SUPPLIER EVALUATION OF LOGISTICS FACTORS AND THEIR CONTRIBUTION TO IMPROVED CUSTOMER SERVICE

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1 SUPPLIER EVALUATION OF LOGISTICS FACTORS AND THEIR CONTRIBUTION TO IMPROVED CUSTOMER SERVICE M. Muya 1, A. D. F. Price 2 and A. Thorpe 3 Department of Civil and Building Engineering, Loughborough University, Loughborough, Leicestershire, LE 11 3TU, UK Customer service is a central element that should draw together materials supply logistics,therefore, the performance of a materials supply chain should be assessed in terms of contribution to improved customer service. Such an assessment should highlight gaps between theory and practice, and consequently point to better approaches for addressing problems in materials supply chains. The paper presents a methodology for evaluating contributions of logistics elements to improved customer service in the supply of construction materials using the analytic hierarchy process (AHP). Evaluations by five major UK suppliers of the AHP model s ability to assess contributions of logistics elements to improvements in the supply of construction materials have been presented. Keywords: Construction materials, logistics, customer service, analytic hierarchy process INTRODUCTION Various authors have emphasised the importance of managing the supply of construction materials efficiently. Kerridge (1987) estimated that the supply of construction materials controls 80 per cent of the project schedule from initial materials acquisition to delivery of the last item. Construction materials have also been estimated to account for 30 to 80 per cent of the project installed cost depending on the type of project (Stukhart 1995; Muelhlhausen 1991; Kerridge 1987). Despite the high cost and significantly high influence of construction materials on construction schedules, the supply process of materials has many problems (Stukhart 1995, Thomas et al 1989; Borcheding et al 1981). From a synthesis of literature, Majid and McCaffer (1996) identified late delivery of materials as one of the critical factors that caused construction programme schedule delays. Other than cost savings that could be achieved from the cost of materials, improvements in materials supply can lead to an estimated six per cent increase in labour productivity (Business Roundtable 1983). Re-engineering materials management through the introduction of best practices such as fewer, high quality long-term supplier relationships, cross-functional involvement of personnel in different departments, purchasing and inventory management during supplier negotiations, Just-in-Time supplier contracts, supplier-owned inventory, introduction 1 M.Muya@lboro.ac.uk 2 A.D.F.Price@lboro.ac.uk 3 A.Thorpe@lboro.ac.uk Muya, M, Price, A D F and Thorpe, A (1998) Supplier evaluation of logistics factors and their contribution to improved customer service. In: Hughes, W (Ed.), 14th Annual ARCOM Conference, 9-11 September 1998, University of Reading. Association of Researchers in Construction Management, Vol. 2,

2 Muya, Price and Thorpe of electronic data interchange (EDI), payment upon receipt and other practices can help enterprises cut costs, enhance efficiency in their business processes and satisfy their customers (Bartoski 1995). This paper outlines results of research into materials supply logistics. The objective of the research was to determine, from experiences of major UK suppliers, the extent to which various logistics factors enabled their organisations to improve their levels of customer service in the supply of construction materials. This was achieved by using the analytic hierarchy process to determine percentage contributions of logistics factors (i.e. enablers) to improved customer service. MATERIALS SUPPLY LOGISTICS Muya et al (1997) adopted the logistics perspective of managing construction materials, arguing that such a viewpoint helps to capture elements which may be overlooked when the process is considered from a materials management viewpoint. A frequently cited operational definition of logistics was developed by the Council of Logistics Management and defined logistics as The process of planning, implementing and controlling the efficient effective flow and storage of raw materials, in-process inventory, finished goods, services and related information from point of origin to point of consumption (including inbound, internal and external movements) for the purpose of conforming to customer requirements (Coyle et al 1996). Logistics activities include: demand forecasting, requirements planning, purchasing, inventory management, warehousing, materials handling, industrial packaging, distribution planning, order processing, transportation and customer service (Coyle et al 1996). Probably the most important of all the logistics activities is customer service. All logistics activities should be efficiently managed to ensure the highest level of customer service at an optimum total cost. Achieving the highest level of customer service at an optimum cost of supplied materials involves trade-off decision making among the various logistics elements. The analytic hierarchy process (AHP) was proposed as an appropriate method for assessing, via trade-off analysis, factors that enable achievement of efficient and costeffective materials supply logistics to support construction (Muya et al 1997). RESEARCH METHODOLOGY The analytic hierarchy process is based on three main problem solving approaches: decomposition, comparative judgements and synthesis of priorities (Saaty 1983). Decomposition Decomposition involves breaking down a complex problem into its most specific elements and then structuring them into a hierarchy. Such structuring reduces a problem to manageable elements at lower levels and provides an efficient way of dealing with complexity. Using the AHP methodology, a decision model for evaluating the contribution of logistics factors to improved customer service was decomposed following the steps outlined in Figure 1. Logistics factors were classified into two groups: performance indicators and enablers. A logistics performance indicator was defined as a metric by which a supplier could be evaluated in satisfying customer requirements, and an enabler was defined as a characteristic which made it possible for a supplier to meet customer requirements. 360

