Embrace AI now to lay the groundwork for future disruption
Highly unusual or emergency situations have a tendency to put a spotlight on the functional gaps inside any organization. Unsurprisingly, we’re seeing that play out in retail pricing for many organizations in the wake of the current pandemic.
It’s clear that many have struggled to respond with agility to the pricing pressures of a pandemic no one could predict in a quarterly planning meeting. From runs on paper products and bakery items to growing concerns of a meat shortage, retailers and CGs alike are working furiously to meet demand and price products accordingly.
The truth is, the organizations that are already further along in the AI-enabled pricing journey have more insights to more efficiently react. Their accessible analytics elevate them as they monitor the situation and its evolving trends. They have significant advantages over trying to solve pricing questions through Excel spreadsheets and historical sales reports.
As supply pressures and rising costs emerge, you can’t manage prices independent of a cohesive and data-driven plan to come out stronger on the other side. Therefore, this is a unique opportunity to put new tools and capabilities in place and build the infrastructure for whatever unforeseen crises may lie ahead.
You must plan for the future in order to manage the future, and now is as good a time as any to build the AI infrastructure to become better prepared. When things return to some level of predictability this year or next, our new retail “normal” will belong to the organizations that have become AI fluent. With AI driving decisions around pricing and promotions, CGs will become more profitable while building better relationships at the same time.
Matthew Pavich is the managing director of global strategic consulting for Revionics, where he develops data-informed, industry-leading pricing strategies, processes, analytics and organizational fluency to help retailers meet the challenges of today’s increasingly dynamic and competitive landscape.