Despite optimism within the retail industry that a return to normal could be seen at some point in 2022 as we navigate the second half of the year, the state of the retail industry is perhaps in a more vexing and fragmented state than it was. when the year started.
After two and a half years of uncertainty, supply challenges and digital transformation revolutions, the retail industry faces another extremely daunting challenge when it comes to managing its inventory crisis.
Inventory management is an incredibly complex proposition with many often conflicting priorities that retailers must balance. Even in the best of times, retailers are constantly trying to juggle inventory hurdles, such as balancing a merchant’s desire to buy new seasonal inventory while liquidating inventory that hasn’t moved as planned. However, due to the disruption of the past three years, these priorities are more competing than ever and finding the right balance has become almost impossible for retailers to manage. So retailers are desperately looking for ways to help them regain control of their inventory operations and recalibrate their operations so they can be in the best possible position for the upcoming holiday season and beyond.
With that in mind, here are several of the key areas retailers are turning to artificial intelligence to help them navigate.
Inventory Risk Assessment
Effectively managing inventory is all about staying one step ahead. Fortunately, even before the pandemic, retailers were applying predictive data science to their inventory supply chains. That said, following the rise of the omnichannel shopping experience and expanded delivery options – from next day shipping to online purchase to in-store pickup – many retailers have feeling far from where they want to be when it comes to their agility and responsiveness to supply chain disruptions.
Simply put, retailers can’t ship what they don’t have, and every time a customer faces extended wait times for their orders to arrive, it’s more and more likely that he will leave your brand for another. AI is helping retailers take back control of this incredibly heavy business function by giving them a dynamic view of the internal and external risks they face in managing inventory so they can avoid failing to meet customer expectations. in terms of product availability and lead times. .
Formation and redistribution of demand
Beyond predicting disruption, AI is also helping retailers address another long-term challenge: forecasting demand and containing cost of ownership. Before the “age of data,” retailers relied on an unscientific combination of crude data, anecdotal experience, and intuition to predict demand. This often resulted in retailers facing inventory shortages or large amounts of excess inventory that depleted the balance sheet due to carrying costs and markdowns. AI allows retailers to not only be much more accurate in terms of inventory projections, but also to maximize that inventory by ensuring it is properly allocated to align with demand in each region and store. per store. This allows retailers to significantly reduce over-purchasing and associated costs.
Build confidence with more accurate simulations
Due to the amount of unknowns that retailers face today, they incur indirect expenses from having too much or too little inventory. Things like additional warehousing and logistics capacity are incredibly expensive right now. Having a better understanding by embracing the dynamic capabilities of AI through highly accurate simulation capabilities allows retailers to better balance all competing factors to arrive at the right outcome for their customers and their bottom line.
For example, retailers can now reduce the uncertainty of how much space they will need in any given quarter instead of having to pay out fixed space guarantees that they cannot use. Inventory management isn’t just about how many SKUs you have in stock; it flows into all aspects of a retailer’s operations. Therefore, any savings that can be found in inventory could have huge benefits across an organization, including markdown savings, working capital return on investment, and in-store or distribution center labor. .
Unfortunately, given the various disruptive forces at play, stock management is unlikely to experience calm seas anytime soon. However, by harnessing the benefits of advanced technology such as AI, retailers will not only be able to better address the challenges they face in the immediate term, but will also position themselves for long-term success.
Sandeep Bhogaraju leads the practice, consulting and delivery of supply chain analytics at Fractal analysisa global provider of artificial intelligence and advanced analytics for Fortune 500 companies. Sharada Karmakar is responsible for AI strategy and enablement for retail merchandising and supply chain and Fractal AI .