A modular approach to ERP system selection

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A modular approach to ERP system selection

A modular approach to ERP system selection

A case study Mohsen Ziaee, Mohammad Fathian and S.J. Sadjadi

485

Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran Abstract Purpose – This paper aims to study an enterprise resource planning (ERP) software selection problem. The primary goal of this paper is to propose a two-phase procedure to select an ERP vendor and a suitable ERP software. Design/methodology/approach – In the first phase of the proposed method the preliminary actions – such as constructing a project team, collecting all possible information about ERP vendors and systems, and identifying the ERP system characteristics – are established. In the second phase, the authors present a modular approach to ERP vendor and software selection and propose a 0-1 programming model to minimize total costs associated with procurement and integration expenditures. Findings – The proposed approach and the model are considered to be more useful for small manufacturing enterprises (SMEs). Originality/value – In using the model for analyzing the data about a real case study that is a commercial SME and based on obtained results, some parameter values of the model for all SMEs are suggested. Keywords Computer software, Manufacturing resource planning, Modelling Paper type Case study

1. Introduction Severe market competition has dramatically transformed the business environment with the result that companies need to reduce total costs, maximize return on investment, shorten lead times, and be more responsive to customer demands. Highly dynamic markets call for effective enterprise information systems to enhance competitive advantage. Enterprise resource planning (ERP) is increasingly important in modern business because of its ability to integrate the flow of material, finance, and information and to support organizational strategies (Yao and He, 2000; Yusuf et al., 2004). Owing to limitations in available resources, the complexity of ERP systems, and the diversity of alternatives, selecting an ERP project is a time-consuming task. Several methods are proposed for selecting suitable ERP software or an information system. One of them is the scoring method (Ptak, 2000). This method is intuitively simple. Another method is based on the nominal group technique and the analytic hierarchy process. The method suggests ten criteria for the evaluation of the ERP projects (Teltumbde, 2000). Other methods are also proposed for the selection of a suitable information system which uses the nonlinear programming models, 0-1 goal-programming models and the analytic network process method (Lee and Kim, 2001; Santhanam and Kyparisis, 1995, 1996). Wang and Wei (2002) suggest a fuzzy

Information Management & Computer Security Vol. 14 No. 5, 2006 pp. 485-495 q Emerald Group Publishing Limited 0968-5227 DOI 10.1108/09685220610717772

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multiple-criteria decision-making method to evaluate the ERP alternatives. This paper tries to integrate the evaluation of objective external professional data sources and subjective internal interview data sources. A recent study on ERP package selection in 55 Turkish manufacturing companies from a variety of industries applies 17 criteria for the ERP selection (Baki and C¸akar, 2005). However, many of these methods have some limitations, inadequacies and deficiencies including (Wei et al., 2005; Wei and Wang, 2004), they: (1) do not ensure resource feasibility; (2) do not contain sufficient detailed criteria; (3) are not easy to quantify; (4) involve only the consideration of internal managers; (5) are not compatible with overall organizational goals and strategies; (6) do not initiate appropriate business process changes; and (7) need to be customized. Some researchers may claim that their proposed frameworks are more comprehensive, but they do not meet all these seven criteria. Indeed, it seems that developing such a framework containing all aspects and lacking the limitations and inadequacies mentioned above is a tedious task. A big portion of ERP system acquisition costs are the costs of the consultation before the procurement and the costs of ERP architecture. Most of these costs are related to the analysis of the organizational processes and a careful determination of the required modules by ERP vendors and consultants. Therefore, if the modules are studied by the customer organization in the ERP software selection process, then the customer knowledge of his organization increases, the project failure probability decreases and a large amount of the consulting costs are saved. In this paper, we propose a two phase method to select ERP vendor and software. In the first phase, the preliminary actions are done. These actions are: forming a project team and doing business process re-engineering (BPR), collecting information about ERP software packages and vendors and filtering unqualified vendors out. Some more information concerning these actions can be found in (Wei et al., 2005; Wei and Wang, 2004). In the second phase (selection phase), we present a modular approach for ERP vendor and software selection. We propose a 0-1 programming model to minimize the costs of procurement and integration. The proposed approach and model is especially useful for small manufacturing enterprises (SMEs) because of the following reasons (Ravarini et al., 2000): . they have strict financial limitations and they seek cheaper solutions; . there are usually no formal business strategies. Therefore, they rarely spend time on studying strategic choices of IT; . information systems used by SMEs are usually very cheap and have a very high degree of customization; . they seek solutions with lower functional and orgazinational impacts; and . they have little or no experience of outsourcing. Finally, we use the proposed model for a commercial SME.

