a multi-level approach to measuring the benefits of an erp system in manufacturing firms-p

PLEASE SCROLL DOWN FOR ARTICLE

This article was downloaded by: [PERI Pakistan]On: 11 April 2011Access details: Access Details: [subscription number 909589956]Publisher Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Information Systems ManagementPublication details, including instructions for authors and subscription information:http://www.informaworld.com/smpp/title~content=t768221794

A Multi-Level Approach to Measuring the Benefits of an Erp System inManufacturing FirmsDavid Gefen; Arik Ragowsky

To cite this Article Gefen, David and Ragowsky, Arik(2005) 'A Multi-Level Approach to Measuring the Benefits of an ErpSystem in Manufacturing Firms', Information Systems Management, 22: 1, 18 — 25To link to this Article: DOI: 10.1201/1078/44912.22.1.20051201/85735.3URL: http://dx.doi.org/10.1201/1078/44912.22.1.20051201/85735.3

Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf

This article may be used for research, teaching and private study purposes. Any substantial orsystematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply ordistribution in any form to anyone is expressly forbidden.

The publisher does not give any warranty express or implied or make any representation that the contentswill be complete or accurate or up to date. The accuracy of any instructions, formulae and drug dosesshould be independently verified with primary sources. The publisher shall not be liable for any loss,actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directlyor indirectly in connection with or arising out of the use of this material.

http://www.informaworld.com/smpp/title~content=t768221794

http://dx.doi.org/10.1201/1078/44912.22.1.20051201/85735.3

http://www.informaworld.com/terms-and-conditions-of-access.pdf

18

W W W . I S M - J O U R N A L . C O M

W I N T E R 2 0 0 5

A MULTI-LEVEL APPROACH TO MEASURING THE BENEFITS OF AN ERP SYSTEM IN MANUFACTURING FIRMS

David Gefen and Arik Ragowsky

This research study examines associations between the business characteristics of manufac-turing firms and their perceived benefits from ERP system investments. The perceived ERP benefits are measured at two levels: (1) an enterprise level and (2) a specific IT module level. The perceived value for ERP investments was consistently better explained at the specific IT module level.

ith the growing proliferation of enter-prise resource planning (ERP) systems,including among midsize companies,it becomes critical to address why and

under what circumstances one can realize thebenefits of an ERP system. In contrast to previ-ous research, this study examines how manag-ers (president, CFO, production VP, etc.) assessERP success in specific modules (e.g., suppliersand purchase orders, customers and sales) ascontrasted with their assessment of the entireERP portfolio as one entity. Data collected in270 manufacturing organizations that imple-mented initial ERP systems (without additionalmodels such as CRM) show that the benefitfrom investment in ERP is explained better byorganizational business characteristics when ex-amined at a specific ERP module level.

To meet organizational needs, computer-ized information systems in manufacturingfirms have evolved over the past 40 years fromaccounting and simple inventory control,through MRP (material requirement planning)and MRP II (manufacturing resource planning),

to today’s focus on ERP systems (Sarkis and Gu-nasekaran, 2003). ERP systems are softwarepackages that manage and integrate all the en-terprise’s data, and provide information basedon this data on a real-time basis. ERP systemscan provide the organization with competitiveadvantage through improved business perfor-mance (Hitt et al., 2002; Kalling, 2003) by,among other things, integrating supply-chainmanagement, receiving, inventory manage-ment, customer orders management, produc-tion planning and managing, shipping,accounting, human resource management, andall other activities that take place in a modernbusiness (Gefen and Ridings, 2002; Hong andKim, 2002; Kalling, 2003). Yet the cost of im-plementing an ERP software package is sub-stantial, ranging from $200,000 for smallcompanies with annual sales approximating$10M, through $600,000 to $800,000 for mid-size companies with annual sales approximat-ing $50M to $80M, and up to several milliondollars for larger companies. This refers to themanufacturing management aspects of the ERP

W

ENTERPRISE SYSTEMS

DAVID GEFEN is Associate Professor of MIS at Drexel University. His work has also appeared in such publications as MIS Quarterly, Information Systems Research, and Journal of Management Information Systems. He can be contacted at [email protected].

