Today, we have the pleasure of speaking with Craig Norman about the dynamic world of general merchandise and discount retail. Craig will shed light on the complexities retailers face, particularly around managing seasonal changes, leveraging technology, and navigating economic challenges like inflation and currency fluctuations. Join us as we explore how advanced technology, including AI, is transforming retail operations and helping businesses stay ahead in a rapidly evolving market.
Listen to the full conversation:
Transcript:
Madison Griffin: Hello everyone and thank you for joining us today for what I expect to be a very insightful and delightful discussion with my colleague Craig Norman on General Merchandise and Discount retail.
Thank you so much for joining us today, Craig! I know there are a lot of complex issues that surround general merchandising and discount retail so I wanted to see if we could dive into some of the pain points that we are seeing in the industry. And I think maybe one issue most retailers are familiar with is the complexity around managing seasonal changes. Could you elaborate on what issues you’ve seen throughout the industry and what might be causing those?
Craig Norman: Seasonal changes are something general merchandise retailers have to think about each year, from the style and color changes in housewares and apparel – think of the trends that you see in how clothing changes each year – to things like electronics, where chips and components can change each year too. Even food, where tastes change dramatically, with new flavors, ethnic foods, and that sort of thing. It may seem like a race just to stay current on what is the latest and greatest.
When these changes happen, the retailer must adapt. Seasonal changes mean that retailers must be aware of trends and shift their forecasts and orders to avoid overstocking out-of-style items and to capture sales on the on-trend products. If a retailer has long supply chains, such as sourcing products in Asia, that means they need to plan months in advance. Add in inflationary pressures, and you get even more complexity since you must think not only of meeting demand but also of optimizing your costs.
In addition to trend awareness, retailers may see problems if they don’t have a good system for seeing end-to-end demand and matching supply closely to that. Without a unified platform for supply and demand forecasting, ordering, and fulfillment, the retailer must make their decisions in silos. And when you do that, you can get excess inventory, higher markdowns, lower profits, and other inefficiencies. Since seasonal changes mean new, unproven products, you must be able to manage those without much historical data, and that is another example of why modern platforms help address supply and demand.
MG: Now of course here at RELEX, we’re always interested in how retailers can leverage technology to solve common problems within retail. So, could you elaborate a little further on how technology specifically can address the challenges you’ve mentioned?
CN: As I mentioned, technology can help address seasonal changes by providing more accurate information. Besides trend-tracking tools, the best way technology can help address the impacts of seasonal changes is through an end-to-end platform that allows you to have visibility into accurate data on not just sales but also inventory levels, costs, and forecasts.
The better you can plan each week or month, the better they will be able to capture sales while staying nimble and carrying less inventory. Examples of how technology can help include automating replenishment, optimizing and recommending pre-season and end-of season allocations and markdowns, and highlighting opportunity buys. The more the platform can connect the entire retail chain end-to-end, the better off you are.
MG: What exactly differentiates these advanced technology solutions from the more traditional methods that retailers have been using?
CN: Traditional methods include things like spreadsheets or multiple applications focused on specific parts of a retailer’s business. The problem with these methods is that they are highly manual or siloed from other areas of the business. Spreadsheets must be shared, and you might not be working from the latest version. And if a retailer has multiple applications to handle warehouse forecasting versus store orders, there can be a disconnect where lack of end-to-end visibility creates the chance for over-buying (and future markdowns) or under-buying (and missing sales).
When you’re dealing with seasonal products that have a shorter shelf-life, they come out in spring or fall or holidays. Underbuying or overbuying become undesirable outcomes. Advanced technology uses AI and machine learning to automate a lot of that manual work involved in planning for stores and warehouses and at the same time gives better visibility, identifying potential bottlenecks before they happen, and more. In other words, AI and machine learning allow these modern advanced technology applications to anticipate instead of reacting.
MG: Now I want to jump in on that AI buzzword quickly. AI has been a very talked-about topic lately. Can you expand a little more on what role AI plays in these solutions?
CN: AI, or artificial intelligence, gets a lot of attention. But it’s not exactly new. AI (and machine learning) plays a key role in a retailer’s ability to accurately predict and manage supply and demand.
In today’s complex world, local events, weather patterns, even things like politics, can disrupt supply chains. When you have all these internal and external factors happening at the same time, AI can help analyze those impacts and provide better, more accurate recommendations faster – without needing many people doing manual work or calculations.
As I mentioned, being able to anticipate future changes allows retailers to get ahead of issues and propel them forward. Essentially, AI helps you understand what to do more accurately. This contrasts with older, more siloed options which may show you what is happening today but only let you react in the short term.
What is new is the generative AI aspects being explored. That’s really interesting because it opens up new ways of interacting with data and generating new insights from what you already have.
MG: I keep coming back to complexity and I think about the large supplier networks a lot of retailers navigate, including long lead times and high shipping/storage costs. How does technology and AI plan for those types of complexities?
CN: To optimize costs, you might look at maximizing the efficiency of truckloads you’re receiving or containers coming from overseas. Or consolidating orders, including those from multiple suppliers. You have things like order requirements and limits and different logistics models to consider as well.
Modern AI technology helps you take all those pieces and optimizes them. You can think of it as asking, “how to I optimize this process to maximize my product supply, profitability, or other business objective?”
Without AI, you would need to figure out those connections manually or tie together all these different sources in some way looking at different rules and different data and it would take a lot more time and effort.
MG: Now I want to move to some of the more economic challenges that both consumers and retailers are facing. Inflation is another big buzzword recently. So, I wanted to ask, in what ways do inflation and currency fluctuations impact General Merchandise & Discount retailers? Are there any strategies you see them use to navigate these harsh economic conditions?
CN: In a perfect world, we wouldn’t have to worry so much about inflation, but it’s really been top of mind the last few years. Disruptions like COVID-19 threw normal business out the window and we’re still working our way through the inflation caused by that.
At a basic level, inflation makes a retailer’s products cost more as inflation rises. Over the last couple of years, with high rates of inflation, many basics – from food to clothing – have risen in cost. Add in currency fluctuations, and you get an even more complex picture.
When you’re dealing with long supply chains and lead times, particularly when they’re sourcing from Asia for example, you want to order at the best possible price and avoid potentially costly mistakes, shipping costs, and so on. It forces retailers to plan out over longer time frames and look at things through a risk management point of view.
In terms of strategies, this is another area where AI and machine learning have helped. AI can analyze years of data to uncover trends in the supply chain and, as we’ve already discussed, optimize seasonal and other product types. This lets retailers use strategies to target the best possible combination of cost and availability to maximize profits – instead of buying large quantities to get a low cost, but having to mark them down later, which hurts profits.
MG: So it seems like technology can really come in handy with the puzzle it takes to get ordering just right, especially with the economic issues we’ve all been facing recently. It’s good to know there are potential strategies out there to alleviate some of the struggle.
Well thank you so much for the insights, Craig. Do you have any final thoughts you’d like to share with us today?
CN: I suppose I would add that platforms like RELEX really enable better coordination, not just with internal teams in stores and warehouses, but also with suppliers. Advanced technology helps drive increased sales, while greatly reducing manual effort at the same time. And as these platforms evolve, adding capabilities such as workforce scheduling and management makes future possibilities exciting. And if you think about that even deeper, the impact AI and technology can have in the future is just huge.
