It is very difficult to forecast with any granular accuracy the demand for a product in a channel over an entire season and retailers are basing their sales and survival on this forecast. They take this forecast then to drive purchasing for the entire product line for the season. This practice and method is now colliding with the changes in shopping and purchasing practices driven by the consumer in addition to the impact of smaller competition made possible now by eCommerce. All of these demands and influences on the retailer only makes the planning and forecasting practice more important and, in turn, demands greater accuracy and a more granular level in their forecasts. There is no easy way for retailers to take these factors into account to product a forecast that provides accuracy to make large season long purchases.
I do not believe there is enough data that can be provided to a forecasting to increase the accuracy of the long term forecast at a level of granularity to purchase accurately. Granted, the long term forecast can provide trends and tendencies but these must be continuously monitored and updated because of the velocity of consumer change. To increase the level of difficulty, for the large retailers especially, there has been an explosion of competition for the commodity type products and consumer shopping and purchasing practices have become even more opportunistic as a result of the capabilities offered by mobile technologies. All of these factors have come together to increase the importance of forecast granularity while at the same time disrupting the ability of the large retailers to produce accurate long term forecasts.
There is the opportunity now though for retailers to increase the data collected to improve the forecasting. The data collection and availability itself will not necessarily improve the accuracy of the forecast but it will provide input to improve the trending analysis and this is a critical aspect to produce a forecast at the appropriate level of granularity. In addition to the collection of additional data retailers must collaborate with the consumer to understand the consumer demands and reduce reactionary changes that also disrupt the forecast.
This requires a change in the practice to shorten the forecast and purchase cycles while increasing the types of data utilized for trending analysis. This change in practice also requires a change in culture to open the planning and forecasting process to incorporate input from consumers. This is the most important, and the most difficult change because culture requires a change throughout the organization and commitment from leadership.
And now for the audience participation portion of the show…
ECommerce will have wide ranging impacts on both the retail and manufacturing sectors. How can you focus these abilities to improve the consumer's experience? Improving the consumer’s experience will require a re-evaluation of the sales channels, the manufacturing channels and practices and the supply chain channels and practices from the raw materials to the consumers’ homes. In order to ensure and maintain success in this new reality you must harness the tools and capabilities in many new areas. How can you support these continuously changing requirements?