ARIK RAGOWSKY is Associate Professor in Information Systems and Manufacturing Director, Center for Information Systems and Manufacturing at Wayne State University. His work has also been published in Communications of the ACM, Information Technology and Management, and International Journal of Industrial Engineering. He can be contacted at [email protected]

ISMA20501.book Page 18 Thursday, November 11, 2004 12:11 PM

Downloaded By: [PERI Pakistan] At: 05:22 11 April 2011

mailto:[email protected]

mailto:[email protected]

19

I N F O R M A T I O N S Y S T E M S M A N A G E M E N T

W I N T E R 2 0 0 5

ENTERPRISE SYSTEMS

alone, excluding CRM. It was estimated that inthe past decade about $300 billion was invest-ed in ERP systems worldwide and that thiswould grow to $79 billion annually by 2004(Carlino et al., 2000). While some companiesclaim to have reduced their cycle time, im-proved their financial management, and ob-tained information faster through ERP systems(Kalling, 2003), ERP systems in general stillhave a high initial implementing failure rate(Hong and Kim, 2002; Songini, 2004).

Many prior studies examining the relation-ship between investing in IT and the perfor-mance level of the organization (Weill, 1992)dealt with the ratio of total IT investment (i.e.,software, hardware, personnel) to the entireorganization’s performance (the total profit ofthe organization). Many early studies found nopositive relationship between the two vari-ables. Strassmann (1985) examined service-sec-tor firms but found no significant relationshipbetween investment in IT and high-performingfirms. Berndt and Morrison (1992) even founda negative relationship between the growth inproductivity and investment in high-tech, al-though, as they point out, this may have beenthe result of measurement problems. As Bryn-jolfsson (1993) summarizes, positive returnsfrom investing in IT may not have shown up inprevious research because of the inadequateway it was measured. In part, early researchmay not have found such a productivity in-crease because of the way IT usage and in-creased company productivity were measured.When measuring IT investment on a per-userbasis, there is a positive correlation between ITinvestment and overall productivity (Brynjolfs-son, 2003). Although there is a large varianceamong companies in the benefit they achievefrom their IT investment (Brynjolfsson, 2003),on average there is a $10 gain in company val-uation for each dollar invested in IT (Brynjolfs-son et al., 2002). Showing such a positiverelationship is important because it affects MISfunding.

Still, whether investment in ERP systemspays off remains a controversial question (Hittet al. 2002; Sarkis and Sundarraj 2003; Kalling,2003). ERP systems are very complicated soft-ware packages that support the entire organi-zational activities. Hence, it is possible thatthere are many unknown factors that impactthe relationship between investment in ERPand the organizational productivity. This studyapproaches this problem from another direc-tion. Instead of looking for the relationship be-tween investment in IT and the productivity of

the organization as other studies did, it exam-ines the senior manager’s perception of thebenefit their organization gains from usingtheir ERP system and what impacts this benefit.

The basic assumption in this article is thatwhat an organization expects of its ERP isshaped by the organization’s activities, but thatthese expectations will be better formulatedwhen examined on a specific level. Because toa large extent ERP activity is determined by or-ganizational business characteristics and be-cause these differ among the various ERPmodules, it follows that the nature of these ac-tivities should determine differently the per-ceived value of each ERP module. In amanufacturing firm, for example, ERP systemscoordinate customer orders with materialsmanagement, stocks, suppliers, productionschedules, product customizations, manufac-turing requirements, and employee schedulesand hiring. An ERP system can have a dramaticeffect in such cases, based on the organiza-tion’s operational characteristics, but differentERP modules will have different impacts.

