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Inventory Optimization Strategies for Retail CX Domination

Welcome to the final post in our “Specialty Retail Series.”

In case you need a refresher, Part 3 covered “Where to Put Your Retail Tech Investment in 2020,” which was all about being adaptable in your replenishment forecasting.

Today we’ll wrap up with some inventory optimization strategies that leverage data to help you OWN customer experience!

The Struggle is Real.

SCDigest recently reported that U.S. retailers are currently sitting on about $1.43 in inventory for every $1 of sales they make.

In addition, 70 percent of shoppers would shop for an item at a competitor if it was unavailable, rather than waiting any length of time for back-ordered inventory, according to Repricer.

The retail distribution industry needs better inventory optimization strategies because having the right items in stock, in store, in season (not too much, not too little) is the strongest driver of Customer Experience (CX) and profitability.

Top retailers and distributors have found the answer. Inventory optimization solutions that use data, AI and machine learning algorithms with intelligent replenishment are empowering businesses to respond fast and respond first to highly volatile demand patterns. By automating demand planning activities and continuously optimizing the inventory strategy based on daily, data-driven forecasting, these systems keep high-value items in stock, shoppers happy, OpEx low + profit margins high. At a fraction of the effort.

It’s All About the Data

Data, data, data. Everything about the retail universe is driven by data – from the orders you place with suppliers to the social ‘ripple effect’ of those decisions. Data is the DNA of your brand. It tells you who buys what, how often, when, and how they buy it.

Analytics and machine learning help you turn more inventory, but more importantly, they drive positive CX and ultimately profitability by ensuring the right balance of inventory on-hand. No stockouts and no costly surpluses. Finding this balance today requires heavy math and solid dose of inventory optimization, which can no longer be done by humans alone.

Demand Forecasting Then vs. Today

Traditionally, demand planners spent a great deal of their day gathering demographic data and economic indicators to build a picture of spending habits across the market. From there, they’d build out a demand forecast for the month or quarter (or maybe even the year), which drove purchasing decisions. Even with the best laid plans, unforeseen anomalies such as a supplier stoppage always seemed to pop up and wreak havoc on lead times – resulting in either brand-damaging stockouts or capital tied up in safety stock, which eventually winds up in clearance.

Today, however, consumers have all the control. The bar is sky-high, with Amazon and other ecommerce players having set the standard of next-day or same-day delivery. Competing with that means going beyond intuition and the rigid inventory planning processes we’ve always known. Inventory optimization solutions bring a method to the madness. These solutions use data calculations based on user-specified service assignments to help planners make smarter decisions faster.

How the Math Works

Inventory optimization solutions use AI and machine learning to rank items according to how quickly they sell and how important they are to the business. A high-turn replenishable item usually receives the highest service-assignment rank, whereas a fashion/seasonal, low-volume item, such as apparel or firewood, would receive a low ranking because the risk of surplus at the end of the selling season is high.

Example: Pain Relievers

A grocery retailer knows their shoppers have very little tolerance for stockouts on an item like Tylenol; therefore, they would categorize Tylenol as an “A Item,” which gets a 99-percent service assignment. It can never be out of stock. Turn on the item is high, so the customer relies on the supply chain system’s algorithms to determine how much safety stock is needed.

B Items might include something like laundry stain remover or pet toys with, say, a 98-percent service assignment, and so on. The service assignments define buying decisions on down to the lowest-turnover items so that the grocer’s inventory is optimized for the top 80 percent of their entire business.

“It’s all about putting inventory behind the winning SKUs.”

The system tells you exactly how much it will cost to provide a certain service level. You decide how much annual safety stock is acceptable, and whether adjustments need to be made. The supply chain planning solution does the heavy lifting; you just sit back and respond to alerts from system.

No need to do math, guess on how much to order, etc. It’s all being monitored and optimized DAILY, automatically. Users have an always-up-to-date picture of demand. You can order week-by-week to ensure you always have the inventory needed to hit your service levels, without leaving dead-inventory investment on the table.

The cool byproduct of all of this is better retail CX and resulting social validation, which we all know is the golden ticket to long-term profitability. If you can influence customer perception and get that five-star review, you win.

Must-Haves for Inventory Optimization Solutions

Think you might be interested in an inventory optimization solution? How do you choose the dozens of inventory optimization solutions on the market? Make sure yours automates demand planning activities, predicts and reacts daily to demand trends, and communicates those changes with extended supply chain partners.

The solution should offer unparalleled agility so you can adapt your inventory optimization strategy for rapid changes in the macro-economy, as well as gain control over inventory challenges unique to a particular store or region. Particularly with your replenishable SKUs.

Rather than focusing on turns and markdowns, start making proactive, profit-driven decisions that will keep high-demand products available everywhere, and shoppers happy – online, offline, all the time.

Read Part 3

Read Part 2

Read Part 1