Data-driven cost optimization in retail. Part 1: The value of using data to reduce costs

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Today retailers can collect and process massive amounts of rich and diverse data, enabling them to position for creative disruption in every aspect of the decision-making process.

The growing economic uncertainties at the beginning of 2020 due to sudden and unforeseen developments are pushing retailers to fast-track cost-optimization initiatives to stay competitive and sustain their bottom lines. Furthermore, in a hyper-competitive age of e-commerce, retailers face massive investment demands and are looking aggressively for “cost-out” opportunities to re-invest in growth initiatives.

Fortune 1000 retailers were among the earliest and most aggressive backers of the data-driven enterprise in several areas, including marketing, customer experience, promotions, and pricing. Yet many have been hesitant to fully embrace a data-driven culture in all areas of the business, due to worries about business disruptions and challenges in data integration.

Significant advancements in the world of AI/ML, IoT, 5G, computer vision, robotics, and geo-spatial is opening incredible new opportunities for exponential cost benefits. Businesses need to blur the boundaries between digital-transformation and cost-optimization initiatives to unlock true potential. The cost champions leverage data and insights at the core of their business to identify key opportunities, to operate at peak efficiency, and also to reinvest into their growth journey. The data-driven, technology-enabled approach for cost optimization will position any retailer into the champions league.

The digital era opened up new opportunities for retailers to digitize everything they do. For example, digitizing customer and supplier interactions has provided a wealth of information to grow the top line by activating marketing, sales, product development, and supply chain, whereas digitizing internal processes generated data and insights to optimize operations and improve productivity and the bottom line.

In this multi-part blog series on data-driven retail, we will explore how retailers can move towards a continuous data-driven cost optimization culture.

The case for optimizing costs with data

Unlike a few years ago, when retailers relied on traditional performance metrics and tacit knowledge to optimize cost in their supply chain, inventory, or marketing, today their ability to collect and process massive amounts of data has significantly changed. It’s not just about volume; data itself gained tremendous richness and diversity. The confluence of data, storage, computational power, and algorithms has positioned retailers for creative disruption in every aspect of the decision-making process.

Retail cost leaders are already reaping the benefits from an insights-driven approach, armed with data to, for instance, develop a deeper understanding of the products consumers really value. They can then manage negotiations with suppliers and reward those who actually drive category sales. But still, far too few retailers are consistently embedding analytics, data, and evidence-based reasoning in all aspects of their decision-making processes.

Key cost levers for retailers

The increasing demands for business agility, the evolving technology stack, resource constraints, and a changing regulatory landscape mean businesses need a comprehensive data-driven approach for cost optimization. They should not continue to operate with a narrow, fragmented, tactical point-solutions approach.

Retailers have opportunities across the retail value chain, including marketing, buying and merchandising, supply chain, inventory, distribution, delivery, and operations (both store and digital), as well as in the areas of IT, finance, HR, and legal processes. They can use historical data trends to scrutinize every business process and arrive at an optimal strategy.

For example, IT can look at opportunities in the standardization and rationalization of hardware, software, platforms, applications, processes, and services. These might include moving into cloud to exploit a pay-as-you-go pricing model and maximizing open-source software deployment in place of commercial software. Several tools are available to capture data around current infrastructure, application, and data landscape to spot the right opportunities.

Retailers should look to strategically reimagine core business processes using IoT, AI/ML, computer vision, and robotics, etc. This is where they can gain the most, not only in terms of cost but also in business value creation – for example: AI/ML assisted demand forecasting and inventory planning, cognitive sourcing and procurement, robotics assisted warehousing, etc.

Lastly, internal operations or support functions can focus on automating and digitizing IT and business operations using a machine-first approach, with tools such as AI/ML, RPA, and image processing.

With the case made for optimizing cost through data, I will explain in part two of this blog how companies can actually implement the required systems and processes.

To learn more about data-driven cost-optimization, please contact me via my Expert Connect profile.

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