Accordingly, the objective of this study is toexamine whether managers’ perceptions ofbenefit from their ERP is better explainedwhen measuring it on a module-by-module ba-sis, rather than on an investment in IT as awhole level. Along the same lines, Barua et al.(1995) explain the need to measure the bene-fits from IT module by module, rather than ex-amining investment in IT as one homogeneoustechnology, and examining these module leveleffects within the context of the organizationalhierarchy. Barua and Lee (1997) also highlightthe need to examine IT productivity within thecontext of how the IT is used. Recent studiessupport this assessment (e.g., Sarkis andSundarraj, 2003; Kalling, 2003). For example, asaving in inventory holding costs at the loweroperational level will contribute to total costreduction at a higher level, and ultimately toimproved organizational performance. The ap-proach to valuing IT investments resemblesPorter’s (1985) explanation that competitiveadvantage should be understood at the specificoperational activity level, rather than by exam-ining the impact of the entire company’s IT.

However, the benefits derived from the useof IT cannot necessarily be evaluated indepen-dently of the organization itself. For example,the benefits from an ERP module that handlesmaterial requirements planning (MRP), a first-order effect, may also result in a better returnon investment, which is a second-order effect(Barua et al., 1995). Yet to accurately predict

ositive returns from investing in IT may not have shown up in previous research because of the inadequate way it was measured.

P



20

W W W . I S M - J O U R N A L . C O M

W I N T E R 2 0 0 5

ENTERPRISE SYSTEMS

the first-order effect, a better understanding ofthe manufacturing environment is needed. Acommon manufacturing IT application, such asan MRP system, enables manufacturing manag-ers to determine the timing and quantities ofmaterial purchases and component productionrequired to satisfy finished goods demand in atimely and cost-efficient manner. This results intangible benefits, such as increased inventoryturnover, a reduction in holding costs, and anincrease in the overall capacity utilization by as-suring the availability of raw materials. But thiseffect is not necessarily applicable to all manu-facturing contexts. A process plant that pro-duces products such as chemicals, milk, orcans usually produces the same products overand over again. This type of manufacturer usu-ally dedicates each production line to the man-ufacture of one product and maintainsminimum levels of raw material in inventory.An MRP system is less likely to be adopted be-cause it has little value in this type of manufac-turing environment. Another example is acompany that produces semiconductors. Themain raw material this company uses is steel.The lead-time for this raw material is about 15weeks. But the lead-time for a customer orderis only 10 days. Consequently, this companymust keep high levels of raw material to meetits customers’ orders on an on-time basis. MRPsystems cannot help this company reduce thelevels of inventory and reduce inventory hold-ing costs. However, while an MRP system maycontribute little to such companies, other ERPmodules may be of greater value. Hence, itmight be more advisable to examine ERP valueat a modular, rather than global, level. Arguablythen, the decision to implement a specific ERPmodule should depend on the organizationalcharacteristic because the expected benefitsfrom it should be affected by the specific needsand characteristics of the organization(Ragowsky et al., 2000).

Accordingly, the underlying proposition ofthis article is that to gain a better assessment ofthe benefits derived from ERP systems, theevaluation should be conducted on an individ-ual module level, as suggested by Barua et al.(1995). This article therefore challenges thetendency to assess ERP value as one package —as software vendors suggest (

Wall Street Jour-nal

, June 9, 1999) — despite the recognitionthat ERP systems are designed to integrate in-formation across functions and processes.

RESEARCH QUESTIONS AND MEASURES

Because the business success of a for-profit or-ganization is measured by profit, managersmust have a means of assessing the benefittheir organizations gain through investment inIT. This is particularly true for ERP systems be-cause of the large cost involved in ERP imple-mentations. Accordingly, the research questionof this study is:

Are there organizational characteris-tics that predict the benefit an organi-zation may gain from an ERP systemand can these be assessed better at asubsystem level?

One way of addressing this question is througha sample with firm-level data where evidenceof benefit is based on the assessment of themanagers involved. Such an approach shouldalso take organizational characteristics into ac-count because different organizations may gaindifferent benefits even from using similar IT ap-plications (Ragowsky et al., 1996; Ragowsky, etal., 2000). Following Porter (1985) and Baruaet al. (1995), it is proposed that the benefitsgained by ERP systems will be better predictedby being measured separately at the level of ac-tivity areas within the organization (purchas-ing, customer management, productionmanagement, and the like), rather than at thebroad level of the entire ERP system. From thisargument two expectations are derived:

1. An organization’s characteristics will be apoor predictor of the benefits an organiza-tion gains from an ERP system when thesebenefits are measured for the entire ERPsystem as a single entity.

