In today’s rapidly evolving retail landscape, inventory management remains one of the most critical and challenging aspects of the business. To shed broader light on this subject and go deeper into the root causes of inefficiencies while exploring how cutting-edge AI technologies are reshaping inventory management, we spoke with Chinmay Nayak, Head of Sales India at Onebeat. Chinmay brings a wealth of experience and insight into the challenges retailers face globally and offers innovative solutions that are driving profitability and customer satisfaction.
DT: What are the primary reasons behind inventory management inefficiencies causing such significant losses for retailers globally?
Chinmay: Over the past decade, about 173 leading retail brands went bankrupt. A few weeks ago, Forever 21 filed for bankruptcy for the second time. The common thread between these retailers is that they failed to adapt to changing market conditions. Consumers today want hyper personalization. They want products that meet their unique and specific needs, calling for bigger assortments. Consumers also want instant gratification. The quick commerce success story in India is testament to it. Another new consumer behavior is the need for freshness. They want new products at any given point in time.
As a consequence of changing behaviors, retailers are under pressure to increase their reach and be closer to the customer but also maintain high levels of inventory to ensure availability. The product life cycle is shorter than ever before — meaning retailers have to sell their inventory at full price in a dramatically shorter time frame.
Retailers that fail to adapt to these changes face challenges like overstocking, where capital is tied up in inventory that doesn’t move, forcing them to mark down significantly. It shrinks their margins significantly. The reason why it’s so difficult for retailers to adapt is the heavy reliance on forecasts, legacy approaches, and reliance on analytics. Retailers do know trends, and they try to rely on data to draw insights from analytics but by the time they get the insights, it's too late to act on them. Opportunities are wasted. These challenges make inventory management a constant battle in retail in India and globally.
DT: Can you elaborate on how overstocking and stockouts impact a brand's profitability and customer loyalty in the long run?
Chinmay: Overstocking and stockouts both significantly impact a brand's profitability and customer loyalty. Let’s consider fast fashion as an example. When it comes to product life cycles, fast fashion, in India particularly, is growing at an extraordinary pace. Keeping up with consumer demand, brands are offering hundreds of designs in a five-week lifecycle. Some fast fashion giants are launching new designs every day. There simply isn’t enough time to respond to the overstocking problem. If retailers lack the ability to get predictions in quickly — including forecasting and identifying similar products based on demand behavior and clustering them together — they cannot understand which products to sell in which stores.
When it comes to stockouts, brands simply cannot miss the revenue they can generate by having the right inventory of in-demand products. If they run out of stock too quickly, consumers will switch to competitors who can give them what they want.
Retailers need technology that simplifies inventory management. Instead of discounting excess inventory, Onebeat’s solution is helping many retailers redistribute products to the right locations at the right time. This ensures better inventory turnover, reduced markdowns, and improved profitability. The goal is to improve full-price sales by a few percentage points — enough to turn loss-making stores into profitable ones.
DT: How does AI technology detect subtle patterns in inventory data that traditional methods might miss?
Chinmay: The need for instant gratification and growing assortments make inventory management in India more challenging than it is compared to the rest of the world. Fast fashion is dictating this norm and retailers are facing a future where traditional approaches won’t work anymore. They need advanced technology that goes beyond demand forecasting. Retailers need AI tools that gather demand signals, identify products based on demand behavior, and cluster them together. AI must help determine which stores can sell a product and which cannot, with high certainty. More importantly, AI must optimize decisions.
In retail, hundreds of possible transactions can be successfully made by mobilizing inventory between stores. For example, in fast fashion, brands are moving not just products but also sizes. Consolidating sizes into sets across every new release is overwhelming. Many retailers still do this manually and crunch numbers on Excel. It isn’t enough to do this once a month or once a season.
Brands need to be nimble enough to move SKUs more frequently. AI-powered solutions like Onebeat reduce these complexities by identifying cost-effective transfers and helping retailers do it in manageable chunks week on week. The ease of moving inventory from store to store improves the likelihood of the product selling at full price in the right store. It boosts margins significantly.
DT: Could you share specific examples or success stories where AI has helped retailers optimize inventory management and improve profitability?
Chinmay: Leading apparel brand Being Human leveraged AI-powered inventory management to streamline their replenishment processes and redistribute products between stores effortlessly. Within the first six months of adopting the technology, the brand recorded a 10% increase in full price sell-through. At the same time, they could manage store inventory with 23% less stock, making way for fresh assortments.
Retailers don’t need a nationwide presence to adopt AI. Artificial intelligence is a huge competitive differentiator for retailers across the board, regardless of the size of the business. A great example is Hyderabad-based retailer White House which operates around 90 stores in the region. With expansion in mind, they adopted Onebeat’s AI-powered platform and saw results in six months. The company reduced slow-moving stock surplus by 15%, improved the availability of fast-moving products by 28%, and increased full-price sales by 10%. The numbers speak for themselves. Leveraging AI for inventory management offers massive ROI. It provides greater flexibility in planning, frees up cash tied to inventory, and drives up profit in parallel.
DT: In your view, how will the adoption of AI-driven inventory management shape the future of retail, particularly in competitive markets?
Chinmay: Adopting AI-driven inventory management is inevitable. AI adoption will be widespread because the challenges that retailers face in the age of instant gratification are far too many to solve manually. Brands will have no choice but to leverage AI as a tactic to achieve specific and measurable business objectives. In retail, the ultimate constraint is traffic—which no business can control. Businesses are then left with achieving higher sales conversion, better assortments, and replenishment cycles.
I see the use of AI for inventory management becoming a standard practice in the next few years as AI takes into account macroeconomic and external factors to predict outcomes. It offers retailers quick insights and helps them modify processes quickly. AI helps retailers gain predictability in an unpredictable market, making inventory management smarter, more efficient and ultimately more profitable.
