Tackling the spoilage menace

Supermarkets throw away 43 billion pounds of food every year due to spoilage. Not only does this impact their bottom line directly, but it also adversely impacts customer perception of their brands.

For example, every piece of produce past its “best by date” results in a 100% negative margin for the retailer. To prevent spoilage and lost margins, supermarkets typically adopt a dynamic pricing model wherein each SKU is classified into the following four broad categories based on remaining shelf life: 1) full price, 2) promotional price, 3) clearance price, and 4) zero price  (when produce is thrown away or given for free) .

Unsold products move across each stage as time passes and, as they move, the margins for the retailer get progressively smaller. The store manager’s prerogative, therefore, is to move unsold products on time and efficiently from one stage to another and label and place them on the appropriate shelves to further the chances of a sale. Most supermarkets today follow a labor-intensive process for this, leveraging some form of paper-based operational reports. Store signage is used to attract customers to marked down items.

Leveraging technology to reduce spoilage

To reduce spoilage, it is essential to have products on store shelves as soon as possible and spend maximum time in the appropriate place.

To do this more efficiently, retailers are experimenting with the latest technologies, including artificial intelligence, digital inspection, and store automation. However, many supermarkets have yet to figure out how to do this effectively and are still losing money.

To reduce spoilage and cut losses, retailers need to adopt a multi-pronged, graded approach that leverages the latest technologies to reduce food spoilage. Here are the key elements of a successful approach:

1. Optimized demand forecasting

Retailers need to begin by ensuring that their existing demand or sales data is cleansed and leveraged for optimized shelf replenishment. The data should be made available to the appropriate store personnel at the right time – and ideally in real time – to enable them to make the right replenishments decisions. When coupled with better tracking of forecasting errors via AI-powered demand forecasting solutions which relies on real time inventory and sales data, spoilage can be reduced considerably.

2. Process analysis

Process mining is a systematic approach to identifying systemic and process inefficiencies that can lead to spoilage. Many process mining tools are available that leverage time-stamped digital footprints in retail IT systems to help businesses identify and quantify the financial impact of process deviations and bottlenecks. With this technology, stores can analyze and improve the entire process cycle of “fresh” SKUs, from production or sourcing to sale.

3. Actionable operational dashboards

Retailers need to build real-time operational dashboards at every stage of sale with actionable instructions on what needs to be done. With these dashboards, store managers can be prompted in real time to mark down SKUs by the right amount when sales are missing the forecast. This is made possible with AI technologies.

4. Automation

A recent study from the Capgemini Research Institute reveals that 69% of consumers prefer to shop with retailers that use automation technology to reduce food waste, and there are several new automation alternatives available for retailers to reduce spoilage. Although these options come at a capital cost, they have the potential to pay for themselves over time. For example, electronic shelf labels (ESL) enable dynamic pricing by showing pricing changes at a click of a button. Similarly, RFID technology alerts store staff about go-backs or abandons to help items such as produce get back to the right place. IoT sensors have much potential in stores ensuring produce is always maintained in the right condition.

5. Personalized engagement with loyalty customers

Loyalty apps are not just the gateway to engaging with your most valuable customers; they can also serve as a key channel for addressing spoilage. Retailers can leverage loyalty data to tailor content and promotions for perishable items to the customers who are most likely to buy. This would mean customizing promotions to specific preferences rather than sending a generic mailer for all products. This also means thinking about clearance products with the lowest margins as an opportunity to entice bargain hunters.

6. Aggregator apps and corporate social responsibility

Apps such as Flashfood and Food for All re-sell groceries approaching their “best-by” date at a discount to customers in order to prevent food waste. Some of these apps also cater to retailers’ corporate social responsibility initiatives by donating the products close to their “best-by” dates to food banks and soup kitchens to ensure that food does not go waste and minimize disposal costs.

Capgemini has worked with grocers of all types to implement the solutions mentioned above to address the spoilage issue and would be happy to work with you. To start with, we would begin with extracting some operational data to assess the signs and extent of spoilage. This would help identify the solution that would generate the greatest return for your business.

This article is co-authored by Chiranth Ramaswamy.

Kashif Khan

Expert in Data analysis, Digital Manufacturing, Digital Transformation, Finance and Accounts, Procurement

At Capgemini, I am a part of the Digital Solutions and Consulting team with a primary focus on helping our clients thrive in the digital age through best practices and innovation.
I have 18+ years of experience in Consulting and Delivery across IT, ITES and Manufacturing Industry handling clients across industry domain.
Along with expertise in managing end-to-end Accounting, Source-To-Pay and Supply Chain Operations, I have also been involved in various Software Product Development (Conceptualization to Delivery) and maintenance projects.
I am also an experienced and advanced Certified Scrum Master from Scrum Alliance, with a proven ability to lead and motivate teams and drive Agile and Waterfall projects to success through effective motivation, monitoring and mentoring.
I am passionate about working with data and have Data Engineer and Data Analyst certifications in data mining tools such as Celonis, Aris Process Mining Tool etc.
Lately, I have been investing time to learn software languages like SQL and Python to effectively handle and leverage data to gain insights and help clients achieve their business goals.
Some of my recent work includes-
Data Mining and Analysis for a $ 50 Bn company engaged in natural gas and propane pipeline transport with recommendations to improve their Accounts Payable and Accounts Receivable operations with savings of over $ 10 Mn.
Scrum Master for an onsite maintenance and support project for a major American manufacturer for locomotives, freight cars and passenger transit vehicles.
Building a business case for an S/4HANA-based digital transformation for a specialty chemical manufacturer with a revenue of $5 billion.