Following our very informative recent virtual roundtable of supply chain executives facilitated by my colleague David Kane, I was anxious to take a turn in the moderator’s chair for our next executive roundtable, ‘How to Maximize ROI of Your Inventory in Today’s Uncertain World?’, this past August 11.
As usual, we were fortunate to welcome representatives from a broad range of companies—in this case senior merchandising and supply chain executives from international luxury fashion brands as well as one of America’s leading home improvement/DIY retailers.
We kicked off this session with a novel added incentive—a virtual wine tasting, courtesy of Napa’s Grgich Hills Estate Winery. But none of our attendees would exactly require a glass of wine to encourage them to share their firsthand experiences with today’s numerous inventory challenges. We wanted to focus on the impact of misplaced inventory upon retailing—gluts of excess/out-of-season inventory as well as nagging out-of-stocks—exacerbated by lingering point-to-point logistics disruptions, inflation, and other external drivers.
While our panel generally recognized the value of demand forecasting at the front end of the inventory cycle, we were very intrigued to learn more about steps they’re taking to mitigate their real pain point—relationships with suppliers and vendors as they struggled to meet fill rates and MOQs. They acknowledged a significant data gap—information the suppliers had, but they didn’t—and sought solutions that would create transparency and proactively streamline those key partnerships.
As our panel shared more of their common challenges, we wanted to highlight other key takeaways from our discussion:
- The primary impacts from supply chain and inventory uncertainties revolve around lead times. Retailers who’ve typically worked within a 6–8-month lead calendar have generally been forced to extend those schedules up to 12-15 months. As lead time windows grow longer, the accuracy of long-term demand forecasting has suffered—particularly when it comes to predicting season-to-season demand.
- These protracted lead times have made re-forecasting more difficult than ever, requiring the agility to rapidly adapt to fluctuating inventory capacities and shifting consumer trends. Merchandisers who find themselves bottlenecked by outmoded manual, spreadsheet-based processes are turning toward automated solutions for overseeing promotions, markdowns, end-of-lifecycle pricing, or transferring excess inventory into outlet channels.
- To compensate for external supplier/vendor/logistics delays, retailers are doing whatever they can to shorten internal lead times—such as streamlining inefficient workflows via AI and machine learning applications.
- Our panelists acknowledged that customers have increasingly grown impatient with prolonged product shortages—both store shelves and online—and are quick to turn to competitors when an item they’re looking for isn’t readily available. In turn, retailers are on the lookout for automated, holistic data tools that would coordinate directly with vendors—and perhaps even relevant data points among their upstream suppliers—in real time to assure the customer with a firm date when an item will be back in stock—an innovation one panelist considered a potential “game changer”.
- Retailers are mindful of the relationships between inventory and pricing—from cost increases of raw materials to consumer price resistance at the retail level. Our panel did note nuanced differences among types of goods and sales channels—such as high-end manufacturers’ direct-to-consumer online sites, which became more essential—if not quickly created and launched—during the height of the Covid lockdown. Targeted promotions and timely discounts play key roles in right-sizing inventory.
These insightful online forums, as well as our ongoing conversations with best-of-breed retailers and CPGs, tell us that the challenges of past two years have only sped up an evolution of sales forecasting into demand forecasting. This means leveraging advanced AI-powered data modeling to de-risk multiple touchpoints—from supply and inventory capacities through retail seasonality and customer spending patterns—to achieve an optimized overall ROI.