American Journal of Industrial and Business Management, 2013, 3, 39-42 http://dx.doi.org/10.4236/ajibm.2013.36A005 Published Online October 2013 (http://www.scirp.org/journal/ajibm) 39 Analytical Models for Delivery Performance of a Supplier or a Service Provider M. Chandra Paul 1 , A. Vinaya Babu 2 , D. Mallikarjuna Reddy 3 , Malla Reddy Perati 4* 1 Department of Computer Science, Kakatiya University, Warangal, India; 2 Department of Computer Science Engineering, Jawaharlal Nehru Technological University, Hyderabad, India; 3 Department of Mathematics, GITAM School of Technology, Hyderabad Cam- pus, Hyderabad, India; 4 Department of Mathematics, Kakatiya University, Warangal, India. Email: mcpaul1@yahoo.com, * mperati@yahoo.com Received August 8 th , 2013; revised September 10 th , 2013; accepted September 17 th , 2013 Copyright © 2013 M. Chandra Paul et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT Delivery performance has evolved as an important metric in total quality management of an organization accredited with Lean Six Sigma and Capability Maturity Model (CMM) levels. Two analytical models are used to compute the delivery performance of an organization. One is deterministic and based on the number of days taken for the delivery and other is probabilistic and based on various stages of the product development which follow exponential distribution. For the second one cost effective analysis is made. This kind of analysis is very useful in the customer selection and appraisal of employee’s performance. Keywords: Delivery Performance; Lean Six Sigma; Capability Maturity Model; Exponential Distribution; Incomplete Gamma Distribution; Expected Penalty Cost 1. Introduction Lean Six Sigma is a powerful cost effective and waste reduction process. For several years, it has been a good practice in both private and public market driven organi- sations. It is equally applicable in manufacturing industry and IT sector. Lean sigma has three components: 1) Six Sigma tools, 2) values and leadership and 3) customer oriented. These components are to guarantee the quality of service (QoS). On the other hand, capability maturity model (CMM) is a time tested framework to improve product quality in IT sector. There are five levels of CMM consisting of several key process areas (KPA’s). One KPA at level 2 is supplier agreement and manage- ment to achieve the schedule. One of the Lean Sigma tools is 7 types of waste. One of these is waiting, for example, waiting for the request or specifications from the customer. Both frameworks Lean Sigma and CMM reveal that delivery performance plays an important role in total quality management (TQM) of an organization. According to the seminal study of Dickson [1], delivery performance is the third critical success factor (CSF) after quality and price. In the domain of supply chain management, delivery performance is cited as an impor- tant metric for supporting operational excellence of sup- ply chain [2], and it is classified as a strategic level per- formance measure by Ganasekaran et al. [3]. In this di- rection, there are some empirical studies by da Silveira and Arkader [4], and Iyer et al. [5]. Above studies are confined to the domain of supply chain management. In the paper [6], cost effective analysis is made even for early delivery, because of inventory holding cost. This is not the case in the IT sector. In this paper, we employ two models, one is the deterministic model and other is the probabilistic model. In the first case, delivery per- formance depends on just number of days delayed. In the second case, delivery performance is probabilistic, it de- pends on the various stages of the product, and each stage follows an exponential distribution. The rest of the paper is organized as follows: In Sec- tion 2, the deterministic model for delivery performance is employed. In Section 3, the probabilistic model for delivery performance is developed. Finally, numerical results and conclusions are given in Section 4. 2. Deterministic Model In this section, we apply the formula [7] to compute over all delivery performance of a team. The following pro- * Corresponding author. Copyright © 2013 SciRes. AJIBM