3 Supplier evaluation of logistics factors Provide a clear definition of the problem and define a set of possible solutions Develop a top-down hierarchy model of the problem Obtain n(n-1)/2 pairwise comparison judgements of the the AHP model elements at each stratum with respect to each of the elements in the level just above Obtain priorities and measure consistency of the pairwise evaluations of all the stratum elements with respect to each of the elements in the level just above Perform hierarchical composition to generate overall priorities and consistency for laternative solutions Figure 1: Steps for formulating an Analytic Hierarchy Process model Logistics performance indicators identified from literature include delivery reliability, flexibility, lead time, value-added service and cost-effectiveness of the service provided (NEVEM-workgroup 1989; Korpela and Tuominen 1996). Enablers include: information and communication technologies such as EDI, bar codes and IDBMS; contractor-supplier relationships; quality management systems of suppliers such as Total Quality Management (TQM), Quality Control (QC) and Quality Assurance (QA); supplier s capability viewed in terms of financial strength, product technology, operational efficiency and experience; supplier s location in relation to a project; and supplier s quoted prices. Based on findings of preliminary interviews, it was also decided to include environmental and health records of suppliers as enablers because evidence suggested that these were increasingly being considered important in the evaluation and selection of suppliers. 361

4 Muya, Price and Thorpe OVERALL PURPOSE Improved Customer Service (Efficient and cost-effctive construction materials supply) PERFOMANCE INDICATORS PI1 Delivery reliability At right time, in right quantity and quality, without damage PI2 Flexibility Responsiveness to changing needs of customer PI3 Lead Time Time between placing order and receipt of order PI4 Cost-effectiveness Cost of products and level of service satisfactory to customer PI5 Value-added service Service exceeding basic requirements E N A B L E R S E1 Information and communication technologies.bar codes.dbms.edi E2 Relationships with suppliers Trust, Commitment, Open & honest communications E3 Quoted price of construction materials E4 Quality management system of supplier TQM, QA, QC E5 Location of supplier in relation to the project E6 Capability Financial strength, product technology, operation efficiency, experience E7 Management and administrative ability of supplier E8 Health & Safety record of supplier E9 Environmental record of supplier Figure 2: Analytic Hierarchy Model for construction materials supply logistics 362

