Neil Smith

1. SALES FORECAST SHOPS WAREHOUSE SPAIN WAREHOUSE CHINA REPLENISHMENT Sales Forecasting & Replenishment for a Medium-sized Toy Retailer Students: Carolina Ruiz, ZLOG 2010 Neil Smith, ZLOG 2010 Advisors: Professor Mozart Menezes Lecturer Alejandro Serrano Motivation / Background Methodology • The following methodology is proposed to evaluate the research hypothesis. • 1) Develop an understanding of the client’s business model and how it is supported by the supply chain • 2) Analyze the client’s current forecasting and replenishment models to understand problems and identify opportunities for improvement • 3) Visit retail locations to develop a better understanding of the role of a shop manager in the forecasting and replenishment processes • 4) Complete a literature review of sales forecasting and replenishment models and strategies • 5) Obtain client sales data and select a subset of shops and products on which to base algorithm development • 6) Develop and validate a shop-product level sales forecasting algorithm • 7) Develop and validate an optimal shop replenishment algorithm based on sales forecasts • 8) Define a methodology that the client can use to extend algorithms to additional shops and products The client is a medium-size retail toy brand with more than 300 shops in 29 countries. Distributing thousands of products to shops across a large retail footprint while maintaining high customer service levels is a significant source of supply chain costs. The Problem Key Question / Hypothesis Expected Contribution The client faces a combination of supply chain challenges that are unique to their business model. Complicating Factors • Shops are distributed across four continents • Approximately 1,000 products stocked at each retail shop • New product collections released twice each year • High demand uncertainty exists for new products • Seasonal demand patterns • Small retail locations provide little stockroom space for inventory • High variation in replenishment lead times across the retail footprint • Few channels for shops to return unsold merchandize • Commitment to a 99% customer service level Can a global toy retailer increase its supply chain surplus by improving shop-product level sales forecasts and developing optimal shop replenishment parameters? • Potential Benefits for the Client • Reduction in the number of retail stock outs • Decrease in inventory of unsold merchandize in shops • More balanced distribution of inventory across all retail locations • Definition of an optimal customer service level for each product • Decrease in the uncertainty of shop replenishment order size and frequency • Increase in supply chain surplus • General Benefits • Forecasting and replenishment methodology is relevant to many medium-size, global retailers • Opportunity to test and critique current research on forecasting and replenishment models Relevant Literature * Fisher, Marshall L. (1997) ‘What is the right supply chain for your product?’. Harvard Business Review, Vol. 75. * Johnson, M. Eric (2001) ‘Learning from toys: Lessons in managing supply chain risk from the toy industry’. California Management Review, Vol. 43. • Petrovic, Radivoj and Dobrila (2001) ‘Multicriteria ranking of inventory replenishment policies in the presence of uncertainty in customer demand’. Harvard Business Review, Vol. 75. * Silver, Edward A. Inventory Management and Production Planning and Scheduling. Wiley. • * Yew Wong, Chee. ‘What is the right supply chain for your product?’. Emerald, 356: 378. Carolina Ruiz Neil Smith