Supply chain may be designed both at the strategic and at the operational levels. The strategic level model decides the basic structural configuration of the supply chain whereas the operational level model controls the day-to-day activities of the supply chain. For designing the supply chain models, considerable data is required because of the complex structure of supply chain. Efficacy of the model depends upon the accuracy and reliability of the data used for solving the model. The data may be collected from numerous sources i.e., either directly from the industry or through survey instruments depending on the type of data required. The objectives of the paper are: (1) to provide a focused review of literature on data collection methods for supply chain design, and (2) to discuss the problems faced in data collection and some suggestions to overcome the problems.

Most of the firms do not have a formal system that specifically generates data needed for planning function. Because of this, researchers have to collect the needed data from different sources both internal and external to the firm. Primary sources of such data include standard operating statements, accounting reports, published information, industry websites and judgment, etc. Standard operating statements are the rich source of data required for planning. These documents includes sales orders, freight bills etc. From sales orders the data that may be extracted are: customer location, product sales level, shipment sizes, stock status, order fill rate and customer service level, etc. From freight bills, data related to shipment charges and the mode of transportation, etc. may be extracted. Accounting reports are also rich source of data and mainly focus on operating costs. These costs may include inventory holding costs, fixed costs of plants and inventory handling costs etc. Published information which is available from outside the company is also a rich source of data. Trade magazines, government sponsored research reports and academic journals are some examples of sources of information on costs and industry trends. Executives within the firms, consultants to the firms, sales staff, operating personnel and suppliers to the firm, all represent data sources. The literature on the data collection methods has been reviewed and presented below.

Lambert and Cooper (2000) [13] collected the supply chain related data for addressing the conceptual issues in supply chain management in order to properly understand supply chain management (SCM). The methodology for collecting the data was in-depth interviews with managers representing various levels in companies covering different supply chains. The functions represented by those interviewed included marketing/sales, logistics, manufacturing, information systems, finance, quality management, and strategic planning.

Management Research Journal, Supply Chain Data Collection Methods, Supply Chain Management, SCM, Quality Management, Strategic Planning, Production Management, Mathematical Programming Approach, Production Management, Industrial Marketing Management, Total Quality Management, Logistics Management.