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Home » Blogs » Think Tank » Bridging the Gap: Turning Data Into Action for Grocery Retail Success

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Bridging the Gap: Turning Data Into Action for Grocery Retail Success

ORANGES SIT STACKED IN PLASTIC CRATES, MANY TIERS TALL

Photo: iStock / SonerCdem

December 5, 2024
Greg Wilson, SCB Contributor

Grocery retailers are sitting on a wealth of data, from customer buying habits to inventory levels. Yet many still struggle to make effective use of it.

Despite advances in technology, the challenge of transforming raw data into insights that drive business improvement remains. Solving this problem requires more than just new tools; it demands a fundamental shift in how retailers approach and integrate data across their operations. 

Many grocery retailers today are overwhelmed by the sheer amount of data available to them. From point-of-sale transactions to real-time inventory updates, every aspect of operations generates data, yet much of it remains unused or underutilized. Many still rely on manual processes, such as spreadsheet reporting and data entry, which slows decision-making and creates inefficiencies across departments. This is particularly important in fresh produce management, where overstocking or understocking can lead to waste and missed sales.

Traditional methods simply can’t keep up with the pace and complexity of modern retail demands. Retailers are left with incomplete views of their operations, leading to poor inventory management, missed promotional opportunities and inefficiencies that affect both profitability and customer satisfaction. Traditional systems only perform as well as their input data permits.

Artificial intelligence and machine learning can help address data integrity issues, and anticipate external disruptions using real-time and historical data. To make that possible, however, retailers must undergo a strategic shift in how that data is approached within the organization. 

The Role of AI and ML 
AI and ML are transforming how grocery retailers convert vast amounts of data into meaningful insights. These technologies automate decision-making across areas like assortments, promotions and replenishment. In fresh produce management, AI can track key variables such as shelf life and sales patterns, and external factors like weather, enabling retailers to optimize stock levels and reduce waste. Instead of manually adjusting based on rough estimates, AI-driven tools deliver real-time, data-based recommendations, helping retailers precisely manage inventory to meet customer demand while minimizing spoilage. 

In today’s cost-conscious environment, pricing and promotion optimization is especially crucial. A recent report by Incisiv revealed that promotions drive more than $1 trillion in sales for retailers, yet many are still using outdated methods such as spreadsheets to manage promotions. With AI and ML, retailers can unify their pricing and promotions strategies, ensuring that promotions are tailored to customer preferences and are aligned with overall business goals. 

Retailers can use these technologies to streamline operations across the board, from pricing strategies to workforce management. Fresh produce, with its perishable nature, benefits from automated forecasting and replenishment made possible by AI, reducing waste and ensuring the freshest items are always available to customers. By automating data analysis, grocery retailers can focus on strategic, high-impact decisions rather than being bogged down by manual processes and guesswork. 

Barriers to Decision-Making 
Even with advanced tools available, grocery retailers face barriers to implementing AI. One of the most common challenges is the integration of new technologies with legacy systems. Many retailers rely on outdated infrastructure that isn’t designed to work seamlessly with AI-driven platforms, creating friction and delaying the benefits of implementation.

A key benefit of using AI and ML technologies is their ability to offer hybrid or “good-better-best” integration options, allowing grocers to mature into more advanced capabilities while balancing legacy technology and operational enablement. 

Another challenge is the resistance to change from within the organization. Employees, especially those in-store, may be hesitant to adopt new technologies that seem complex or difficult to use. Overcoming these barriers requires more than just technological upgrades — it necessitates a cultural shift within the organization. Retailers need to foster a data-driven culture, where employees at all levels understand the value of data and are empowered to use it in their daily tasks. 

To ease this transition, it’s crucial to invest in intuitive, user-friendly tools that reduce the learning curve for store associates and managers. These tools should integrate seamlessly into existing workflows, helping employees make better, data-informed decisions without feeling overwhelmed by new technology. 

A Data-Driven Culture 
Creating a data-driven culture is about more than just implementing AI and ML. It’s about changing the way teams collaborate and make decisions. Data needs to be truly accessible and understandable across departments, from IT and operations to merchandising and customer service. 

Retailers can foster this culture by encouraging cross-departmental collaboration. When departments such as IT and merchandising work together, data can flow more easily through the organization. Additionally, empowering store employees with real-time data -— whether it's stock levels, customer preferences, or sales trends — can lead to more informed decisions at every level of the organization.

As grocery retail continues to evolve, the role of advanced technologies will only become more critical. In the next five to 10 years, these innovations will move beyond optimization into areas such as hyper-personalization and predictive analytics. Retailers who invest in AI and ML today are positioning themselves to stay competitive in an industry that demands speed, accuracy and adaptability. 

Pricing and promotions will continue to be key focus areas, especially as retailers aim to capture more value from data-driven promotional strategies. As AI-powered tools become more sophisticated, retailers will be able to make pricing and promotion decisions in real-time, responding quickly to customer behavior and market trends.

Overcoming data utilization challenges is crucial for grocery retailers looking to stay ahead in a rapidly evolving industry. By adopting AI-powered systems and fostering a data-driven culture, retailers can turn raw data into insights that drive better decision-making, optimize operations, and enhance the customer experience. Now is the time for grocery retailers to invest in these technologies and organizational shifts, and ensure that they’re prepared for the future of retail.

Greg Wilson is vice president of field strategy with Relex Solutions.

Artificial Intelligence Data Management (Big Data/IoT/Blockchain) Forecasting & Demand Planning Inventory Planning/ Optimization Food & Beverage Retail

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