Gregory A. Graman

A partial-postponement decision cost model

A number of factors, including product proliferation and increased customer service-level requirements, have led many companies to consider adopting postponement as a supply chain strategy. Packaging postponement is the process of delaying packaging of a common item into a final product configuration until the customer order is received. For a given product, a portion of demand is known with a high level of certainty and would not benefit from postponement. The remaining portion of demand is known with little certainty and would benefit from delaying the differentiating stage of the operation until demand is known. We develop a single-period, two-product, order-up-to cost model to aid in setting the levels of finished-goods inventory and postponement capacity. Minimum-cost optimal solutions to inventory levels and capacity are obtained by solving the derived analytical expressions using a non-linear programming formulation. We examine the sensitivity of the model to different levels of the model parameters to generate managerial insights beyond those of previous work. We show that changing product value, packaging cost, cost of postponement, holding cost, fill rate, and demand correlation can decrease expected total cost and increase postponement capacity.

Implementation issues influencing the decision to adopt postponement

Purpose – Postponement (also known as delayed product differentiation) has been shown to be an effective supply chain strategy from an inventory‐reduction, service‐level improvement standpoint. However, there has been relatively little empirical research on identifying the drivers and/or obstacles to a successful implementation of a postponement strategy. This study aims to identify the importance of several managerial issues surrounding the implementation of such a strategy.Design/methodology/approach – Exploratory depth interviews with company managers were conducted to identify and examine issues that may affect a successful implementation. Borrowing from the concept of triangulation, the findings are integrated with results reported elsewhere in the literature to understand the interrelated aspects of postponement implementation issues. This approach provides insights that would not be had if the results of each study were viewed independently of one another.Findings – The identification of managerial...

Costs of quality and maintenance: Improvement approaches

The inclusion of maintenance-related costs in an organisations financial reports, through the analysis of the costs of maintenance, helps management evaluate the relative impact of its maintenance problems on the organisations profitability. A cost of quality (COQ)/cost of maintenance (COM) system, once implemented, provides us with an invaluable foundation for our efforts to improve the effectiveness of the maintenance function. This approach provides us with a common language for communication between top management and the maintenance function to draw attention to where management should provide resources to correct quality problems and make improvements. The system provides new channels for communication to share best practices and to coordinate the efforts of experts in quality management with those in maintenance to improve our understanding of the statistical capability and reliability of equipment.

Modelling the tradeoff between postponement capacity and forecast accuracy

The ability to offer rapid delivery of a wide variety of customised products requires companies to maintain high levels of product inventories to quickly respond to customer demands. One alternative for reducing final product inventories while providing the required customer service level is delayed product differentiation, known as postponement. This strategy, however, can result in significant costs of increasing capacity at the postponement stage. Another alternative is to improve forecast accuracy, resulting in costs associated with more sophisticated forecasting methodologies. In this study we model the costs associated with each alternative and the resulting reductions in inventory levels, while maintaining a constant service level. We illustrate the interaction between these variables using a numerical example motivated by our work with a local manufacturer of non-durable household goods. Our findings show that large cost differences can exist between the two strategies, and that these costs play a significant role in determining the best strategy. Also, the value of the product (through holding cost) sets a limit on the benefit that can be realised by either strategy. These results have important managerial implications that should be considered when making the postponement decision.

Impact of Bias Magnification on Supply Chain Costs: The Mitigating Role of Forecast Sharing

The impact of forecast error magnification on supply chain cost has been well documented. Unlike past studies that measure forecast error in terms of forecast standard deviation, our study extends research to consider the impact of forecast bias, and the complex interaction between these variables. Simulating a two-stage supply chain using realistic cost data we test the impact of bias magnification comparing two scenarios: one with forecast sharing between retailer and supplier, and one without. We then corroborate findings via survey data. Results show magnification of forecast bias to have a considerably greater impact on supply chain cost than magnification of forecast standard deviation. Particularly damaging is high bias in the presence of high forecast standard deviation. Forecast sharing is found to mitigate the impact of forecast error, however, primarily at higher levels of forecast standard deviation. At low levels of forecast standard deviation the benefits are not significant suggesting that engaging in such mitigation strategies may be less effective when there is little opportunity for improvement in accuracy. Furthermore, forecast sharing is found to be much less effective against high levels of bias. This is an important finding as managers often deliberately bias their forecasts and underscores the importance of exercising caution even with forecast sharing, particularly for forecasts that have inherently large errors. The findings provide a deeper understanding of the impact of forecast errors, suggest limitations of forecast sharing, and offer implications for research and practice alike. [web URL: http://onlinelibrary.wiley.com/doi/10.1111/deci.12208/full]

Outsourcing practices of Midwest US public universities

Universities face increased pressures to reduce and contain costs while simultaneously offering high-quality, non-core value-added services to their students, faculty and staff. The purpose of the study was to empirically assess whether and how various dimensions of the outsourcing process for non-core operations in higher education impact performance. Our findings suggest that there is wide disparity in the level of sophistication of outsourcing processes for non-core operations and their impact on performance measurement. The study revealed that organisational variables have an impact and direct relationship to operational revenue and cost. This study focused on Midwest US public universities in seven states.