Forecasting demand is a core process in retail and other consumer products businesses with a direct impact on Customer Experience and the business bottom line. Underestimating product sales leads to out-of-stock situations, lost revenues and unhappy customers. Following from this, overstock results in reduced profits.
Interested in Improving your Demand Forecast accuracy on AWS in 4 weeks? Connect yourself with Reply regarding their Demand Forecast PoC engagement on AWS technology to deliver 'quick wins' to your business. Contact us.
The Demand Forecast PoC of AWS & Reply allows clients to quickly adopt and use machine learning algorithms achieving the following results:
Latest technology developments in cloud, computing power, advanced analytics and Machine Leaning enable retailers and other product focused businesses to significantly improve their Demand Forecasting capability – its speed, accuracy, granularity and flexibility. By utilising sophisticated probabilistic algorithms with a combination of internal and external data sources – taking into account seasonality, pricing, promotions, events, competitors, economic, demographic, COVID related and other data - Demand Forecasting can be done in hours as opposed to months and at a very granular SKU level and different time horizons.
Amazon Forecast Service offers an easy way for any business to start benefiting from these advancements – accurate time-series forecasting based on the same technology used at Amazon.com and no Data Science or Machine Learning experience required.
Reply works with a number of global apparel brands, retailers and consumer goods companies on Demand and Sales forecasts at global, regional and local levels, including individual stores at granular SKU levels.
More granular and accurate demand forecasts also enable further optimisation in Supply Chain, Inventory, Pricing and Promotion strategies and tactics. Reply can help you deploy Amazon Forecast in days and then fine-tune it to get most value from your specific data. Our accelerators can then help you speed up your production deployment.