Q&A: AI-powered general merchandise and discount retail

Sep 5, 2024 • 5 min

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:

Q: What are some of the pain points that general merchandise and discount retailers face, such as seasonal complexity?

A: (Craig) Seasonal changes are something general merchandise retailers have to consider, and it may seem like a race just to stay current on what is the latest and greatest.

When 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 of the on-trend products.

If a retailer has long supply chains, they need to plan months in advance. Add inflationary pressures, and the situation becomes even more complex, as it must consider not only meeting demand but also optimizing costs.

In addition to trend awareness, retailers may face problems if they don’t have a good system for assessing end-to-end demand and matching supply closely to that. Without a unified platform for supply and demand forecasting, ordering, and fulfillment, retailers must make their decisions in silos. This can lead to excess inventory, higher markdowns, lower profits, and other inefficiencies.

Since seasonal changes mean new, unproven products, you must be able to manage them without much historical data, which is another example of why modern platforms help address supply and demand.

Q: How can retailers leverage technology to address seasonal challenges?

A: (Craig) 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 plan each week or month, the better you can 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.

Q: What differentiates advanced technology from the traditional methods retailers have been using?

A: (Craig) Traditional methods include 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 business areas.

Spreadsheets must be shared, and you might not be working from the latest version. If a retailer has multiple applications to handle warehouse forecasting versus store orders, there can be a disconnect, where a lack of end-to-end visibility creates the chance for over-buying (and future markdowns) or under-buying (and missing sales).

Advanced technology uses AI and machine learning to automate a lot of the manual work involved in planning for stores and warehouses. At the same time, it gives better visibility, identifies potential bottlenecks before they happen, and more.

In other words, AI and machine learning allow these modern advanced technology applications to anticipate instead of react.

Q: AI is a very talked-about topic lately. What role does AI play in retail technology solutions?

A: (Craig) AI 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, and 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 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.

Q: How does AI-enabled technology help plan for complexities such as large supplier networks?

A: (Craig) 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 do 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.

Q: What strategies can general merchandise and discount retailers use to navigate harsh economic conditions?

A: (Craig) 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. 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, 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.

Q: Thank you for the insights, Craig. Do you have any final thoughts you’d like to share?

A: (Craig) 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. 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 can have in the future is huge.

Learn more in the webinar: Future-proof retail