2. A strong and significant relationship existsbetween an organization’s characteristicsand the benefit derived by the organizationwhen assessed at a specific ERP modulelevel.

The findings are based on a field survey of270 manufacturing organizations that imple-mented ERP packages. None of these organiza-tions had a relationship with any of the others.The software packages were from differentvendors (e.g., SAP and others). The data wascollected during the second half of the 1990svia personal interviews with a senior managerof each organization (most of them presidentsor vice presidents). More information on thedata collection is provided in Table 1. The compa-nies in the sample varied widely in their charac-teristics, and Table 2 shows this variability.

t is proposed that the benefits gained by ERP systems will be better predicted by being measured separately at the level of activity areas within the organization, rather than at the broad level of the entire ERP system.

I



21

I N F O R M A T I O N S Y S T E M S M A N A G E M E N T

W I N T E R 2 0 0 5

ENTERPRISE SYSTEMS

Perceived ERP benefits were collected fromthe respondents at two levels. The perceivedoverall benefits at the enterprise level from us-ing the ERP system was used to assess the firstexpectation, while the benefits from individualERP modules were used to assess the secondexpectation. In addition, information was col-lected on several organizational operationalcharacteristics that contribute to an organiza-tion’s uncertainty or complexity. Organizationscan thus benefit from their ERP systems by re-ducing the level of this uncertainty or complex-ity (Ragowsky et al., 1996). Based on Porter(1985), each activity area was represented byrelevant organizational characteristics, such asthe average number of purchase orders permonth for the purchasing activity area, averagesupply time to customers for sales activity area,etc. If these characteristics are found to have astrong effect on the perceived benefits fromspecific ERP modules, but little effect on the to-tal perceived benefit from the ERP system as awhole, then there is merit to the claim that or-ganizations should assess the benefits from ERPsystems on a specific ERP module basis.

The business operating characteristics mea-sured are described below.

Relative Share of Cost of Raw Materialin the Overall Cost of the FinalProduct. Using an ERP system, organizations

can negotiate better with suppliers and thus re-

duce the cost of raw materials by as much as

15 percent (Schlack, 1992). Hence, the higher

the relative share of cost of raw material in the

cost of the final product, the higher the savings

for the organization and, hence, the greater the

benefit of the information provided by the ERP

system. This variable represents the impact of

the decision supported by the additional infor-

mation on organizational objectives regarding

suppliers and the raw material purchase orders

activity area.

Differences among the Suppliers.Suppliers can differ in price, quality, supply

lead-time, etc. The greater these differences are

among suppliers, the more information is need-

ed to choose among them for a specific pur-

chase order. This variable represents the level

of uncertainty or complexity with respect to

suppliers and the raw materials purchase or-

ders activity area.

TABLE 1 Research Methodology Details

The interviews were conducted with the help of trained paid interviewers who conducted structured interviewswith a senior manager of each of the participating organizations. One of the authors personally trained eachinterviewer candidate. Every interviewer candidate first learned the theoretical background of the study andthe questionnaire. Then the interviewer candidate joined the author for two or three interviews in which the au-thor conducted the actual interview with the interviewer observing him. After the interviewer candidates feltthey were ready for interviewing, they interviewed two or three respondents with the author observing them.Only candidates who successfully conducted the interview when the author observed them were selected toserve as interviewers. The objective of this training was to reduce bias due to differences among interviewees.

The senior managers were well aware of the benefits derived from the ERP. The questionnaire was divided intotwo sections. The first section included questions about the organization’s characteristics (e.g., number of sup-pliers, relative share of raw materials cost in the cost of the final product, number of customers, average lead-time to customers, number of products, number of production lines, volume of sales, and number of employ-ees). In the second section, the respondent was asked to assess the benefit the organization derived using itsERP on an overall level: “How would you rank the overall level of benefit derived by your organization from theentire ERP applications portfolio on a scale of: 1 2 3 4 5 6 7, 1 indicating very low benefit and 7 indicating veryhigh benefit?” A similar question was asked with regard to other enterprise-level benefits, as well as with re-spect to the benefits received from implementing key ERP modules.

