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Taming the retail supply chain beast

Publisher: Retail Biz

Author: Rajeev Mitroo, Managing Director Asia Pacific at Aera Technology

taming-the-retail-SC-beast

Times are tough for Australian retail supply chain executives. The stakes are high, as every day seems to bring news of another high-profile setback or failure, particularly since COVID-19 hit.

With a large percentage of retail supply chains involving manufacturing operations or products sourced from overseas, COVID-19 has certainly taken its toll, particularly those relying on Chinese-based manufacturers and warehouses.

Despite these challenges, retailers remain under intense pressure to support the seamless omnichannel experiences that consumers are demanding in the digital world. Meeting those expectations depends a cost-efficient supply chain that can react quickly and accurately. Delivering a superior customer experience is as every bit as important as personalised front-end marketing.

The retail supply chain is a complex beast that’s difficult to tame. A study by Sapio Research found that 94 percent of retailers lack end-to-end visibility of events that affect supply chain performance; 71 percent say a lack of supply chain visibility negatively affects the business; and 87 percent believe that a fully visible supply chain with real-time updates would provide competitive advantage.

Those results aren’t surprising. Nearly two-thirds of retailers and manufacturers still use Excel for supply chain planning, with 46 percent relying on manual, time consuming supply chain processes, according to a study by eyefortransport by Reuters. Traditional planning solutions are no longer suitable for solving today’s complex supply chain challenges.

When a band-aid isn’t enough

Retail supply chains are innovating to better meet customer demands. One example is a pop-up warehouse, situated in high-demand areas to accelerate last-mile delivery. They can also double as a location for consumer pickups or offer a limited retail selection. In addition, retailers are using ship-from-store models, turning physical stores into ad hoc fulfillment centres.

Both models are getting goods to consumers faster, but can introduce additional costs that trim margins. These band-aid solutions don’t address the root cause of supply chain inefficiency: siloed applications, fast-growing data volumes and inherent human limitations.

Excel-based planning and conventional demand forecasting tools that use data from systems for enterprise resource planning (ERP), warehousing, inventory, sales operations and logistics, can’t keep up. Data volumes and application complexity are rising just as fast as consumer expectations.

As a result, retailers can’t react quickly to changes in demand. With lead times set months in advance, they’re slow to adapt if demand soars in one area yet falls in another, or if e-commerce sales exceed projections. They’ll often resort to overstocking inventory, risking high carrying costs and unsold product if sales fall short.

Managing the many dynamics of today’s real-time supply chain is proving virtually impossible for human planners. There’s simply too much data, applications and variables to account for.

Meanwhile, old-school retailers are losing ground to digital natives like Amazon that use next-gen technology such as artificial intelligence (AI) to help optimise the supply chain and consumer experience. Retailers must start thinking about how to use new analytics technology to not only analyse and understand the past, but to make better decisions for the future.

Moving forward with automation

AI is giving retailers ground-breaking capabilities to run faster, more visible and less-costly supply chains. It’s a foundational technology in what’s called cognitive automation, which brings deep machine learning (ML) analytics into supply chain operations.

An AI-powered cognitive automation platform will do data crawls thousands of times a day across all relevant applications, aggregating that information into a single cognitive data layer. This is where AI and ML algorithms are applied to analyse situations, predict outcomes and make recommendations for optimal actions based on objectives such as reallocating inventory, reducing costs or speeding up delivery times.

Unlike conventional methods, these insights are based on near real-time information, rather than drawing on data that’s weeks or months old. Trends and issues are spotted as they unfold to enable swift intervention. Since cognitive automation is connected to transactional systems, corrective measures can execute automatically, without humans having to log into systems to modify processes.

Cognitive automation can provide retailers with the following key benefits:

Better forecasting by consolidating highly granular SKU-level data across multiple applications, channels and geographies. AI analysis of sales trends, demographics, SKU varieties and other variables improves accuracy in having the right product in the right place at the right time.

Agile inventory reallocation by constantly analysing real-time stock and sales data with a speed and scope not possible with traditional tools. It makes recommendations to reallocate inventory as conditions change or may suggest promotions for undersold goods.

Integrated planning by drawing on a broad range of data, cognitive automation that helps retailers coordinate across production, inventory, marketing, merchandising, promotions, logistics and other areas that are typically siloed. Retailers can make data-driven decisions across full lifecycles, rather than relying on educated guesses.

Improvements in transportation and logistics by enabling retailers to accelerate fulfillment and minimise costs by analysing real-time variables such as on-hand inventory, demand fluctuations, carrier availability, freight costs, lead times and more. If disruption occurs, AI will recommend alternatives to meet objectives.

Disruption across the Australian retail landscape will continue beyond this year. It’s becoming increasingly clear that technological innovation is what separates winning retailers from the laggards. Retailers that invest smartly in technology to make data-driven decisions and orchestrate processes, will be equipped to survive and thrive in a fast-changing industry.

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