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Retail

Retail meets RPA

Retail is a highly competitive industry where old and new players equally vie for the customer’s attention. According to an industry report by eMarketer, global retail sales are set to reach $27.7 trillion by 2020. It includes both brick and mortar, and e-commerce shops, which means the competition is only going to become intense. However, with increasing competition, retail industries have to work constantly on improving the shopping experience for the customers.

There is also an additional responsibility of managing the internal processes such as the inventories, customer complaints, and business operations. Considering the mounting pressure on the retail companies to provide excellent customer service, the scope for human error also increases. Retail industries realize the potential reputation damage caused by human error and are now looking at integrating Robotic Process Automation (RPA) in some of their highly process-oriented functions.
 

HOW DOES RPA IN THE RETAIL SECTOR HELP?

Retail is the concluding step of a complex supply chain that has several additional costs that keep adding at every stage. Anything (such as RPA in retail) that can improve these costs or optimize the costing of a product, can potentially also improve the profit margins of the retailers. RPA in retail supports an array of activities, such as inventory, supply chain, returns processing, invoice and contract management as well as store planning management. The lesser-known fact, however, is that RPA also supports multiple office tasks such as onboarding, staff selection, payroll, training, health, and safety as well. The finance department can optimize activities around regulatory compliance, cashflow management, incentive claims, payables, and receivables.

Benefits of implementing RPA in Retail industry

  • Helps in automatically updating the inventories
  • Helps in automating business processes
  • Helps in updating number crunching sheets such as the sales reports, marketing, and sales analytics report, and balance sheets
  • Improves operational and technical efficiency

Product Categorization

Product categorization is one of the most important and the most ignored functions of the retail industry. There have been instances where a particular product is available on an e-commerce website, but the customer fails to find it owing to poor product categorization done by the retailer. Proper taxonomy is essential for a seamless customer experience. However, with millions of products sold in e-commerce or brick and retail shops, the scope for human error also increases. Retailers are now realizing the scope of improving the process and have slowly started integrating RPA to assign attributes and categorize products based on the customized product mapping rules. The automated process of product categorization helps in giving proper taxonomy to every product, which allows the customer to find them when they search for it.

Case Study

1. Business & Sales Analytics

For multiple retail decisions, such as trade promotions, churn rate, and product introductions, sales analytics is the key. RPA in sales can automate sales analytics by offering data-based, real-time reports on customer preferences and user behavior related to particular aspects of a product. Utilizing these reports, you can analyze why a few customers are phasing out and use this opportunity to retain these users. Further, RPA analytics also helps in forecasting or predictive analysis, which supports stock optimization.

2. Store Planning & Inventory Management

The old-school, in-store strategy of retail is to arrange the store according to existing customer preferences and requirements. And this is still relevant. For instance, if you shop from a store regularly and the retail owner strategically places products based on your requirements, you are likely to complete purchase early. When the user can find relevant products without much hassle, that is a high selling point. However, the issue with traditional methods is that it is only possible for human interpreters to consider a few significant factors. This is because the nuances extracted from high-level sales data can’t be analyzed by human analysts alone. They need support from technology, which is effectively offered by smart automation. RPA in the retail sector can help you analyze the organization of your store to fit customer expectations, improve user experience, and boost profits.

3. Demand-Supply Planning

What is demand-supply planning? Based on the demand of the user regarding a particular product or service, organizations create a supply plan to fulfill this demand. Traditionally, this was achieved by gathering data, standardizing of this data, simulations, and other such activities. Needless to say, this was executed manually, and hence, guesswork was also a major element of the structure. With RPA in the retail sector, demand-supply planning can be automated. You would also be able to make data-driven decisions for asset management, customer support, supplier management, and capacity management.

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