Consider the Importance of Forecasting for the Global Supply Chain of a Retail Food Company

Forecasting is a management planning tool which is aimed at coping with future uncertainties, depending by and large on data of past and present as well as trend analysis (Chopra & Meindl 2010). The core characteristics of todays forward facial expression supply twines is flexibility and agility which utilises forecast, as one of the or so kindled planning forms of supply chain strategies to provide the needed qualification to quickly respond to changes in situations which positions the agile supply chain fruitfully (Acar & Gardner, 2012).Forecasting is a critical element in any organisations decision do processes since its accuracy helps organisations to opt for the appropriate actions pertinent to demand planning, promotion planning, impertinent product launch and inventory management in browse for the personal line of credit to become efficient and lean. Hence organisations are now paying item attention to how the quality of forecasting can be enhanced in order to incr ease the accuracy of its output (Acar & Gardner, 2012).In so doing organisations must sell collaboration building with the entire supply chain in order to generate a to a greater extent accurate forecast which will exploit the performance of the supply chain (Shu et al. , 2011). In a retail nourishment company, it is essential to apply the appropriate storage procedures and inventory technique to sufficient to serve customers better, because of this, forecasting plays a critical role in the capability of the company.Hence, forecasting in the retail food industry has become more challenging as result of price wars among competitors, uncertainty occurring from natural disasters, clime changes and epidemics (Hayya et al. , 2006). As a retail food company based in UK, Tesco considers availability of product as naturally the main competitive bring to success in the retail food industry and with products of over 50, 000 on its shelves, 6 distinctive store formats and operating in 1 4 countries, establishing decent inventory could be very difficult.A sales projection based on past patterns, which is classified as base-level forecast, is very complex. Tesco distribution network centres and mature technology have been developed to uphold the modern and cost effectual supply chain. The efficiency of the distribution system understands the product needs of all store. This is achieved in two methods, forecasting the preferences of the customers by employing refined, detailed models which considers variables for instance, seasonality, weather forecasts as well as responding to promotions.The second deals with the automated system ordering, which helps in update in real time on what customers really want to buy, in order to quickly and accurately provide stores with the the right way products at the right time. An improvement in the accuracy of sales forecasting by Tesco has enhance the availability of products for customers and decrease the supply chain cost. Te sco forecast accuracy is achieved by sharing valuable data beneficial to its entire supply chain via its web-based system known as TescoConnect to achieve an effective inventory system and lean supply chain.By utilising the capabilities of IT in the forecasting and integration of its partners, it enables them to make for each one part of the supply chain process productive. However, one of the challenges associated to supply chain is poor forecasting resulting in supply chain inefficiencies and lack of responsiveness which can create stock-outs in the shelves of Tesco. References Acar, Y. & Gardner, E. S. (2012) Forecasting Method Selection in a Global Supply Chain, internationalistic Journal of Forecasting, 28(4), pp. 842-848, Online. inside 10. 1016/j. ijforecast. 2011. 11. 003 (Accessed 9 walk 2013) Chopra, S. amp Meindl, P. (2010) Supply chain management strategy, planning, and operation. quaternary Ed. Englewood Cliffs, NJ Prentice-Hall. Hayya et al. (2006) Estimation in Sup ply Chain In neckcloth Management, International Journal of Production Research, 44(7), pp. 1313-1330, Online. DOI 10. 1080/00207540500338039 (Accessed 9 March 2013) Shu et al. (2011) Supply Chain Collaborative Forecasting Methods Based on Factors, International Journal of Innovation & Technology Management, 8(1), pp. 135-157, Online. DOI 10. 1142/S0219877011002180 (Accessed 9 March 2013)