Category Management is undergoing a quiet revolution. Gone are the days when a category manager could trust in intuition and experience alone. The new generation is embracing Retail Science to make better price, promotion, merchandise and assortment decisions. Retail Science applies sophisticated data analysis to help better understand what customers want. Data sources include Point-of-Sale (POS), Transaction Log (TLOG), competitive pricing, panel, syndicated, weather, demographic, and location attributes. Data cleansing, quality assurance tests and outlier analysis are essential for measuring causal relationships. The result is a demand model that accounts for price elasticity, promotional lift, merchandising, seasonality, cannibalization, affinity, space, and assortment. Category managers use this demand model to evaluate and compare scenarios. For example, a supplier may offer a incentive to promote Cheerios. The category manager can evaluate the category profit accounting for vendor incentives, cannibalization, and affinity. This analysis shows how cannibalization of private label erodes category margin. Even the impact on loyalty customers can be evaluated in terms of basket size and trip frequency by customer segment.
Ideas are like tomatoes. They start out small and green, but if the circumstances are right, they grow and ripen until they bear fruit. That is definitely the case for Revionics’ idea to provide retailers with One Integrated Forecast.
The idea was born years ago. At the time retailers had multiple contradictory forecasts: one forecast was used for financial planning; another for replenishment; another for workforce management. There was a store forecast for all categories and a category forecast for all stores---but the two did not match at the enterprise level. There were forecasts at daily, weekly, monthly, quarterly, and annual levels---when rolled up these didn’t match either. None of the various forecasts provided the accuracy necessary to make good business decisions. Retailers could not accurately or consistently predict their business. If a business is not predictable, then how can it be managed?
By: Ken Cline, Application Consultant, Revionics, Inc
I was recently reading Supermarket News, and came across this article that spoke to the state of the state within the grocery vertical. It speaks well to what it takes to succeed in today’s environment.
Food retailers are turning to analytical systems that can help them survive the harsh economy, according to SN’s latest technology survey.
By: Jeff Smith, Founder & EVP Business Development, Revionics, Inc.
In retail, there is a key piece of information that contains a lot of power, that piece of information is the price sensitivity of a given item in a given store. Obtaining that piece of information is a very difficult thing to do. If it weren’t for seasonal effects, holidays, promotions, out of stock conditions, low unit movement and a variety of other challenges, it actually would not be too difficult to determine. After all, it is simply a prediction of how much the unit sales will change given a change in price.
By: Christie Frazier-Coleman, VP Consulting, Revionics, Inc.
According to Antony Karabus, President and CEO of Karabus Management these five strategies for retailers are important in order to emerge as a strong retailer.
1. Optimize cash and cost management
2. Understand what is relevant and motivates your customer
3. Use science to improve gross margins and inventory productivity
4. Invest in technology correctly and on the right projects
5. Get your supply chain right