as two additional factors. Yet based onour findings, we suggest that organizations may Agetit rightB simply by managing three factors, champi-

Ž .oning at the executive and operational levels , re-sources, and linking the system to business objec-tives. We also saw evidence that these systems can-not succeed if they contradict the prevailing manage-ment system. As usual, companies that believe theycan solve their problems with an information systemwill likely fail. Those that translate business goalsinto corresponding information needs and then into awell-managed system will likely succeed.


Appendix A


Appendix B


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