TABLE 2 Overall Characteristics of Participating Organizations

Min. Max. Median Mean St. Dev.

Volume of sales (in million $U.S.) 1 400 33 41.78 39.52Number of employees 10 2400 100 200 321Number of suppliers 1 5000 45 177 526Number of customers 1 10,000 150 672 1746



22 W W W . I S M - J O U R N A L . C O M

W I N T E R 2 0 0 5

ENTERPRISE SYSTEMS

Average Lead-Time of the Raw Materialsthat the Organization Uses. The longerthe lead-time, the higher the probability ofchanges being made in the order, such as levelsof raw material demand or the risk of a partialor full cancellation of the order. The longer thelead-time, the more information is needed tomanage the purchase orders. This variable rep-resents the level of uncertainty or complexitywith respect to suppliers and raw materialspurchase orders activity area.

Price Elasticity of Raw Materials.Suppliers sometimes offer quantity discounts.The greater the price elasticity, the more infor-mation is needed to obtain the best purchaseorder. This variable represents the level of un-certainty or complexity with respect to suppli-ers and raw material purchase orders activityarea.

Product Complexity. The greater the com-plexity of the product, the more information isneeded for properly managing customer or-ders. This variable represents the level of un-certainty or complexity with respect to thecustomer order activity area. Three kinds ofproducts exhibit different orders of complexityand different degrees of difficulty in tracing thecustomer’s order.

1. Standard products. Customers cannot askfor changes in the products (e.g., food onstore shelves). There is no difficulty in trac-ing customer orders.

2. Standard products with modifications.Modifications are made according to cus-tomer requests (e.g., furniture that can beadapted to the customer specifications).Because this type of product is slightlymore complex than a standard product, it isnecessary to manage information on thespecial specifications to make sure that thechanges have been performed.

3. Custom-designed products. Each order is aspecial product manufactured to customerspecifications. The level of the complexityof the product is the highest. The organiza-tion must create product-specific design,raw material purchase, and scheduling.

Average Time Raw Material InventoryRemains in the Organization. Manufac-turing organizations can save up to 25 to30 percent of inventory carrying costs (financ-ing, storing, insurance, etc.) with its IT. Thelonger the raw material inventory remains inthe organization, the greater the potential for

cost saving. This variable represents the impactof the decision supported by the added infor-mation on organizational objectives with re-spect to material requirement planning.

Average Number of Levels in the Billof Materials of the Firm’s Products.The greater the number of levels in the bill ofmaterials, the more raw materials there are ineach product unit. The more complicated theproduct, the more information is needed tomake sure that every raw material item is avail-able when needed. This variable represents thelevel of uncertainty or complexity with respectto purchasing and customer order activity.

Average Time of a Work-Order. Thelonger the work-order, the more complicatedthe product. Hence, with complicated prod-ucts, more information is needed to managethe process, such as what operations should beconducted and in what order, and when eachraw material is needed in the process. This vari-able represents the level of uncertainty or com-plexity with respect to the customer orderactivity area.

Number of Production Lines. Two fac-tors are primarily responsible for determiningmultiple production lines: either (1) the orga-nization produces many products or (2) thereare several stages that each product must gothrough, as when different parts are producedon different production lines and are then as-sembled. In either case, the more productionlines, the more complicated the productionand the coordination involved. Hence, more in-formation is needed for managing raw materialpurchasing and for customer orders whenthere are more production lines. This variablerepresents the level of uncertainty or complex-ity with respect to customer order activity.

Percentage of Producing for CustomerOr ders vers u s P r o d u c ing forInventory. When producing for customerorders (versus producing for inventory), eachcustomer order must be managed separately onissues such as order specifications and specialrequirements. The more an organization pro-duces for customer orders, the more importantand valuable the information about each orderis, if the company is to supply the order ontime and based on customer specifications.This variable represents the level of uncertaintyor complexity with respect to customer orderactivity.



