By Ira Dubinsky, Go-to-Market Strategy Director, Peak
Working in retail can be wrenching when things aren’t working, but equally rewarding and fulfilling when things are humming. Serving and delighting customers – connecting them to the things they need and want – is a source of pride for millions of front-line retail employees and the millions more who support their efforts behind the scenes.
But retailers are facing intense headwinds: the cost of products, manufacturing and transportation are all going up; suppliers are unable to meet delivery timelines; demand from customers is unpredictable; new channels such as e-commerce need to be managed; the imperative to reduce environmental impacts cannot be ignored; and all of this is made that much more difficult with outdated technology.
It would be foolish to suggest there is a silver bullet or panacea for these woes. But the context we are operating in does provide some clues for what to do next. We are on the precipice of a revolution not unlike the dawn of e-commerce in the mid-90s or the launch of the iPhone in 2007. Artificial intelligence in transforming the world around us. Every single decision a retailer makes can and will be informed by AI, resulting in unprecedented leaps in operational efficiency and improvements in customer experience.
Retailers would be wise to consider how they can use AI to build a competitive advantage. Those that don’t invest today risk the same fate as those that ignored the e-commerce trend: they’ll disappear into the retail history books. Broadly speaking, there are three main themes to adopting AI in retail.
1) Interconnected data as your crystal ball
If only it were possible to know exactly what consumers will want in the future, down to the detail of how many, what colour, in what stores, and at what price they’d be willing to pay. The next best thing to a crystal ball is using data to manage uncertainty.
Retail businesses have always been fuelled by data going back to the early days of open-and-paperer recordkeeping. The modern AI-enabled retailer must bring together data from different sources to create a single version of the truth and enable data-driven decision-making. Supply chain, demand, pricing, and customer data can all be combined in a way that allows business applications and end-users to access data and insights as needed.
Bringing together data allows a retailer to create a single demand forecast that becomes the beating heart of the business. With consensus on what customers are most likely to buy, when, and how, retail teams can plan their buying, merchandising, allocation, pricing, and promotions more effectively. Moreover, a unified demand forecast allows teams to re-imagine or re-invent their plans in response to the market. For example, with a more accurate and connected demand forecast, the planning team for a major global sportswear retailer can allocate individual SKUs to exactly the right stores on a daily basis, resulting in higher levels of sell-through and increased profits.
2) Probabilistic decision-making
That sportswear allocation example illustrates how building AI across a variety of data sources has the potential to disrupt entrenched business concepts, notably “business rules.” Every retailer has them and uses them to make decisions. But the truth is that rules alone were never meant to be the basis for good decision-making. The constraints of technology and the linear nature of programming have made business decision-making models what they are today.
We’ve ended up with a lot of rules-based systems, not because it works best, but because that’s all we could handle. We are often told new tech systems will be customized to fit our way of doing business but it’s actually the other way around; our business models have been made to fit what tech could manage. These systems and the rules they brought have not prioritized innovation and creativity but rather standardization and compliance. Merchandising, buying, planning, and pricing have all been slaves to the rules imposed on them by a sub-optimal approach to technology.
Things don’t have to be that way any longer.
The right way of doing things for a retailer no longer means a single right way to the exclusion of other options. Data-driven decision-making is probabilistic by nature, with infinite options allowing for more creativity, flexibility, and innovation. For example, an AI-powered department store could send different marketing messages to each one of its millions of individual customers or set a different pricing strategy for each one of its thousands of SKUs. AI gives you the flexibility to rework, reimagine and reengineer your business quickly and easily. The end result is increased productivity, happier customers, and stronger margins.
In addition to the bottom-line benefits of leveraging AI, there can be enormous environmental benefits. Using AI to optimize buying means raw material use is limited to what you know will sell. Machine learning models can optimize stock movements to and between distribution centers, reducing thousands of miles of unnecessary emissions. And utilization models can help drive down energy, transportation and other resource uses.
Where to start?
How does AI fit into a retailer’s existing technology ecosystem? First, we have to consider the tech they are using today. The systems that run retail businesses may include a myriad of legacy operational and planning systems, plus systems for accounting, HR, and more. On top of this, many retailers will have a patchwork of point solutions for planning and analytics.
To leverage the transformational potential of AI, retailers need to build a new layer of tech: an artificial intelligence layer that sits across the value chain. The ideal technology architecture of the future is “composable” with individual tools and systems working together. This will offer retailers greater flexibility and create opportunities to infuse artificial intelligence across the entire business.
In conclusion, as the tides of uncertainty continue to wash over retailers, the time is now to invest in reimagining retail powered by AI.