Despite the optimism within the retail industry that a return to normal might be seen at some point in 2022, as we move through the back 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 began.
After two-and-a-half years of uncertainty, sourcing challenges and digital transformation revolutions, the retail industry is dealing with yet another massively daunting challenge when it comes to navigating its inventory crunch.
Inventory management is an incredibly complex proposition that features numerous, often conflicting priorities that retailers have to balance. Even in the best of times, retailers are constantly trying to juggle inventory hurdles like reconciling a merchant’s desire to purchase new seasonal inventory while liquidating inventory that didn’t move as forecasted. However, because of the disruption of the last three years, these priorities are competing with one another more than ever, and striking the right balance has become nearly impossible for retailers to manage. Thus, retailers are desperately searching for ways to help them get their inventory operations back under control and recalibrate their operations so that they can be in the best position possible for the upcoming holiday season and beyond.
With that in mind, here are several of the key areas that retailers are turning to artificial intelligence to help them navigate.
Inventory Risk Assessment
Effectively managing inventory is all about remaining one-step ahead. Fortunately, even prior to the pandemic, retailers were applying predictive data science to their inventory supply chains. That said, as the result of the booming omnichannel shopping experience and expanded delivery options — from next-day shipping to buy online, pick up in-store — many retailers feel as if they're a long way from where they want to be when it comes to their agility and supply chain disruption responsiveness.
Simply put, retailers cannot ship what they don’t have, and each time a customer is faced with extended wait times for their orders to arrive, the more and more likely it is that they will leave your brand for another. AI is helping retailers bring this incredibly unwieldy business function back under control by giving them a dynamic view of both the internal and external risks that they face in managing inventory so that they can avoid falling short of customer expectations in terms of product availability and fulfillment timing.
Demand Shaping and Redistribution
Beyond predicting disruptions, AI is also helping retailers with another long-term challenge: demand forecasting and limiting carrying costs. Prior to the “data age,” retailers relied on an unscientific combination of rudimentary data, anecdotal experience and intuition to predict demand. This often resulted in retailers either facing inventory shortages or having significant amounts of surplus inventory that drained the balance sheet through carrying costs and markdowns. AI is allowing retailers not just to be far more accurate in terms of their inventory projections, but to also maximize this inventory making sure it's allocated correctly to align with demand in each region and on a store-by-store basis. This allows retailers to dramatically cut down on over-purchasing and the related costs.
Creating Confidence Through More Accurate Simulations
Due to the amount of unknowns that retailers are having to cope with at the current moment, they're incurring tangential expenses related to too much or too little inventory. Things like additional warehousing and logistics capacity are incredibly expensive right now. Having a better grasp by adopting the dynamic capabilities of AI through highly accurate simulation capabilities allows retailers to better balance all of the 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'll need in a given quarter instead of having to splash out on fixed space guarantees that they may not use. Inventory management isn't just about how many SKUs you have in stock; it flows into every aspect of a retailer's operations. Therefore, any savings that can be found in inventory could have huge benefits throughout an organization inclusive of markdown savings, working capital ROI, and store or DC labor.
Unfortunately, given the various disruptive forces at play, inventory management is likely not going to experience smooth seas any time soon. However, by tapping into the benefits of advanced technology such as AI, retailers will not only better navigate the challenges they face in the immediate term, but position themselves for long-term success as well.
Sandeep Bhogaraju leads the Supply Chain analytics practice, consulting and delivery at Fractal Analytics, a global provider of artificial intelligence and advanced analytics to Fortune 500 companies. Sharada Karmakar is AI strategy and enablement lead for Retail Merchandising and Supply Chain and Fractal AI.
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Sandeep leads the Supply Chain analytics practice, consulting, and delivery at Fractal. He is focused on enabling clients on the digital supply chain transformation, enabling data to decisions across supply chain functions, and driving the adoption of analytics solutions.
Sandeep comes with over two decades of supply chain domain experience spread across analytics, consulting, and IT in the CPG and retail industry. He comes with a proven track record of delivering analytical solutions across S&OP transformation, inventory optimization, manufacturing, and IIoT analytics along with optimizing logistics and distribution and sourcing analytics. Over the years, Sandeep has performed multiple roles, including business system leader for customer service & logistics, solution head & architect, practice management, and CPG consultant.
He has a keen interest in problem-solving, AI, and ML with its applications to CPGR and at large to humanity. Sandeep has a Bachelor’s degree in technology from Sri Venkateswara University.
Experienced retail and consumer goods industry professional. Led successful serial product launches in diverse areas such as e-commerce fulfillment, logistics and distribution, robotic warehouse automation, online grocery, merchandise planning and digital payments. Successfully delivered large scale transformation programs, across strategy, execution and build while working closely with cross-functional stakeholders at various levels of the retail organization. Proven track record of engaging with senior executives to deliver tangible business outcomes through the application of emerging technologies, data and process optimization techniques. Strong communicator with demonstrated ability to liaise with business (including C-level sponsors) as well as engineering and design teams.