23I N F O R M A T I O N S Y S T E M S M A N A G E M E N T

W I N T E R 2 0 0 5

ENTERPRISE SYSTEMS

Average Supply Time for CustomerOrders. The longer the lead-time for a cus-tomer order, the more complicated productioncan be. This is because order specification, rawmaterials, and other resources availability maychange. Hence, more information is needed tocoordinate all the activities during the lifetimeof the order. This variable represents the level ofuncertainty or complexity with respect to thecustomer order activity area.

RESEARCH FINDINGSHow the Analyses Were DoneTable 3 presents the results of the regressionanalyses. These regression analyses were usedto find the degrees of explained variance in therelationships between the different benefitsgained by using the ERP as explained by organi-zational characteristics. In Table 3, the first fourcolumns show the effects of operational charac-teristics on the total overall benefit at the enter-prise level, and on three other enterprise-levelbenefits (i.e., Organizational Profitability, MarketCompetition, Cost Reduction). The two right-hand columns in Table 3 show the benefits of

specific modules (suppliers and customers).N/A means that the organizational characteris-tic is not applicable in the case of the specificmodule. These results show, as described be-low, that benefits gained by ERP systems arebetter predicted when measured at a specificbenefit and a specific module level.

Enterprise-Level BenefitsAs Table 3 shows, only two organization charac-teristics have a significant effect on the overallbenefit from the ERP, and even then the degreeof explained variance, the R2, is low at6.9 percent. When more specific enterprise-level benefits were examined, the explainedvariance, while higher, was still low (7 to11.5 percent). Specifically, we asked about “theoverall contribution of the ERP systems to theprofitability of your organization,” “to what de-gree do the ERP systems serve your organiza-tion in competing in the market,” and “to whatdegree do the ERP systems serve your organiza-tion in costs reduction.” These results areshown under the heading “Benefit of ERP as aWhole” in Table 3.

TABLE 3 Effects of Organizational Characteristics on Benefits Gained from ERP

Benefit of Specific Modules

Overall Benefit:

Suppliers and Purchase

Order

Overall Benefit:

Customer Order

Management

Benefit of ERP as a WholeOverallBenefit

Organizational Profitability

MarketCompetition

Cost Reduction

The relative share of cost of raw material in the overall cost of the final product.

0.456** N/A

Differences among suppliers –0.154* 0.125** N/AAverage lead-time of the raw materials that the organization uses (in days)

0.144* 0.140* 0.243** .009**

Price elasticity of raw materials 0.164** 0.217** 0.218** N/AProduct complexity N/AAverage time raw material inventory remains in the organization (in days)

N/A N/A

Average number of levels in the bill of materials of the firm’s productsAverage time of a work order (in days).

–0.144* N/A 0.314**

Number of production lines 0.146* 0.135* N/APercentage of producing for customer orders versus producing for inventory

N/A 0.026**

Average supply time for customer orders

0.154* N/A 0.466**

R-square 0.069 0.071 0.087 0.115 0.390 0.402

Note: Only significant coefficients are shown. * means significant at .05. ** means significant at .01.



24 W W W . I S M - J O U R N A L . C O M

W I N T E R 2 0 0 5

ENTERPRISE SYSTEMS

Results for the Suppliers and Purchase Order ModuleThe Suppliers and Purchase Order modulemanages the suppliers and raw material pur-chase orders. The information provided by thismodule helps the organization plan the pur-chase of raw materials according to its produc-tion plan and the anticipated need for rawmaterials. Using this information, the organiza-tion can obtain better prices for raw materialsand receive the supply as close as possible tothe date it is needed.

As shown in Table 3, four characteristicshad a significant effect on the perceived bene-fits derived from this module. First, the relativeshare of raw materials in the overall cost of thefinal product is an important characteristic.With an ERP, an organization can better negoti-ate with suppliers and reduce the cost of rawmaterials by as much as 15 percent (Schlack,1992). Hence, the higher the cost of raw mate-rial, the higher the value of raw material costreduction out of the cost of the product, andthe information provided by this application ismore valuable. Second, the average lead-timeof raw materials also contributed here. Longerlead-times could result in more interactionswith the suppliers and more changes thatmight impact the purchasing (e.g., changes incustomer orders that change the productionplan and consequently change the need for rawmaterials). These, in turn, require more infor-mation to handle the purchase orders. Hence,the effect this variable has on the benefit orga-nizations gain from the specific ERP module issignificant. Also, price elasticity of raw materi-als and differences among suppliers affect thebenefits for this module. The more options forquantity discount and the more the differencesamong the suppliers, the more informationneeded to compare the different scenarios inorder to make the right decision. The muchhigher degree of explained variance here(39 percent) supports our second research ex-pectation (see “Research Questions and Mea-sures”).