2. A procedure for selecting suitable ERP software In this section, we describe a two phase algorithm for ERP vendor and software selection. In this procedure, almost all of the customer organization members are involved and almost all of the existing potentials of the customer organization (including knowledge and experience) are used. The procedure can be successful only if there are commitment, strong leadership and persistence within the organization management (as it was mentioned by Al-Mashari and Al-Mudimigh, 2003). 2.1 The preliminary phase This phase consists of two steps. In the first step, a project team is formed. It consists of top managers or decision makers, executive managers, stock holders, functional experts, users or their representatives. The project team then has to model business processes and reengineer them as much as possible. During the processes analysis period, the functional characteristics of required ERP software are recognized to some extent. In the second step, as much information about ERP vendors and systems as possible are gathered from all possible sources including the internet, magazines, exhibitions and so on. Initial requirements of the desired system are submitted to the vendors’ representatives and they are requested to respond to related questions included in questionnaires or check lists. After receiving their responses, the clearly unqualified vendors are eliminated based on the responses. The following classified factors can help us make decisions concerning the selection of a few vendors. 2.1.1 Software system factors. These factors are related to the characteristics of a software system and its modules which are offered by any of the ERP vendors. The factors are: . strategic fitness or fitting the ERP system to vision, strategies and goals of the organization and adapting to environmental requirements; . required infrastructure, including required hardware and platform independence; . network architecture and security; . module completeness; . standardization (such as data standardization, multi-language, multi-currency, etc.); . user-friendliness including ease of operations, ease of learning, online and offline help; . ease of integration with external systems; . ease of in-house development and upgrading; . use of newest capabilities of information technology; . automatic backup of information; . shorter processing times; . minimum of errors, bugs and breakdowns, automatic data recovery; and . maintainability.

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2.1.2 Vendor factors. These factors are related to the vendors of the ERP software system. The factors are: . supporting and consulting services; . experience and knowledge of our business area; . implementation ability, financial conditions, ERP market share and the scale of vendor; . research and development (R&D); and . prices of products and services. 2.1.3 Project factors. These factors are related to terms and conditions of the contract and its contents. The factors are: . total time of project; . total cost of project; . training, after sales services, technical support and upgrading the versions of software; and . warranties and delay penalties. The above factors are more comprehensive than the factors presented by Baki and C¸akar (2005), Wei et al. (2005), Wei and Wang (2004), Bernroider and Koch (2001) and Verville and Halingten (2003). 2.2 The selection phase In this phase, the best vendor from the vendors qualified in step 2 is selected. Also, we consider the required ERP modules and decide which modules to purchase, which modules to order according to special organizational requirements and processes and, finally, which modules to produce using in-house experts. In this regard, we first have to list the required modules by performing an organizational study and considering all of the modules proposed by the vendors selected in the previous phase. We have to consider the following aspects to determine which modules are purchased, which modules are ordered and which modules are produced: (1) Processes. Before deciding on the modules, we have to consider the type of processes of the respective organizational unit/units. The use of the standard modules needs to impose new processes on the organization. It may also require changes on the previous methods and procedures, completely. If so, the costs of the new system training may be much more than the expected cost. (2) Organizational changes. The use of the ERP standard modules may need to change the organizational units, the job descriptions including job duties, educational and skills requirements, experience requirements, credentialing requirements, etc. (3) Data. Experience has shown that if the standard modules are used, data conversion may be the main challenge and a costly and time-consuming job. (4) User interfaces. User interfaces required by the functions are another important factor.

