Business Intelligence (BI) and traditional forecasting methodology can provide visibility into a retailer’s past sales, promotions, stock levels, and more. Unfortunately, they do not eliminate the need to manually consolidate data in order to make intelligent decisions about the future. Last year’s data cannot accurately project what will happen moving forward, because of variances such as changing trends, new products, moving holidays and other differences from year to year which must be considered.
The result of unreliable projections is inventory imbalances: mistakes in planning, purchasing, and inventory management, resulting in inventory levels that don’t match actual demand. Each year, inventory imbalances cost retailers an estimated $1.1 trillion annually. By leveraging Retalon’s predictive analytics, retailers can work smarter to increase sales while decreasing inventory costs.
The Measure of Overstock and Out-of-Stock Inventory Imbalances
Retail buyers rely on a combination of data, indicators, targets, and the intuition that comes from years of industry experience. Retailers carry tens or hundreds of thousands of SKUs, far too many for buyers to accurately forecast every product at each channel/location. Therefore, purchasing decisions are largely made at a higher than SKU level. Inventory analysts, unlike algorithms, can’t accurately forecast down to a SKU/Store level efficiently. The problem stems from business intelligence, buyer intuition, or company targets lacking the ability to account for all factors that affect demand.
Retailers run costly markdowns to clear out overstocks, and out of stock merchandise leads to lost sales. Expensive overstocks don’t upset customers and their costs are easier for retailers to measure after the fact. Whereas out of stocks disappoint customers and retailers are unable to accurately measure the impact of lost sales. If they aren’t armed with a predictive analytic solution, a retailer will not be able to accurately quantify the amount of money it is losing to out of stocks.
How Leveraging Predictive Analytics Allows Retailers to Beat Inventory Imbalances
According to Boston Retail Partners, one third of retailers count on a third-party suppliers of Retail Analytics. This number is growing yearly as retailers are recognizing the value of more advanced analytics solutions. Retalon’s unified end-to-end predictive analytics platform plugs into any ERP system and offers solutions to optimize the entire retail process. This allows all elements of a business to communicate through one consistent, secure, and accurate workflow.
Predictive analytics allows retailers to beat inventory imbalances by generating optimal suggested quantities for purchasing, allocation, safety stock, replenishment, balancing, and incremental inventory needed to run successful promotions.
- Purchasing – The system generates optimal purchase quantity suggestions connected to your plan and open-to-buy based on one highly accurate demand forecast. A predictive analytics solution will calculate all influencing factors in your business, how they’re inter-related, and how they’re weighted, to determine what true demand really is. From that, the finest forecast possible is created. Having higher accuracy allows the system to recommend purchase order quantities for new products, or products that have little or sporadic sales history.
- Allocation – Smart Allocation accounts for SKU performance at each location, existing terminal stock, seasonality and other trends, assortment distribution, size curves, and more. The system tells retailers where to send their inventory to maximize profitability within a set of rules defined by the retailer, including new products, constraint inventory, and more.
- Auto-Replenishment – Relaton offers a highly-sophisticated, multi-echelon, replenishment solution. Auto-Replenishment relies on Retalon’s accurate demand forecast to automatically determine optimal shipment quantities and assign them to locations. As this solution is connected to one unified platform, the system will calculate the incremental inventory needed to support upcoming promotions.
- Safety Stock – Retailers should only add stock when doing so adds value. Solutions like Retalon’s Optimal Safety Stock calculate the optimal buffer stock quantity for each product individually for backrooms, DCs, and warehouses. The solution factors in the combination of associated risks such as volatility of demand, variability in lead time, vendor fill rates, and more. They work on an accurate forecast, and company policies, to protect a retailer’s best interests.
- Inventory Transfers & Assortment Balancing – The engine analyzes all influencing factors to recommend the most profitable inter-store transfers to move merchandise from stores where it has minimal chances of being sold, to those where it is in high demand and running out of stock. The system does this proactively, to maximize the changes of selling items at full price, before retailers experience lost sales or have to take markdowns.
Having an integrated predictive analytics approach to retailing offers real tangible benefits. Retailers who have integrated Retalon’s predictive analytics solution typically see the following results:
- Reducing inventory costs – From 20% to 40%
- Increases in sales – From 10% to 20%
- Significant decrease in manual labor and resource costs
- Intelligent coordination of different retail business functions (i.e. connecting marketing with merchandising)
Inventory imbalances happen at a high price to retailers. “Gut” intuition, even with well-thought-out plans, are still no match for an all-inclusive predictive analytics engine that plugs into a retailer’s existing ERP. Once integrated across all functions of your business, a predictive analytics solution can help retailers dramatically reduce inventory imbalances and maximize profitability.
Adrian Silipo is the Marketing Manager at Retalon, an award-winning provider of retail predictive analytics solutions for planning, inventory management, merchandising, pricing, and promotions. Retalon’s solutions are built one unified platform to account for all factors influencing your business. Adrian loves to chat, so if you want to talk about predictive analytics, reach out to firstname.lastname@example.org.