Chasing Retail's Shiny Objects

Chasing Retail's Shiny Objects

Partner Amanda Astrologo recently led a discussion based on a Parker Avery point-of-view titled “Future-Proofing Retail: Building a Solid Foundation for Tomorrow.”

Amanda stressed that retailers must ensure foundational systems and capabilities, as well as a solid change management program, are in place before embarking on new initiatives and innovations like advanced analytics and artificial intelligence.

In this post, Amanda shares her perspectives on what it means to ‘future-proof’ and be prepared for retail’s shiny objects, as well as implications for retailers.

What does ‘future-proofing’ retail mean?

It means making sure you are foundationally ready. There are so many ‘shiny objects’ in today’s technology arena like artificial intelligence (AI), machine learning (ML), and of course, advanced analytics. Every retailer is trying to get ahead—and in many cases just keep up or stay viable. It’s easy to get caught up in today’s retail whirlwind, but so many of our clients are simply not prepared for the fast lane and not taking the critical initial steps to truly assess if they are ready. This means not only having the necessary support systems in place but also from an organizational perspective—the people and roles necessary for success.

It’s also important to have the foundational business processes in a good place. If the ‘simple’ things—basic retail block and tackle business activities like merchandise financial planning (MFP) or buying—are done differently in each area or the solutions are heavily customized, there is a significant risk in being able to do these well in an omnichannel world where everything is connected and customers expect seamless immediate experiences. It’s great to want analytics, but you need to have a place for the data to be housed and be utilized easily across your entire business. Further, you need to have effective data governance in place. Otherwise, it’s just data…and potentially expensive data.

Why are retailers slow to adopt to new technologies like machine learning and artificial intelligence?

Many leaders think investment in science is the silver bullet. However, the more they research or talk to experts in this space, they start to understand it’s a much larger undertaking. Regardless of how AI and ML are touted to be integrated into modern retail systems, there is still very much a human factor that must be taken into consideration. There must also be an acute understanding of where the data comes from (and ensurin