Results for the Customer Order Management ModuleThe Customer Order Management modulemanages customer orders (technical specifica-tions, packaging requirements, supply time tocustomer, details on long-term contracts like“blanket order,” etc.) from the moment the or-der was accepted until it is delivered. This mod-ule helps the organization order according tocustomer specifications, shorten supply time,

and provide timely information to customersabout the status of their orders. These could re-sult in increased sales. The degree of explainedvariance for this module is 40 percent. Again,the higher degree of explained variance can beexplained by how each organizational charac-terstic relates to the actual benefit of the ERPmodule. The far-right column in Table 3 showsthe result of this linear regression. The more theorganization produces for customer orders, themore important and valuable the informationabout each order is, if the company is to supplythe order on time based on customer specifica-tions. The longer the lead-time for raw materialsupply, the higher the probability for changes,and hence the more important this informationis. The longer the work order, the more compli-cated it is to monitor and to make sure it will fitwith related customer orders. The longer thesupply time for a customer order, the more in-formation is needed to handle it. Usually, whenthe supply time is long, more work orders areassociated with the customer order, and moreinformation is needed to ensure that the orderis supplied on time and with correct specifica-tions. The much higher degrees of explainedvariance here also support the second researchexpectation.

CONCLUSIONSAssessing whether investment in IT pays off isan important, if contentious, issue. This study,focusing on ERP systems in manufacturing or-ganizations, examined this question from anew perspective, namely the assessed valuethat involved managers give the ERP system asa function of organizational business character-istics. The assessment of ERP benefits wasmade on two levels: (1) an enterprisewide levelwhere the entire ERP system is assessed regard-ing different types of benefits derived from theERP, and (2) a specific module (application)level. The data shows a remarkable differencein the degrees of explained variance regardingthe managers’ assessment of the benefit de-rived from the ERP system as a function of theorganizational business characteristics. Busi-ness characteristics explain between 6.9 and11.5 percent of the variance in the assessed val-ues of the ERP system at the enterprise level,but explain around 40 percent when it is as-sessed regarding a specific module.

These results answer skeptics who ques-tion the benefits of ERP systems based on en-terprisewide general measures such as ROI.While the explained variance of the benefit

he data shows a remarkable difference in the degrees of explained variance regarding the managers’ assessment of the benefit derived from the ERP system as a function of the organizational business characteristics.

T



25I N F O R M A T I O N S Y S T E M S M A N A G E M E N T

W I N T E R 2 0 0 5

ENTERPRISE SYSTEMS

from an ERP as determined by business charac-teristics is low when examined on an organiza-tional level, it is high when analyzed at aspecific module level. Viewed in this perspec-tive, the results may also explain why so manyERP implementation projects seem to fail. AnERP should be installed, like other business so-lutions, to address specific needs and to fit inwith the organization’s business characteris-tics. ERP may be a one-size-fits-all application,but the benefits still depend on how well theyaddress business needs. The benefit derivedfrom an ERP system may be different for differ-ent modules and may depend on the specifictype of benefit in question. Accordingly, thedata implies the need to integrate the ERP intothe organizational work process in a mannerthat will address specific needs as they relate tothe organization’s business characteristics. ▲

ReferencesAhituv, N. (1989). Assessing the Value of

Information: Problems and Approaches. Proceedings of the Tenth International Conference on Information Systems, 315–325.

Barua, A., Kriebel, C., and Mukhopadhyay, T. (1995). Information Technology and Business Value: An Analytic and Empirical Investigation. Information Systems Research, 6(1), 3–23.