(5) Upgrading. The use of customized modules may be very risky because of the upgrading and integrating problems. (6) Project team costs. If we use the customized modules, the duration of the ERP project and ERP experts’ engagement may be increased and the work is often dependent on the people.

A modular approach to ERP system selection

Another important aspect is the integration of the modules and if the modules are heterogeneous (that is some of them are tailor made, some of them are purchased with no changes, and others are made in-house), this aspect becomes very important. In our 0-1 programming model, we consider this aspect separated from the other aspects described above. Now the modules are studied considering the above six aspects (indexes), and a number between 1 and 9 is allocated to any module by experts considering any aspect (index) and using a numerical scale of 1-9 (Hwang and Yoon, 1981). Because these six aspects are not equally important for making a decision, we first have to determine the weight of any index (aspect) using a weighting method such as the Eigenvector method (Saaty, 1990). We assume that after using such a method, the normalized weights of the indexes are obtained as: w1 ; w2 ; w3 ; w4 ; w5 ; w6 (0 # wj # 1; j ¼ 1; . . . ; 6). The weighted mean of the scores is then calculated and Table I is formed: In Table I, a higher aik (i ¼ 1,2, . . . ,m and k ¼ 1,2, . . . ,6) shows that it is better to produce the module i with in-house experts based on the aspect k and a lower aik shows that it is better to purchase the module i with no changes based on the aspect k. Also, a medium amount of aik shows that it is better to order the module i considering the aspect k according to the experts. In fact, a higher aik shows that the expert’s interest is to keep the current situation. As mentioned earlier, one of the most important factors to determine the way of procuring the modules is the integration of the modules. This integration can be studied considering two aspects. The first aspect is the severity of the relation between any two modules without considering the way of procuring them. Another aspect is the effect of the module procurement method (purchasing, ordering or producing) on the integration of the modules. In the first aspect, we have to specify the severity of the relation between any two modules. A numerical scale of 1-9 is, again, used for this comparison. The amounts close to 9 indicates that the severity of the relation between the corresponding modules is very important and the integration of them is vital. To obtain a quantity showing the severity of the relation between two modules, we have to consult with the ERP project team experts. After receiving these quantities from the experts, a weight is allocated to any expert and the weighted mean of the scores is then calculated. The obtained values are normalized and Table II is formed. It is clear that in the above table r ij ¼ r ji for all i, j. Let B, O and D denote the purchase of a module with no change, the purchase of a module with changes and customizations, and the production of a module by in-house

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Module 1 Module 2 .. . Module m

Process

Organization

Data

User interface

Upgrading

Project team costs

a11 a21

a12 a22

a13 a23

a14 a24

a15 a25

a16 a26

am1

am2

am3

am4

am5

am6

Table I. The weighted mean of the scores offered by the experts

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experts, respectively. Now, we consider these three cases (B, O, D) and specify the degree of difficulty of integrating any two cases. Therefore, Table III is formed and the values of I ij ’s (i ¼ 1,2,3; j ¼ 1,2,3) are calculated. The method of calculation is similar to the r ij ’s calculation method. In this case, the viewpoints and the scores of the software development experts are very important and their weights in the calculation should be relatively high. It is clear that in Table III I ij ¼ I ji for all i, j. In order to determine the way of procuring the modules, the following 0-1 programming model is formed: min z ¼

m X 3 X L X

m X m X 3 X 3 X L X C ijl X ijl þ l r ab I pq X apl X bql a¼1 b¼1 p¼1 q¼1 l¼1

i¼1 j¼1 l¼1

subject to: 3 X L X j¼1 l¼1

6 X

X ijl ¼ 1

1 X X i1l A wk aik # A2 þ M @1 2 6 X

1 X X i1l A wk aik þ M @1 2

i ¼ 1; 2; . . . ; m

ð3Þ

i ¼ 1; 2; . . . ; m

ð4Þ

i ¼ 1; 2; . . . ; m

ð5Þ

l[E

0

1 X X i2l A wk aik # A4 þ M @1 2 l[E

k¼1

A3 #

6 X

0

1 X X i2l A wk aik þ M @1 2 l[E

k¼1

Table III. The degree of difficulty of integrating any two cases (B, O, D)

