04 Mar How Leading Retailers are Optimizing and Automating Their Business
How retailers are optimizing and automating their business with Predictive Analytics
Retail is changing faster than ever, and keeping up fulfilment needs, competitive pricing, and trendy assortment is costly. Retailers must leverage innovative tools and strategies to evolve their business to compete with modern competitors and avoid extinction. By leveraging predictive analytics retailers are optimizing and automating their business. Here’s how they’re doing it, the benefits they’re seeing, and what they’re doing with the time they’re saving.
Retail tools and their applications have continuously evolved: Papyrus, the abacus, the mechanical calculator, and the electronic calculator were all forgotten and replaced by the next wonderful creation to come along.
Today retailers are seeing the decline of another era of retail tools: Excel sheets which often crash or freeze, are difficult for multiple users to work on simultaneously, and simply have a poor workflow. Retailers rely heavily on past sales data to predict future buying patterns, but too many things change, leading to low accuracy forecasts, poor results, and more frozen spreadsheets.
Modern retailers take advantage of advanced retail predictive analytics planning solutions. The predictive analytics engine generates a demand-based forecast that considers dozens of factors that influence demand. It then calculates the demand of every individual SKU across each location and/or channel and then proactively makes profitable recommendations.
Rather than a forecast being done once and never re-evaluated for long periods a time, a predictive analytics system does these calculations daily. This ensures the highest possible level of accuracy, far beyond what humans would be able achieve based on the sheer number of calculations necessary. Retail businesses that utilize predictive analytics are constantly self-learning and adapting to new scenarios dynamically.
With multiple plans, and several levels of planners, plans may go through lots of re-consolidations, merging, and adding up to the “master plan”. Every time a number is changed, the entire plan must be re-calibrated to consolidate the number and make sure it works across all locations, products etc. This means that changes to plans are very cumbersome. Retalon will automatically re-calibrate the plan and intelligently adjust “sub-plans” to make sure all numbers make sense across all levels of the business.
Traditional inventory management is fragmented silo work that doesn’t take other processes into account. Retailers often rely on homegrown systems that are very labour intensive and not necessarily scalable without additional labour. This leads to many exceptions and situations where forecasts are inaccurate, leading to more manual action needed to correct errors. Things are done retroactively or not at all, and any changes made tend to be at a category level, not a SKU level, leading to lost sales and unnecessary markdowns.
Modern retailing requires a different approach. Retailers can leverage Predictive Analytics automation to integrate all elements of Inventory Management (purchasing, allocation, replenishment) with the rest of their business. As one Vice-President of Planning and Allocation at a top fashion retailer put it:
“It’s impossible for my staff of three people to look at all those (SKU/store) combinations every week (…) so we’ve purchased the Retalon redistribution module to help us go through all those numbers ever week to help us make the best decisions that we can.”
Customers are expecting more convenient fulfillment options, better timing, and a more unified shopping experience. Leveraging predictive analytics automation gives retailers a competitive edge in meeting customer demands, and it does so while reducing the time and cost of manual labor. For example, with the use of auto-replenishment, Retalon customers are typically able to decrease their inventory management team size while being to execute replenishment more consistently and with greater accuracy.
Predictive Analytics solutions such as Retalon’s allows users to create business rules and triggers to manage different situations. The system automatically selects the rule(s) to use depending on the situations as they occur, meaning that the system is designed to run with minimal user intervention. Users only have to deal with rare exceptions.
Another benefit to automation is less dependency on experts within your team, who may retire or leave the organization, and more expertise kept in the system that any user can easily be onboarded to and work with. This also means more consistency across various users, with only one database and one forecast, users can customize their views but always work together, thereby creating a very efficient and consistent workflow.
Lastly, retailers experience better customer experience and greater profitability. For example, Retalon customers typically increase and maintain in-stock percent at the high nineties, especially top performing products, even those with very seasonal business. One Retalon customer saw an impressive 40% decrease in inventory costs with a 20% increase in sales in the same product line.
The idea is for retailers to leverage the time a retail business saves in order to get smarter about how they do business, so that they can make smarter and more informed decisions.
Retailers can leverage predictive analytics solutions for optimization and automation that provides highly-accurate forecasts, better employee workflow, and greater visibility to all lines of a retail business. This all leads to significant time savings, reductions in labour cost, better customer experience, and greater profits.
Retail predictive analytics automation empowers staff to move away from analytical work and towards other areas of the customer journey and shopping experience. Retailers can focus on creative work that builds the brand, relationships with loyal customers, and expanding their assortment.
Most importantly however, predictive analytics solutions are necessary to compete with modern retailers, live up to increasing customer expectations, and avoid extinction. If you’d like to learn more about retail Predictive Analytics, give us a call just to chat, or to set up a personalized demo with our team.
- 30 August, 2019