5 Supplier evaluation of logistics factors Based on literature review, preliminary interviews and two questionnaire surveys, one sent to UK contractors and the other to UK construction materials suppliers, the AHP model for evaluating contributions of logistics performance indicators, and through them, contributions of enablers towards improved customer service was decomposed as shown in Figure 2. The rationale of the model is that customer satisfaction in delivery of construction materials depends on the influence of each of the identified performance indicators on customer satisfaction. Optimisation of performance indicators is affected by an array of factors that have been referred to as enablers. Through their contribution to performance indicators, enablers can thus be regarded as the critical success factors which impact upon improved customer service, and consequently its derivative, customer satisfaction in the delivery of construction materials. After decomposing the problem, the next step was to solicit for comparative judgements from industry experts. Comparative judgements The 9-point scale given in Table 1 is commonly used for making numerical judgements in AHP pairwise comparisons (Saaty 1983) and was used in this research. Using the scale, measurement is accomplished by asking the decision-maker to exercise judgement about the dominance of each element at a given stratum over the other elements at the same level with respect to each goal at the next higher level. Table 1: The AHP response scale Intensity of Importance Definition Explanation 1 Equal importance Two activities contribute equally to the 3 Weak importance of one activity over another objective Experience and judgement slightly favour one activity over another 5 Essential or strong importance Experience and judgement strongly favour one activity over another 7 Demonstrated importance An activity is strongly favoured and its dominance is demonstrated in practice 9 Absolute importance The evidence favouring one activity over another is of the highest order of affirmation 2, 4, 6, 8 Intermediate values between the two When compromise is needed Reciprocals of judgments judgements If activity i has one of the above numbers assigned to it when compared to j, then j has the reciprocal value when compared to i. Evaluations of the model in Figure 2 were performed using Expertchoice installed on a lap-top computer. The model evaluation process was initially pre-tested by two stand-in experts and appropriate changes were made following their suggestions before soliciting for judgements from suppliers. From a prior questionnaire survey of construction materials suppliers, five companies had agreed to take part in subsequent phases of the research programme. Consequently, model evaluation interviews with individuals in the five organisations took place according to the schedule in Table

6 Muya, Price and Thorpe Table 2: Schedule for evaluation of AHP model by construction materials suppliers Interviewee Supplier identity and interview date Type of company and products dealt in Position in company Experience in construction industry S1 15 Jan 98 S2 20 Jan 98 S3 22 Jan 98 S4 27 Jan 98 S5 2 Feb 98 Manufacturer/supplier/subcontractor Coated roadstone, sand & gravel, hardstone Supplier/subcontractor Aggregates, ready-mixed concrete, concrete blocks, precast concrete products, contracting services Distributor Insulation and related products Manufacturer/supplier Beams, columns, sheets & bearing pilings and other streel products used in construction Manufacturer/supplier Ready-mixed concrete and general quarry products such as sand and aggregates CUSTOM ER SERVICES MANAGE R Business Services Manager Marketing Executive General Manager for Marketing and Planning Marketing and Public Affairs Manager 22 years 4 years 9 years 26 years 20 years The model evaluation process followed the stages outlined in Figure 3. A brief introduction of Expertchoice was given to each interviewee at the outset of each interview. Each of the interviewees then evaluated the model following the steps outlined in Figure 3. Evaluation interviews took between one to one and a half hours each. Synthesis of priorities Contributions of logistics performance indicators and consequently enablers to efficient and cost-effective construction materials supplies were next synthesised in the presence of the interviewee after the evaluation. Arriving at priorities or weights of elements involves calculating eigenvalues of matrices constructed from pairwise comparisons of the elements. The whole synthesis process to arrive at prioritisation of elements was performed using Expertchoice Consistency test Consistency tests to assess the quality of the judgements were also performed via Expertchoice at the time priorities of elements were synthesised. Consistency in AHP is obtained by calculating the consistency ratio (Saaty (1983) outlines the details). Judgements yielding an inconsistency ratio above ten per cent are undesirable and call for revision. Overall evaluation Evaluations of the AHP model by the five supplier organisations resulted in prioritisation by individual companies of both logistics performance indicators and enablers displayed in Tables 3 and 4 respectively. Overall priorities of the elements were obtained by entering into the model geometric means of pairwise comparison judgements of all the five companies. 364

