Using Predictive Analytics to Improve Inventory Management in the Retail Industry

OVERVIEW: Data has become a massive force in the market, forever changing the behavior of both consumers and brands in the present digital age. Retail, nevertheless, is a trillion-dollar industry where the scope for data is simply massive. Predictive Analytics models, in particular, have the utmost potential to transform this humongous industry to meet the consumer needs of the future! Check out this blog to know more about the role of data and how predictive analytics help retailers optimize their inventory management.

Retail has always been one of the most active channels in the market as consumers tend to spend a majority of their purchasing power in-store than online. However, the pandemic had a massive impact on consumers and their behavior, drastically changing the rules of the market.

Industry experts believe that this paradigm shift is not a one-time thing and, in fact, will remain in the market for a long time. Businesses can easily utilize these new opportunities in the market as this movement is primarily driven by technology.

The preceding ecommerce wave helped many entrepreneurs, small business owners, and innovators to go toe-to-toe with industry giants even though their arsenal was significantly lighter. While many brands were quick to get on this bandwagon, businesses that lacked a holistic vision for tech were left at the bay. The brands that failed to identify and leverage this opportunity also missed the chance to get on the next big thing- DATA!

Without a doubt, data is the “new oil” that’s empowering businesses and consumers alike to be more active in the market. So, how can data impact retail businesses in 2022 and so on? Can data bridge the gap between producers, retailers, and consumers? Can predictive analytics help brands to streamline their inventory and encourage the concept of conscious consumption? Let’s find out!

Data as a core strategy

A report suggests that we produce a whopping 2.5 quintillion bytes of data daily! Among this ocean of data is a “goldmine” for businesses that lets them understand various aspects of their operations and consumers. Hence, the hype for data and the pursuit of it.

The core strategy for a 21-st century business is to leverage data. And technology has proven to be a sure-shot way to leverage data efficiently. For instance, take the present-day applications. They sit right at the centre of consumers, brands, and employees to craft holistic experiences for the stakeholders.

But what makes brands serious about leveraging data is the fact that they help identify and recognize patterns. Predicting an event, any event, in the present market is a huge advantage for brands as they can capitalize on these events.

So, predictive analytics helps brands hone their market instincts, take decisions and devise strategies that amplify their presence and sales.

This is particularly true for the retail industry as it constantly faces challenges like a rise in inflation rates, balancing investments and ROI, maintaining the infrastructure, crafting unique customer experience, keeping pace with Ecommerce, challenges in product procurement, etc.

However, if you notice the above-mentioned problems, you can understand that most of them have one thing in common- Inventory management!

Answering the Why before the How!

For a retail business, inventory management forms the foundation for its operations. Common operations under inventory management include materials procurement and production, quality control, fueling logistics, demand forecasting, and customer service.

This chain of operations controls pretty much every aspect of a retail business. Any disruption in this chain may directly impact a business’s performance.

Now imagine the scale of these operations for massive retail chains like Walmart, Ikea, or Target that have thousands of branches across the globe! Though they control their consumer actions within the store by ensuring planogram compliance, inventory management sets this whole thing in motion.

Take the pandemic, for example. Consumers were in a “feeding frenzy” as they anticipated lockdowns. Stores across the country ran out of essential supplies within minutes of resuming their operations. Toilet paper, in particular, was in huge demand across the country as consumers started stockpiling goods.

Though there are a variety of reasons behind this panic buying behavior, retail stores identified a huge gap between their inventory and the shelf! The same happened with medical shops, grocery shops, supermarkets, and some reports state that people were stockpiling gasoline, too!

For businesses to be more in control of their stocks without compromising the present needs, predictive analytics is the most practical approach.

How can Predictive Analytics help in improving inventory management for the retail industry?

Defining The “new” ABC method

Predictive Analytics can redefine the traditional ABC approach to help retailers streamline their inventory. Many successful retail businesses leverage the ABC approach to drive sales.

The ABC approach is pretty straightforward. The stocks are categorized into 3- A, B, and C. Products under the “A” category actively contribute to the business’ revenue, while the products under the “B” category perform relatively slower. The products under the “C” are the least contributing.

With predictive analytics in the picture, these metrics can be defined with pristine accuracy. As the market gets more and more dynamic, and channels like the digital, influencing the purchasing decisions of a consumer, it is becoming increasingly difficult for retailers to “keep up with the hype wave.”

Predictive analytics models can fill this knowledge gap for retailers by extracting contextual information from the data sets. This can be distributed among different branches or even employees to expand the ROI horizon!

Investing where the action happens

One of the most important benefits of a predictive analytics model is that it lets you take a peek into the future! Though predictive analytics models are highly contextual, the general principle is pretty simple.

They collect past data, and the system crawls through them to identify areas where the action happens. The system then analyzes more data to see if these patterns are repetitive. By doing these countless times, the system can point you towards the area where this pattern may repeat itself.

Knowing this, retail brands can fill their inventory accordingly. A report by Nasdaq predicts that almost 95% of all purchases will be through Ecommerce by 2040! With such stakes at hand, many hardcore retailers have got into this Ecommerce ship to diversify their sales channels.

Though the inventory is the same, it will be increasingly difficult for the brands to monitor the product flow and segregate these two channels. In such scenarios, predictive analytics can help business owners and decision-makers to “feed the demand” accordingly.

Saving costs with data 

Money is a crucial resource for any business, and brands that focus on saving costs tend to be more future-ready. Tallying costs and innovation is a constant battle for brands as the market gets more and more competitive.

With brands spending a hefty share for their marketing activities, the inventory needs to be more streamlined than ever. No matter how many people you pull with your creative strategies, if there is no product in the stockpile, there is no money made at the end of the day.

Apart from marketing, logistics is another area that drains a brand’s resources. Healthy inventory management is a primary necessity for crafting smoother logistics operations. Predictive analytics can help brands understand consumer behavior across regions. This is particularly helpful as brands are investing in their expansion plans.

Predictive analytics can also help brands to identify products that people in a particular region are most likely to buy. Say product “A” performs better in region “X”, and product “B” performs better in region “Y”. While both these products are under the same inventory, with predictive analytics models, the business can foresee the demand in those particular regions and up the numbers wherever necessary. This also streamlines the storage and maintenance costs.

Wrapping this up,

Data should be treated as an asset for retail to stay relevant in the future. Leveraging data can help a brand move consciously, but for the most part, data equals opportunity! The most anticipated “Smart stores” are expected to create better odds for retail, but the foundation of such a phenomenal concept still lies in data. Predictive analytics has already impressed business leaders to include it in their default digital strategy. However, in the next few years, the adoption of data analytics will be an essential requirement for businesses. Aligning your brand to this bigger picture can help you stay resilient and make your infrastructure shockproof!

Author Bio:

Madhu Kesavan is the founder & CEO of W2S Solutions, a globally recognised  big data analytics company empowering enterprises and governments in their digital journey. With 20+ years in the IT market, he makes his vision for a sustainable future come true by leveraging technology.