Managing Spares Inventory Through Life Time Value Assessment


Author

Mohita Gangwar Sharma
Operations Management Area, FORE School of Management, New Delhi, India

Kashi N. Singh
Operations Management Area, Indian Institute of Management, Lucknow 226 013, India


Content

Spare Parts Management in capital equipment intensive industries is a critical differentiating factor. As we work in a resource crunch environment, we have changed the vantage point for spares management system in this study. Determining the value and usefulness of the spare parts and understanding which spare part is more valuable should guide us in committing resource. Instead of looking from the vantage point of the equipment where the spare is used this spare considers spare part as an investment based on its value. Real Option Analysis has been identified in the literature as a quantitative means to evaluate the flexibility inherent in the decision making process. By adopting a real options framework we develop a model that incorporates the demand uncertainty and the financial implications involved. The value derived in terms of asset utilization determines the viability of this investment. Thus, the concept of ‘Spares Life Time Value’ has been proposed based on an analogy from ‘Customer life time value’. In this model the contribution of spare part reduces to an argument which can be used for strategic insights and decision making. The concept has been illustrated through a case study on the issue of spare resource allocation

Keywords: Spare Parts Management, Real Option Analysis, Spare Part Classification

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We address the problem of spare parts management of capital intensive equipment like aircraft, engine, power plant etc. It has complex structures and the operating time of the equipment should be maximized so as to maximize the return on investments. One way to achieve high operational readiness (or availability) is to acquire enough spare parts. However, the spares are costly and it is seen that the investment in spare parts over the life of the equipment exceeds the investment made for the procurement of the capital goods many folds. Hence, the problem of spare inventory is critical and not a trivial issue.

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What is the need of a spare part? What is the worth of a spare part? What considerations should guide the spares provisioning decision or rather investment in spare parts? These questions need intense deliberations, if we are working in a resource crunch environment

In this study we have drawn an analogy to the marketing concept of “Customer Life Time Value” which is the optimal allocation of resources and efforts across various profitable customers to ensure cost effectiveness. Customer lifetime value of a customer for a firm is the net profit or loss to the firm, considering the transactions made throughout its entire life of that customer with that firm. Hence, the lifetime value of a customer for a firm is the net of the revenues obtained from that customer over the lifetime of transactions with that customer minus the costs, taking into account the time value of money (Berger and Nasr, 1998). This Customer Life Time Value framework has been utilized as the basis for customer selection and resource allocation (Jain and Siddhartha, 2002). It is also used to generate customer level strategies and optimize firm‟s performance especially for customer selection, customer segmentation, optimal resource allocation, purchase sequence analysis and targeting profitable prospects (Venkatesan and Kumar, 2004).

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We propose to utilize this as a classification tool to enable managers to make strategic discretionary decisions based on the consequentiality and the uncertainty involved. It is not possible to stock all items and so there should be a basis of ranking these spares which is based on the value contributed by the spare as 100% spares cannot be stocked. Value of a spare is based on the core benefits or the payoff and the likelihood of demand. We have tried to capture both these characteristics in our model. Real Option Analysis has been identified in the literature as a quantitative means to evaluate the flexibility inherent in the decision making process. By adopting a real options framework we develop a model that incorporates the demand and the financial uncertainties involved. The value derived from this asset in terms of asset utilization determines the viability of this investment. Although valuing options embedded in real life cases with the help of Black-Scholes Model is a systematic way of determining the value of an option but often it requires some assumptions. Our approach focuses on demand because the primary uncertainty lies with demand. In case the failure distribution happens to be different from the normal distribution, the likelihood of exercise can be determined for the given distribution and the value created can be determined. The base model can further be modified to address other aspects of spares management. As the B-S model is widely available even on calculators, widespread acceptability should not be an issue. This model could also be applied to other similar equipment intensive industries and the robustness of the model can be tested. The future research in this area would include adding complexity to this model by incorporating complex behavior of spare and environment influences. This model can also be used in determining the value of spare contracts and can contribute to assessing the material cost of performance based contracts.

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About Author

Mohita Gangwar Sharma is Associate Professor in Operations Management at FORE School of Management. She is an electrical engineer from IIT-BHU, Varanasi and Masters in International Business from IIFT-New Delhi. She obtained her doctorate from Indian Institute of Management (IIM) Lucknow, making seminal contribution in the area of Spare Parts Management. She is a recipient of the coveted N.T.S.E. Scholarship. She has worked in the transportation and power industry for 16 years. She has published in International journals and participated in National and International Conferences. She brings the rich experience of the industry and tough academic rigor to her research. Her current areas of research include Service Operations, Operations Strategy, Product Service Systems, Humanitarian Supply Chain, Sustainability

Kashi N. Singh is presently working as Professor in the Operations Management Area of the Indian Institute of Management, Lucknow. His areas of interest include: Operations Management, Supply Chain Management, Facility Location, and modeling of Production/Operations systems. Prof. Singh holds a Bachelor‟s degree in Mechanical Engineering from Patna University, and Master‟s and Doctoral degrees in Industrial Engineering & Management from Indian Institute of Technology, Kanpur and Asian Institute of Technology, Bangkok, respectively. Prof. Singh, a full professor of more than twenty four years‟ standing, has about forty years of teaching and research experience to his credit. Currently he is a member of POMS, a life member of SOM, a Fellow of the Institution of Engineers (India), a member of the Institute for Operations Research and the Management Sciences (INFORMS) and the Manufacturing & Service Operations Management (M&SOM) Society.