7 Supplier evaluation of logistics factors INTRODUCTION OF EXPERTCHOICE TO INTERVIEWEE Brief explanation & demonstration of AHP model evaluation procedure using expertchoice on a lap-top computer ACTUAL MODEL EVALUATION BY INTERVEWEE Phase I Pairwise comparisons of performance indicators w.r.t. Goal of Improved Customer Service Pairwise comparison of performance indicator PI1 against performance indicators PI2, PI3, PI4 & PI5 w.r.t. Improved Customer Service; then pairwise comparison of PI2 against, PI3, PI4 & PI5 w.r.t. Improved Customer Service; then pairwise comparison of PI3 against PI4 & PI5 w.r.t. Improved Customer Service ; and finally pairwise comparison of PI4 against PI5 w.r.t. Improved Customer Service, checking consistency each time and revising judgements if necessary Phase II Pairwise comparisons of enablers w.r.t. performance indicators Pairwise comparison of enabler E1 against enablers E2, E3, E4, E5, E6, E7, E8 & E9 w.r.t. PI1; and then pairwise comparison of E2 against E3, E4, E5, E6, E7, E8 & E9 w.r.t. PI1;...; and then pairwise comparison of E8 against E9 w.r.t. PI1. Then pairwise comparison of E1 against E2, E3, E4, E5, E6, E7, E8 & E9 w.r.t. PI2;...; up to pairwise comparison of E8 against E9 w.r.t. PI2. The evaluation cycles continue until pairwise comparison of E8 against E9 w.r.t. PI5, checking consistency each time and improving it by revising judgements if necessary. Figure 3: Steps followed during AHP model evaluation interviews Geometric means of the judgements were calculated using the formula (Saaty 1996): GM = (S1x S2 x S3 x S4 x...x Sn) 1/n Where: GM = geometric mean n = number of companies Sn = pairwise comparison judgement by supplier Sn The resulting geometric means were rounded off to the nearest whole number. Then overall priorities and corresponding inconsistency ratios were derived by entering the geometric means of all the elements in the original model in Expertchoice. RESULTS Evaluations of the AHP model yielded inconsistency ratios less than or equal to 10 per cent, giving results with admissible inconsistency (Tables 3 and 4). Logistics performance indicators Table 3 shows percentage contributions of performance indicators to Improvements in customer service. Interviewed suppliers regarded reliability as the most important indicator by which supplier performance in improving service levels to their customers can be measured. This indicator was estimated to contribute 39.4 per cent to improved customer service, with assessments by individual interviewees ranging between 21.1 to 42.7 per cent. Cost-effectiveness of the service provided was regarded as the second most important measure of performance, and was assessed to 365

8 Muya, Price and Thorpe contribute 27.2 per cent to improved customer service. Contributions to improved customer service by this indicator was assessed by individual interviewees to range between 9.7 and 57.5 per cent. The third most important measure of performance in the levels of customer service provided by suppliers was flexibility. It was assessed to contribute 15.3 per cent with individual interviewee assessments ranging between 4.4 and 38.1 per cent. With an overall contribution of 10.8, lead time provided by suppliers was ranked fourth in importance in contributing to improved customer service. Assessments by individual interviewees of contributions to improved levels of customer service by this indicator ranged between 5.2 and 18.8 per cent. Value-added service was the least ranked performance indicator and overall, it was assessed to contribute 7.3 per cent to improved customer service. Contribution assessments by individual interviewees ranged between 2.8 and 22.1 per cent. Table 3: Suppliers perceived percentage contribution of logistics performance to efficient and cost-effective construction materials supplies Indicator Supplier Overall S1 S2 S3 S4 S5 evaluation (%) (%) (%) (%) (%) (%) Reliability Cost-effectiveness Flexibility Lead time Value-added service Inconsistency ratio Enablers Table 4 is a display of assessed contributions of enablers to improved customer service. From their evaluations, experience of interviewed experts suggested that through higher contribution to reliability, cost-effectiveness, flexibility, improved lead times and value-added service, improved contractor-supplier relationships held the greatest potential for improving the level of customer service offered by construction materials suppliers. This enabler was estimated to contribute 18.2 per cent to improved customer service, with assessments from individual interviewees ranging between 14.8 and 17.3 per cent. The interviewed suppliers considered offering a better price to their customers as the second most important factor which enabled them improve their customer service levels and was estimated to have a contribution of 15.3 per cent. Individual interviewee assessments of the contribution of price to improved customer service ranged between 9.6 and 25.4 per cent with the greatest contribution being towards cost-effectiveness. Thus, interviewed suppliers recognised the need to maintain low prices in order to satisfy their customers. Other traditional factors such as management and administrative ability of suppliers, capability of suppliers, location of suppliers in relation to projects and their quality management systems were also assessed to have significant influence on the levels of service offered by suppliers. Management and administrative ability of suppliers was assessed to have 13.3 per cent contribution with individual interviewee s estimations ranging between 5.7 and 14.9 per cent. Capability and location were each assessed to contribute 12.9 per cent to improved customer service. Individual interviewees assessments ranged between 5.3 and 17.1 per cent contribution for capability while for location between 1.8 and 32.2 per cent. Tables 2 and 3 show that all the companies, 366

