If you read to the end of this blog post, you’ll see that it is about the wisdom of investing in retail supply chain analytics powered by artificial intelligence (AI). But where exactly does the return on investment come from? In short, the investment will deliver actionable insights that drive better, faster decision-making. The shift from gut-feel to data-driven decision-making will drive higher margins.
But first, let’s talk retail strategy. With so much chatter and hype in the retail sector around how to leverage advanced analytical technologies such as AI and machine learning (ML), it’s easy to be swayed, or at least distracted, by the newest shiny objects promising to revolutionize your business. That could lead to paralysis, or a glut of overlapping platforms and tools, neither of which is a desirable outcome.
The point is this: it’s important for retail executives to remember that an analytics investment must be strategy-driven. Your task is to harmonize your full array of data assets: sales and marketing, finance, production, supply. In retail, great data is often available, both inside and outside the organization. The trick is organizing it and prioritizing how you’ll use advanced decision-support tools to create lasting value.
Here’s one way to start mapping out your strategy: be brutally honest with yourself about the strengths and weaknesses of your current business model, what makes you competitive now and what the retail landscape will look like in the next 36 months. Take the answer, hold it up to the light, and then ask yourself if this model is sustainable. Is this the vision you have for your future business?
Let’s look at a real example, albeit an abbreviated one. Perhaps you have a retail operation that looks like this:
One could argue that, even before the global pandemic, you were heading for trouble. A savvy online retailer is going to offer a better-priced, more convenient alternative and once your customers try it, they won’t return.
At this point you might cry foul and say, "You deliberately set up a weak straw man business to rig the argument in your favor." That would be fair criticism if we weren’t seeing the retail industry filled with companies that should have seen this coming but didn’t act. Or they invested in advanced technologies in order to protect what they were good at, ignoring the need for innovation and transformation. Again, if your model emphasizes compliance, standardization, repetitive tasks and does not promote novel or flexible customer interaction, you might be replaced with the help of some of the same tools you’re investing in.
Once you have a strategy in place, you must allow it to guide what you want to achieve — and in what order. Remember, retail analytics is a broad discipline that provides insights related to sales, inventory, customers, and other critical aspects of effective supply chain management. One of the biggest benefits is optimization of inventory and purchasing. Thanks to predictive tools, you can use historical data and trend analysis to determine which products to order.
In addition to managing inventory positions, advanced analytics will help you identify your customers’ shifting preferences. By merging sales data with a variety of sentiment measurements, you can anticipate the next big thing. Marketing functions also benefit from this type of analysis.
The bottom line is that sustaining a healthy retail supply chain is a balancing act. Artificial intelligence will help, and we are just scratching the surface of its potential in the retail industry. With the right digital supply chain platform, you can put AI to work at your retail business, predicting market needs and improving in-stock positions while optimizing inventory investments and allocations. And ultimately hanging on to those precious customers you worked so hard to win in the first place.
