Identify data resources: The process of data collection begins with a feasibility assessment. A fairly detailed specification of data is required to formulate or fit the analytical technique. For situations when data are extremely difficult to collect or when the necessary level of accuracy is unknown, sensitivity analysis can be used to identify data collection requirements. For e.g. an initial analysis may be completed using transportation costs estimated with distance – based regressions. The types of data required in a logistical design n study can be divided into three classes: business assumptions, management assumptions and analysis assumptions. The majority of data required in a logistical study can be obtained from internal records. Although considerable searching may be needed, most information is generally available.

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–        The first major data category is sales and customer orders. The annual sales forecast and percentage of sales by month, as well as seasonality patterns are necessary for determining logistics volume and activity levels. Historical samples of customer order invoices are also needed to determine shipping patterns by market and shipment size. The combination of aggregate measures of demand and detailed order profiles of projects the requirements that the logistics system must be capable of satisfying. Specific customer data are also required to consider the cost and time associated with moving the products across distance. Customers and markets ate often aggregated by location, type, size, order frequency, growth rate, and special logistical services to reduce analysis complexity.

–            For integrated channel analysis, its necessary to identify and track the costs associated with manufacturing and purchasing. It’s often necessary to consider the number and location of plants, product mix, production schedules and seasonality. Identification of policies and costs associated with inventory transfer, reordering, and warehouse processing, inventory control rules and product allocation procedures. For each of the current and the potential warehouse, the operating costs, capacities, product mix, storage levels and service capabilities should be established.

–            Transportation data requirements

Transportation data requirements include the number and type of modes utilized, modal selection criteria, rates and transit times, and shipping rules and policies.

For most logistics analysis applications, a select amount of future market data is useful for evaluating future scenarios. Although the management may be able to prepare a consolidated sales forecast it is difficult to prepare a market-by-market projection of sales. There can be two solutions to this problem.

 

1. Usage of demographic projections that correlate highly with sales can help the company to estimate future demand levels and hence determine future logistics requirements. Secondary data published by various government agencies can also provide a data bank of environmental information

 

2. Keeping a watch on the competitors strategies and capabilities by documenting competitive logistical system designs and flows can be helpful in providing competitive benchmarks that compare customer service capabilities, distribution networks and operating capabilities.

 

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