ð2Þ

0

k¼1

Table II. The severity of the relation between any two modules

i ¼ 1; 2; . . . ; m

l[E

A1 #

Module 1 2 .Module .. Module m

ð1Þ

0

k¼1

6 X

i ¼ 1; 2; . . . ; m

Module 1

Module 2

– r 21

r 12 –

. . .. . .

Module m r1m r2m

r m1

–

Note: 0 # rij # 1 for i ¼ 1,2,. . .,m

B O D

B

O

D

I 11 I 21 I 31

I 12 I 22 I 32

I 13 I 23 I 33

6 X

0

1 X X i3l A wk aik # A6 þ M @1 2

A5 #

i ¼ 1; 2; . . . ; m

ð6Þ

i ¼ 1; 2; . . . ; m

ð7Þ

l[O

k¼1 6 X

0

1 X X i3l A wk aik þ M @1 2 l[O

k¼1 m X 3 X L X

C ijl X ijl # B

ð8Þ

i¼1 j¼1 l¼1 m X 3 X

X ijl # MY l

l[E

ð9Þ

i¼1 j¼1

X Yl # 1

X ijl ¼ ð0; 1Þ

;i; j; l

Y l ¼ ð0; 1Þ ;l [ E

ð10Þ

l[E

In the above model, m is the number of the required modules, E is the set of ERP vendors and O is the set of in-house producers. X ijl is a 0-1 variable taking value 1 if the module i is procured in the manner j from the supplier l, and 0 otherwise; j ¼ 1 if the module is purchased with no changes, j ¼ 2 if the module is purchased with relatively considerable changes and j ¼ 3 if the module is produced by the in-house experts. Obviously, for j ¼ 1, 2 the value l is related to an ERP vendor (l [ E) and for j ¼ 3 the value l is related to an in-house producer (l [ O). L is the total number of suppliers including vendors and producers. C ijl is the cost of procuring the module i in the manner j from the supplier l, this cost is only the cost of procuring and it does not include the cost of integrating. If the module is procured in the manner 1 or 2 (purchasing or ordering), then cijl is the module price offered by the ERP vendor and if the module is procured in the manner 3 (producing), cijl is then the cost of the module development (it does not include the cost of integrating). Note that an organization may have some usable software packages, so we should use the manner 3 in the proposed model and the cost of the module procurement (cij) will be equal to zero. l is the scaling parameter, rab is the severity of relation between the module a and the module b, Ipq is the degree of difficulty of integrating the two modules procured in the manners p and q (rab and Ipq are described previously). aik (k ¼ 1,2, . . . ,6) and wk are also described previously. M is a big number and B is the available budget. Yl is a binary variable taking value 1 if the ERP vendor l is selected and 0, otherwise. The objective function of the model is the sum of procuring costs and integration costs. The first constraint set ensures that any module is procured in only one manner (1, 2 or 3) and from only one supplier. The value of A1 is 1 and the value of A6 is 9. Although the objective function of the model tries to select a manner for procuring modules so that the total costs is minimized, the constraint sets (2) to (7) impose other special restrictions on the manner of procuring the modules by considering the following relation between A1,A2, . . . ,A6: A1 , A3 , A2 , A5 , A4 , A6

