Helping Managers Manage

Do conventional management accounts help managers manage? This paper argues that the answer to this question is ‘No’, primarily because conventionally prepared budgets are not accepted by managers as valid measures of performance as a result of either forecasting errors in the data used in the original budget or weaknesses in the simulation algorithms inherent in the budget. The paper then suggests that management accounts can be made more meaningful by incorporating within the management accounting system a ‘resource management system’, the basis of which is a powerful simulation model.     

Finance and Accounts for Managers

Journal of the Operational Research Society -     

Estimating staffing requirements at an airport terminal

The paper reports on the derivation of a procedure for the estimation of immigration staffing requirements at an international airport terminal to meet a given processing time target. The procedure is based on simplifying and streamlining a detailed event based stochastic simulation of passenger arrivals, so that the simpler mainly deterministic time based simulation can be embedded in an iterative algorithm to produce approximate staffing requirements. The original model can then be used to check and refine the roster. Implementation is under Microsoft Windows on a 486 PC computer and the system is currently used by the Airport Company to evaluate proposed landing schedules.     

Modeling customer impatience in a newsboy problem with time-sensitive shortages

Customers across all stages of the supply chain often respond negatively to inventory shortages. One approach to modeling customer responses to shortages in the inventory control literature is time-dependent partial backlogging. Partial backlogging refers to the case in which a customer will backorder shortages with some probability, or will otherwise solicit the supplier’s competitors to fulfill outstanding shortages. If the backorder rate (i.e., the probability that a customer elects to backorder shortages) is assumed to be dependent on the supplier’s backorder replenishment lead-time, then shortages are said to be represented as time-dependent partial backlogging. This paper explores various backorder rate functions in a single period stochastic inventory problem in an effort to characterize a diversity of customer responses to shortages. We use concepts from utility theory to formally classify customers in terms of their willingness to wait for the supplier to replenish shortages. Under mild assumptions, we verify the existence of a unique optimal solution that corresponds to each customer type. Sensitivity analysis experiments are conducted in order to compare the optimal actions associated with each customer type under a variety of conditions. Additionally, we introduce the notion of expected value of customer patience information (EVCPI), and then conduct additional sensitivity analyses to determine the most and least opportune conditions for distinguishing between customer behaviors.     

A fuzzy inventory model without shortages using triangular fuzzy number

In business and industry it becomes very difficult for a manager to take concrete decision regarding inventory, as the data available to him are not always certain. Because uncertainty arises in demand, set-up resources & capacity constraints of an inventory planning system, it could be more justified to consider these factors in an elastic form. Therefore, with these uncertain data, fuzziness can be applied and the problem of inventory can be controlled. In the present paper, an inventory model without shortage has been considered in a fuzzy environment, by considering real-life data from the LPG store of Banasthali University. Triangular fuzzy numbers have been used to consider the ordering and holding costs. For defuzzification, signed-distance method has been used to compute the optimum order quantity.