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

Forecasting is a heed planning tool which is aimed at coping with coming(prenominal) uncertainties, depending mostly on data of past and present as well as trend epitome (Chopra & Meindl 2010). The core characteristics of todays forward looking supply chains is flexibility and agility which utilises prospect, as one of the most raise planning musical arrangements of supply chain strategies to provide the needed capability to cursorily respond to changes in situations which positions the agile supply chain profitably (Acar & Gardner, 2012).Forecasting is a sarcastic element in any organisations decision making cropes since its accuracy helps organisations to opt for the appropriate actions pertinent to demand planning, promotion planning, smart product launch and inventory management in order for the business to become efficient and range. and so organisations are now paying particular attention to how the quality of forecasting can be enhanced in order to increase the accu racy of its output (Acar & Gardner, 2012).In so doing organisations must consider collaboration build with the inbuilt supply chain in order to generate a much accurate forecast which will maximise the performance of the supply chain (Shu et al. , 2011). In a sell food company, it is of the essence(p) to apply the appropriate storage procedures and inventory technique to able to serve customers better, because of this, forecasting plays a critical role in the efficiency 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, climate changes and epidemics (Hayya et al. , 2006). As a retail food company based in UK, Tesco considers availability of product as naturally the main war-ridden drive to success in the retail food industry and with products of over 50, 000 on its shelves, 6 classifiable store formats and operating in 14 countries, establishing prope r inventory could be very difficult.A sales swelling based on past patterns, which is classified as base-level forecast, is very complex. Tesco distribution network centres and advanced technology have been developed to uphold the modern and cost effective supply chain. The efficiency of the distribution system understands the product needs of every 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 updating in real condemnation on what customers really want to buy, in order to quickly and accurately provide stores with the right products at the right time. An improvement in the accuracy of sales forecasting by Tesco has enhance the availability of products for customers and accrue the supply chain cost. Tesco forecast accuracy is achie ved 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 each 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 reactivity which can create stock-outs in the shelves of Tesco. References Acar, Y. & Gardner, E. S. (2012) Forecasting Method Selection in a Global supplying Chain, internationalist Journal of Forecasting, 28(4), pp. 842-848, Online. DOI 10. 1016/j. ijforecast. 2011. 11. 003 (Accessed 9 March 2013) Chopra, S. amp Meindl, P. (2010) Supply chain management strategy, planning, and operation. 4th Ed. Englewood Cliffs, NJ Prentice-Hall. Hayya et al. (2006) Estimation in Supply Chain In Inventory Management, International J ournal 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 found on Factors, International Journal of Innovation & Technology Management, 8(1), pp. 135-157, Online. DOI 10. 1142/S0219877011002180 (Accessed 9 March 2013)