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i ¼ P6 wk aik ; the constraint sets (2) to (7) then state that if A1 # W
, A3 then Let W k¼1
the manner 1 (i ¼ 1) is certainly selected, if A2 , W , A5 then the manner 2 (i ¼ 2) is
# A6 then the manner 3 (i ¼ 3) is certainly selected. certainly selected, and if A4 , W
the objective function will specify the manner of the In the other ranges of W, procuring. The values of A2 ; A3 ; A4 ; A5 are determined based on the type and the size of the organization, the type of the business, environmental conditions and other factors. The constraint set (8) is related to the budget limitation. The constraint sets (9) and (10) insure that only one ERP vendor is selected. In the following section we use the above 0-1 programming model for a real case. 3. An actual evaluation The proposed algorithm has been used in a project control and management center affiliated with a large automotive company to select an ERP vendor and software. This SME controls and manages construction projects. This company needs to use an ERP software package as a new source of competitive advantage and for improving efficiency and effectiveness. After doing all preliminary work (forming a project team and doing BPR as much as possible, collecting information about ERP vendors and systems, and filtering out the unqualified vendors), two vendors have been selected and the ERP project team recognized that the organization would require three modules. These required modules are: HR (human resources), FI (financial accounting) and PS (project system). The other results of using the proposed procedure for this SME are as follows (Table IV): 6 X


1 ¼ A

W j a1j ¼ 6:9935

j¼1


2 ¼ A

6 X

W j a2j ¼ 6:685

j¼1


3 ¼ A

6 X

W j a3j ¼ 7:278

j¼1

A1 ¼ 1

A2 ¼ 5

A3 ¼ 4

A4 ¼ 7

A5 ¼ 6

A6 ¼ 9

B ¼ 200

The values of the Table V have been obtained using the eigenvector method. In this organization, there is only one in-house producer. The optimal solution obtained from solving the 0-1 programming model (with l ¼ 1; l ¼ 1:5) is as follows: X 13 ¼ 1; X 23 ¼ 1; X 33 ¼ 1 (and all other X ij ’s were equal to zero). The obtained solution is reasonable since a SME is not usually able to invest in expensive ERP software (Tables VI– VIII). Aspects modules Table IV. The values of aij’s

HR FI PS

Process

Organization

Data

User interface

Upgrading

Project team costs

7 5.5 7.5

6 8 8.5

8.5 4 7.5

6.5 7.5 7

8 8 6.5

6 7 5

This paper proposes the following values forA2 to A5 in a SME: A2 ¼ 5 A3 ¼ 4 A4 ¼ 7 A5 ¼ 6 In the above values, the interval relating to the manner 1 is larger than the interval relating to the manner 2, since we try to use the standard modules rather than the tailor made or in-house made modules. In fact, to take full advantage of real ERP software, we have to use the standard modules with no changes.

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4. Conclusion and recommendations This paper proposes an algorithm for selecting an ERP system considering all aspects affecting the ERP system selection process. We have proposed a method to determine the way of procuring the required modules based on a 0-1 programming model. The results of a case study indicate that the proposed procedure is useful for selecting a suitable ERP system. Determining the parameters values of the proposed model is very important and it can be the subject of some future research within the area of ERP

Aspect Process Organization Data User-interface Upgrading Project team costs

B O D

HR FI PS

Module HR FI PS

Weight

Normalized weights

7 8 5 4 5.5 3

0.215 0.246 0.154 0.123 0.169 0.092

Table V. The normalized weights of the aspects

B

O

D

1 3 7

3 3 7

7 7 1

HR

FI

PS

– 6 8

6 – 8

8 8 –

Subscript

The manner

Subscript

C i11

C i21

C i12

C i22

C i33

1 2 3

B O D

1 2 3

40 50 70

50 60 85

35 40 75

55 70 95

30 35 50

Table VI. The values of rij’s

Table VII. The values of Iij’s

Table VIII. The values of Cijl’s

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software selection for SMEs. Based on the case study findings, this paper proposes the following values for A2 to A5 in the proposed model used for a SME: A2 ¼ 5; A3 ¼ 4; A4 ¼ 7; A5 ¼ 6:

