A Decision Support Tool (DST) for Inventory Management

Loss of customer goodwill is one of the greatest losses a business organization can incur. One reason for such a loss is stock outage. In an attempt to solve this problem, an overstock could result. Overstock comes with an increase in the holding and carrying cost. It is an attempt to solve these twin problems that an economic order quantity (EOQ) model was developed. Information on fifteen items comprised of 10 non-seasonal and 5 seasonal items was collected from a supermarket in Ikot Ekpene town, Nigeria. The information includes the quantity of daily sales, the unit price, the lead time and the number of times an item is ordered in a month. Based on this information, a simple moving average and y-trend method of forecasting were used to forecast the sales quantity for the following month for the non-seasonal and seasonal items. The forecast value was used to compute the EOQ for each of the items. Different scenarios were created to simulate the fuzzy logic EOQ after which the result of the conventional method, EOQ method, and fuzzy EOQ methods were obtained and compared. It was revealed that if the EOQ method is adopted, savings of 43% of holding and carrying cost would be made. From the scenarios of a fuzzy EOQ, a savings of 35.65% was recorded. It was however observed that in a real-life situation, the savings on a fuzzy EOQ is likely to be higher than that of an EOQ considering the incessant public power outages and the increase in transportation fares due to the high cost of fuel and the bad state of roads in Nigeria. To this end, a Decision Support Tool (DST) was developed to help the supermarket manage its inventory based on daily predictions. The DST incorporates a filter engine to take care of some emotional and cognitive incidences within the environment.

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The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods

BioMed Research International ◽

10.1155/2017/6353510 ◽

2017 ◽

Vol 2017 ◽

pp. 1-13 ◽

Cited By ~ 4

Author(s):

Taran Skjerdal ◽

Andras Gefferth ◽

Miroslav Spajic ◽

Edurne Gaston Estanga ◽

Alessandra de Cecare ◽

...

Keyword(s):

Decision Support ◽

Food Safety ◽

Real Life ◽

Decision Support Tool ◽

Integrated Approach ◽

End Users ◽

Limit Values ◽

Process Step ◽

Support Tool ◽

Starting Point

A prototype decision support IT-tool for the food industry was developed in the STARTEC project. Typical processes and decision steps were mapped using real life production scenarios of participating food companies manufacturing complex ready-to-eat foods. Companies looked for a more integrated approach when making food safety decisions that would align with existing HACCP systems. The tool was designed with shelf life assessments and data on safety, quality, and costs, using a pasta salad meal as a case product. The process flow chart was used as starting point, with simulation options at each process step. Key parameters like pH, water activity, costs of ingredients and salaries, and default models for calculations ofListeria monocytogenes, quality scores, and vitamin C, were placed in an interactive database. Customization of the models and settings was possible on the user-interface. The simulation module outputs were provided as detailed curves or categorized as “good”; “sufficient”; or “corrective action needed” based on threshold limit values set by the user. Possible corrective actions were suggested by the system. The tool was tested and approved by end-users based on selected ready-to-eat food products. Compared to other decision support tools, the STARTEC-tool is product-specific and multidisciplinary and includes interpretation and targeted recommendations for end-users.

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