Barua, A. and Lee, B. (1997). The Information Technology Productivity Paradox Revisited: A Theoretical and Empirical Investigation in the Manufacturing Sector. International Journal of Flexible Manufacturing Systems, 9(2), 145–166.

Berndt, E.R. and Morrison, C.J. (1992). High-Tech Capital Formation and Economic Performance in U.S. Manufacturing: An Exploratory Analysis. Economics, Finance and Accounting Working Paper #3419, Sloan School of Management, Massachusetts Institute of Technology.

Brynjolfsson, E. (1993). The Productivity Paradox of Information Technology. Communications of the ACM, 36(12), 67–77.

Brynjolfsson, E. (2003). The IT Productivity Gap. Optimize, July, 26–31.

Brynjolfsson, E., Hitt, L.M., Yang, S., Baily, M.N., and Hall, R.E. (2002). Intangible Assets: Computers and Organizational Capital / Comments and Discussion. Brookings Papers on Economic Activity, 1, 137–198.

Carlino, J., Nelson, S., and Smith, N. (2000). AMR Research Predicts Enterprise Applications Market Will Reach $78 Billion by 2004. AMR Research. Accessed at: www.amrresearch.com/ press/files/99518.asp.

Gefen, D. and Ridings, C. (2002). Implementation Team Responsiveness and User Evaluation of CRM: A Quasi-Experimental Design Study of Social Exchange Theory. Journal of Management Information Systems, 19(1), 47–63.

Hitt, L.M., Wu, D.J., and Zhou, X. (2002). ERP Investment: Business Impact and Productivity Measures. Journal of Management Information Systems, 19(1), 71–98.

Hong, K. and Kim, Y. (2002). The Critical Success Factors for ERP Implementation: An Organizational Fit Perspective. Information & Management, 40(1), 25–40.

Kalling, T. (2003). ERP Systems and the Strategic Management Processes that Lead to Competitive Advantage. Information Resources Management Journal, 16(4), 46–67.

Porter, E.M. (1985). Competitive Strategy. The Free Press, New York.

Ragowsky, A., Ahituv, N., and Neumann, S. (1996). Identifying the Value and Importance of Information System Application. Information & Management, 31(2), 89–103.

Ragowsky, A., Stern, M., and Adams, D. (2000). Relating Benefits from Using IS to an Organization’s Operating Characteristics: Interpreting Results from Two Countries. Journal of Management Information Systems, 16(4), 175–194.

Sarkis, J. and Gunasekaran, A. (2003). Enterprise Resource Planning — Modeling and Analysis. European Journal of Operational Research, 146(2), 229–232.

Sarkis, J. and Sundarraj, R.P. (2003). Managing Large-Scale Global Enterprise Resource Planning Systems: A Case Study at Texas Instruments. International Journal of Information Management, 23(5), 431–442.

Schlack, M. (1992). IS Has a New Job in Manufacturing. Datamation, (Jan. 15, 38–40.

Songini, M.C. (2004). Ford Abandons Oracle Procurement System Switches Back to Mainframe Apps, Computerworld, August 23, accessed at http://www.computerworld.com/ softwaretopics/erp/story/0,10801,95404,00.html

Strassmann, P. (1985). Information Payoff: The Transformation of Work in the Electronic Age, Collier Macmillan, London.

Tallon, P., Kraemer, K., and Gurbaxni, V. (2000). Executives’ Perception of Business Value of Information Technology: A Process-Oriented Approach, Journal of Management Information Systems, 16(4), 145–173.

Weill, P. (1992). The Relationship between Investment in Information Technology and Firm Performance: A Study of the Valve Manufacturing Sector. Information System Research, 3(6), 307–333.

RP may be a one-size-fits-all application, but the benefits still depend on how well they address business needs.

E



http://www.computerworld.com/softwaretopics/erp/story/0,10801,95404,00.html

http://www.computerworld.com/softwaretopics/erp/story/0,10801,95404,00.html

http://www.amrresearch.com

http://www.amrresearch.com

a multi-level approach to measuring the benefits of an erp system in manufacturing firms-p

Documents