Accelytics CEO, Ash Jain, and Retail Expert, Jared Dolich, have a short conversation around merchandising planning and analytic maturity of grocers. The discuss the process of merchandise planning and how a technology solution could benefit a growing retailer.
Ash Jain: I'm going to get specific on merchandise planning. That's one area where the merchandise planners are spending a lot of painful time working in Excel spreadsheets, if they don't have any planning system. What are they missing out on by not having an integrated technology?
Jared Dolich: So merchandise planning is one of the core processes with grocers. Some call it category planning, but essentially, it comes down to being divided into two sections. There's pre-season and in-season.
Merchandise planning is essentially a dollar-based planning process where we're really looking at the big picture. We're trying to figure out which categories are going to be hot and which ones are going to struggle a bit. We determine how we move our working capital, which is their inventory, from one category to another and figure out where the growth is going to be. And we're looking at all the different categories. Merchandise planning is a fundamental process that is very much impacted by the 4 trends that I mentioned.
Analytical Maturity of Grocers
Jared Dolich: From a technology standpoint, I would say that merchandise planning can be done in a spreadsheet. I mean, I'll just be blunt. It's going to be tricky, it's going to be hard, but it can be done. Each category, or each category manager, or department, however you want to look at it, will have to have their own separate spreadsheets, and then it has to be consolidated. But that's as far as you'll get.
I would say that merchandise planning can be done in a spreadsheet. I mean, I'll just be blunt. It's going to be tricky, it's going to be hard, but it can be done.
There's what I like to call an analytic maturity curve that grocers are on. Some grocers are still at, what I would call, a descriptive level of analytics. So you can start with your foundation, which is just master data. For example, "I got my product hierarchies nice and cleaned up." Then you go in descriptive. Descriptive is just, "Tell me the news."
Once you move from descriptive, you can move on to predictive analytics. Now you're really starting to do forecasting. You really want to start looking for trends. And then from predictive, now you're starting to get into prescriptive analytics. Where now, you're letting artificial intelligence, or machine learning algorithms, or sophisticated statistical modeling start to basically make the decisions for you. Or at least tell you what the decision should be or give some choices. And finally, we get into more of a cognitive analytics.
Most grocers are still all the way back in descriptive. They're dabbling, and they're starting to get into some predictive analytics. But a lot of this is because grocers has been around for so long. People have to eat. They're going to shop. They're going to come into the grocery store. One way or the other, they're going to be there. So it's not an urgent need to immediately get into having a sophisticated, optimized analytic maturity curve with merchandise planning in particular. But at the same time, you really can't move forward with the edge applications that you need because you're stuck at the descriptive level.
You're basically saying, "Look, I can tell you the news, but that's about as far as I can go." And you're going to have to pull this stuff into a spreadsheet. So if you wanted to figure out how to seamlessly integrate online grocery shopping, or pick up in a store, or just, how would I seamlessly integrate all that? You're not going to do that in a spreadsheet. But if you're only focused on basic merchandise planning, it's not that complicated.
But if you do want to scale, grow and edge out competition, you can't really move forward without having a more sophisticated solution in place.
But if you do want to scale, grow and edge out competition, you can't really move forward without having a more sophisticated solution in place so that you can meet all the demand of the customer and current environment.
Is your organization struggling to keep up with the current demands of your customer? Reach out to Jared to discuss your retail planning challenges!
About the Retail Expert, Jared Dolich:
Jared has 30 years of extensive retail and IT experience. He strives to help retail professionals be better at what they do. He combines predictive analytics, business intelligence, planning, business process development, strategy, and IT management, helping retailers all over the world. His love and passion for the retail community inspired him to join Accelytics, a premier Anaplan consultancy with a focus on the retail industry. You can connect with him on LinkedIn here.