Today’s retailers have to find profitable strategies to deliver on their customers’ expectations, amid significant fulfillment challenges and complexities. Customers don’t understand the massive omnichannel fulfillment operation that is set into motion when they click “Buy Now.”
Whether they purchase a product on your e-commerce site for home delivery or order a product to be delivered to your nearest brick and mortar location, customers want immediate inventory availability, fast shipping and a seamless end-to-end purchasing experience. Here’s a closer look at how AI and cognitive technologies are helping improve omnichannel fulfillment in a world of rising customer expectations, free 2-day delivery from the competition, and rapidly shrinking margins.
What does intelligent fulfillment look like?
Minimizing the Cost to Serve While Meeting Expectations
A recent study found that retailers are spending 18 cents out of every revenue dollar generated online to meet customer expectations – and in the JDA PWC annual retail CEO survey, three-quarters believe their costs have increased in the last year. Cognitive tools allow retailers to dive into the details of their cost-to-serve to better understand how to optimize different elements for maximum profits and meeting customer expectations. It’s possible to predict fulfillment costs along all dimensions for omnichannel customers, and choose a last-mile delivery path that prioritizes speed while minimizing delivery costs and other factors that quickly add up in terms of cost-to-serve.
Simulating Sourcing and Fulfillment Streams to Support Decision Making
Access to real-time data is key to helping retailers make the right decisions about fulfillment management. For example, if a customer orders clothing with free 2-day delivery, which distribution center or store should the product be shipped from? A number of factors come into play: the ability to meet delivery windows, the cost effectiveness of shipping options, and inventory impact versus demand, to name just a few. Similarly, a retailer that’s evaluating their supply chain may have an estimate with a lower cost per unit from one manufacturer versus another. When modeled with fulfillment data, it’s possible to see which supply chain or shipping decision controls costs and best aligns with the retailer’s long-term business goals.
Maximizing Omnichannel Fulfillment Capacity
The omnichannel customer can follow any pattern. She might research a product online and buy it in the store; look at it in person and then order it for in-store delivery; or follow the entire buying process end-to-end online. AI tools help maximize fulfillment capacity and create a strategy that’s flexible enough to meet any customer mix, while controlling the cost-to-serve. With tools such as real-time sourcing, it’s possible to move returns and at-risk inventory, quickly scale product to meet increased demand, and meet any change with immediate scenario planning that helps map out the fastest and most cost efficient option in the face of current constraints.
Utilizing Inventory at Its Most Profitable Price Point
In the annual JDA and PWC survey of retailers, just 10 percent of retail executives interviewed felt they have refined their omnichannel delivery to the point that they’re able to meet demand and make a profit. Issues including returns, stagnant inventory and markdowns play a role in cutting into profits. With AI tools, retailers can focus on utilizing inventory at its most profitable price point – minimizing carrying costs while limiting markdowns and unnecessary promotions. Use fulfillment tools to optimize returns, utilize slow moving inventory, and more to meet customer demand and clear the way for the next season’s inventory in a streamlined and profitable way.
Making Dynamic Adjustments to Your Fulfillment Network without IT
To stay competitive, retailers need the ability to access real-time data and make pivots. With AI suites focused on fulfillment, retail managers can access up-to-the-minute trends and demand. Across both peak and regular business periods, it’s possible to shift or pivot to improve sell through, adjust performance for changes in market conditions, and remain agile down to the SKU level if demand changes require supply chain shifts. The right tools enable retail managers to do this in real-time, without opening IT tickets, negotiating complex programming challenges, or handling cross-platform communications issues. Real-time insights lead to up-to-the-minute actions and profits.
Omnichannel shopping has led to a rebirth of commerce and delighted consumers, but also created a whole new set of challenges for retailers. In order to make the most of today’s largely digital path to purchase, retail brands need to harness data to help them forge faster, profitable and efficient omnichannel fulfillment plans.
Is your omnichannel fulfillment engine running like a dream? Are you able to optimize inventory utilization to deliver whenever and wherever your customers are ready to buy? View this video to see intelligent omnichannel fulfillment in action with Watson Order Optimizer.