By Are Traasdahl
The stress and uncertainty felt across the world for the past two years shows no signs of dissipating, with sky-high fuel and grocery prices, ongoing COVID-19 concerns, and economic insecurity running rampant within businesses, investors, and consumers alike.
Inflation alone hit 8.5% in the U.S. last month compared to 2021, causing consumers everywhere to experience diminished spending power and growing concerns over personal economy – with two in three Americans (64%) reporting being extremely or very concerned about inflation. They’re understandably pivoting to more affordable stores and brands, increasing shopping sales and using coupons, and buying pantry items in bulk to stave off further price increases. Executives are feeling this impact, too, having elevated inflation to their number two concern, up from 22nd place just a year ago. Even for those who navigated the challenges of 2008 or the 1980s, the underlying factors fueling inflation today are unique and extreme, ranging from labor shortages and supply chain disruptions to unpredictable weather events and geopolitical conflicts.
The post-pandemic economic recovery will continue to face threat after threat, challenge after challenge—brands and retailers must act now and develop more strategic, sophisticated approaches to navigating the uncertainty in order to protect and strengthen both the financial health of their businesses and their relationship with the consumer.
Navigating Supply Chain Uncertainty with Data
Companies today have exponentially superior data, technology, and tools at their disposal to help navigate the challenges of inefficiencies that lead to wasted product and wasted time. Here’s how brands and retailers can implement a more modern and efficient supply chain:
Prioritize digital transformation: To address high inflation specifically, data from an ever-increasing array of sources must be ingested, normalized, integrated, and accessed in real time and at speed and scale that allows for better collaboration between supply chain partners. But each and every company in the supply chain must first upgrade their own data and technology infrastructure to leverage modern data capabilities. Once that investment in a modern data infrastructure is in place, price optimization models driven by machine learning (ML) and artificial intelligence (AI), for example, can utilize this vast data to identify and predict trends and interactions that can be used to evaluate and recommend pricing and promotion options.
Enhance transparency to reduce waste: A lack of transparency results in skyrocketing prices, delays, heavy over-production and heavy under-production in attempts to over-correct for the unknown. More accurate price and promotion planning, execution, and evaluation based on a shared set of comprehensive data, analytics, and AI/ML recommendations provides a platform for more strategic collaboration between retailers and brands. Sales, marketing, category management, and others from both groups can have more substantive and authentic conversations that are strategically meaningful, locally relevant, and grounded in a common view of timely data and insights.
Price with precision: Rather than taking a standard percentage increase across all products, pricing actions can now be tailored by item to reflect inflation exposure, consumer willingness to pay, and product differentiation. With real-time understanding of consumer demand and behavior at the item level within a competitive framework, companies can remix their pricing portfolio. Precision pricing can also be a tool for shifting demand from one product or category to another based on supply and inventory levels.
Promote with personalization: Promotions were tabled for much of the pandemic, increasing the average retail price paid by the consumer and further fueling the overall perception of rising prices. It’s time to revisit and reset promotion plans, starting with a clean slate and in conjunction with resetting everyday price. Leveraging advanced analytics, pricing and promotion plans can be designed and optimized in tandem.
Identify margin-enhancing opportunities: The holistic and rigorous understanding of consumer demand and price-point drivers inherent in price optimization analytics often illuminates product gaps that can be filled with margin-enhancing innovations mid- to longer term. With these insights, brands could source local products to build differentiated assortments while shortening the supply chain or bundle or unbundle existing products to create new value propositions or price points, for example. A robust innovation pipeline not only meets new consumer needs and addresses margin pressures, but it also demonstrates investment in category growth to retailers and shareholders.
Brands and retailers need to start better leveraging the data at their disposal to more seamlessly navigate today’s challenges and the ones that lie ahead. If they do, prices can be meaningfully tailored in a way that engages consumers, while safely recovering margins to maintain and grow healthy, prosperous businesses.
Are Traasdahl is co-founder and CEO of Crisp, an open data platform that connects information and companies across the food industry supply chain.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.