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References Al-Mashari, M. and Al-Mudimigh, A. (2003), “ERP implementation: lessons from a case study”, Information Technology & People, Vol. 16 No. 1, pp. 21-33. Baki, B. and C¸akar, K. (2005), “Determining the ERP package-selecting criteria: the case of Turkish manufacturing companies”, Business Process Management Journal, Vol. 11 No. 1, pp. 75-86. Bernroider, E. and Koch, S. (2001), “ERP selection process in midsize and large organizations”, Business Process Management Journal, Vol. 7 No. 3, pp. 251-7. Hwang, C.L. and Yoon, K. (1981), Multiple Attribute Decision Making, Springer, Berlin. Lee, W.J. and Kim, S.H. (2001), “An integrated approach for interdependent information system project selection”, International Journal of Project Management, Vol. 19, pp. 111-8. Ptak, C.A. (2000), ERP Tools, Techniques, and Applications for Integrating the Supply Chain, St Lucie Press, Delray Beach, FL. Ravarini, A., Tagliavini, M., Pigni, F. and Sciuto, D. (2000), “A framework for evaluating ERP acquisition within SMEs”, paper presented at AIM International Conference, Montpellier, November. Saaty, T.L. (1990), Decision Making for Leaders, RWS Publications, Pittsburgh, PA. Santhanam, R. and Kyparisis, G.J. (1995), “A multiple criteria decision model for information system project selection”, Computers & Operations Research, Vol. 22 No. 8, pp. 807-18. Santhanam, R. and Kyparisis, G.J. (1996), “A decision model for interdependent information system project selection”, European Journal of Operational Research, Vol. 89, pp. 380-99. Teltumbde, A. (2000), “A framework of evaluating ERP projects”, International Journal of Production Research, Vol. 28, pp. 4507-20. Verville, J. and Halingten, A. (2003), “A six-stage model of the buying process for ERP software”, Industrial Marketing Management, Vol. 32, pp. 585-94. Wang, M.J. and Wei, C.C. (2002), “A multi-criteria model for ERP project selection”, Proceeding of Computers & Industrial Engineering Conference. Wei, C-C., Chien, C-F. and Wang, M.J. (2005), “An AHP-based approach to ERP system selection”, International Journal of Production Economics, Vol. 96 No. 1, pp. 47-62. Wei, C.C. and Wang, M.J. (2004), “A comprehensive framework for selecting an ERP system”, International Journal of Project Management, Vol. 22, pp. 161-9. Yao, Y. and He, H.C. (2000), “Data warehousing and the internet’s impact on ERP”, IT Pro, March/April, pp. 37-41. Yusuf, Y., Gunasekaran, A. and Abthorpe, M.S. (2004), “Enterprise information systems project implementation: a case study of ERP in Rolls-Royce”, Journal of Production Economics, Vol. 87, pp. 251-66. Further reading Beretta, S. (2002), “Unleashing the integration potential of ERP systems: the role of process-based performance measurement systems”, Business Process Management Journal, Vol. 8 No. 3, pp. 254-77.

Boykin, R.F. and Martz, W.B. Jr (2004), “The integration of ERP into a logistics curriculum: applying a systems approach”, Journal of Enterprise Information Management, Vol. 17 No. 1, pp. 45-55. Okrent, M.D. and Vokurka, R.J. (2004), “Process mapping in successful ERP implementations”, Industrial Management & Data Systems, Vol. 104, pp. 637-43. Schniederjans, M.J. (2003), “Implementing enterprise resource planning systems with total quality control and business process reengineering: survey results”, International Journal of Operations & Production Management, Vol. 23 No. 4, pp. 418-29. Themistocleous, M., Irani, Z. and O’Keefe, R.M. (2001), “ERP and application integration: exploratory survey”, Business Process Management Journal, Vol. 7 No. 3, pp. 195-204. Corresponding author Mohsen Ziaee can be contacted at: [email protected]

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