9 Supplier evaluation of logistics factors except the one which dealt in steel products, took location to be of very high significance in contributing to improved customer service. Quality management systems were assessed to contribute 12.7 per cent to improved customer service, with individual interviewee assessments for this enabler ranging between 8.1 and 16.9 per cent. Perceptions of the interviewed suppliers were that use of information and communication technologies such as bar codes, EDI and IDBMS did not have much significance in improving customer service, with a contribution of only 7.7 per cent. The interviewed suppliers also did not consider health and safety, and environmental records of suppliers to have direct bearing in improving efficiency and costeffectiveness in the supply of construction materials, both factors having been assessed to have 3.5 per cent contribution to improved customer service. Table 4: Suppliers perceived percentage contribution of enablers to efficient and cost-effective construction materials supplies Enabler Supplier Overall S1 S2 S3 S4 S5 evaluation (%) (%) (%) (%) (%) (%) Relationships Price Mgmt & admin ability Capability Location Quality management Info & Comm. tech Health & Safety records Environmental records Inconsistency ratio CONCLUSIONS The focus of logistics management is superior customer service. Ensuring efficient construction materials supply involves complex trade-off decision-making among many factors which all contribute to improved customer service. The AHP has been presented and used to quantify, based on opinions of experts, contributions of supplier characteristics which enhance efficiency and cost-effectiveness in materials supply logistics. Overall, the suppliers determined that improved contractor-supplier relationships contributed most to all the performance indicators: reliability, cost-effectiveness, flexibility, lead time and value-added service and consequently were assessed to be the most important enabler in improving customer service in the supply of construction materials. Price was considered to be the second most important enabler in satisfying customer requirements, especially through cost-effectiveness of the products or services provided by suppliers. Other traditional factors such as management and administrative ability of suppliers, capability of suppliers, location of projects in relation to projects and their quality management systems were also assessed to have significant influence on the levels of service offered by suppliers. However, the interviewees, probably from lack of experience, did not regard use of information and communication technologies such as bar codes, electronic data interchange and integrated database management systems in 367

10 Muya, Price and Thorpe materials supply logistics to have significant contribution to improvements in customer service. Health and safety, and environmental records of suppliers were also not regarded to have much direct bearing on improvements in customer service in construction materials supply logistics. REFERENCES Bartoski, M. (1995) Re-engineering to be the best. APICS: Performance Advantage, 5(7), Coyle, J.J., Bardi, E.J. and Langley, C.J. (1996) The management of business logistics. 6ed. Western Publishing Company. Kerridge, A.E. (1987) Manage materials effectively. Hydrocarbon Processing, May, Korpela, J. and Tuominen, M. (1996) Logistics performance with an application of the analytic hierarchy process. IEEE Transactions on Engineering Management, 43(3), Muehlhausen, F.B. (1991) Construction site utilisation: impact of material movement and storage on productivity and cost. AACE Transactions, L.2.1-L.2.9. Muya, M., Price, A.D.F. and Thorpe, A. (1997) Construction materials supply logistics. ARCOM 97 Conference Proceedings, 1, NEVEM-workgroup (1989) Performance indicators in logistics. IFS Publications Saaty, T.L. (1996) Decision making for leaders: the analytic hierarchy process for decisions in a complex world. Pittsburgh, RWS Publications. Saaty, T.L. (1993) Priority setting in complex problems. IEEE Transactions on Engineering Management, EM-30(3), Stukhart, G. (1995) Construction Materials Management. Marcel Dekker. Thomas, H.R., Sanvido, V.E. and Sanders, S.R. (1989). Impact of materials management on productivity: a case study. Journal of Construction Engineering and Management, 13(3), Majid, M.Z.A. and McCaffer, R. (1996) Critical factors that influence schedule performance. Productivity in Construction: International Experiences. Second International Congress on Construction, The Business Roundtable (1983) More construction for the money: summary of the construction industry cost effectiveness project. 368