Exploring the Factors Preventing Retailers From Optimizing Loading and Routing

Retail logistics optimization has become a significant factor in maintaining a competitive edge. However, many retailers struggle to effectively implement artificial intelligence (AI) and software solutions for their supply chain. This disconnect often stems from a misalignment between C-level decision-makers and operational teams, leading to suboptimal results and missed opportunities for true optimization.

These are important decisions because a growing number of retail operations professionals today admit they aren’t optimized enough in their operations. Over half of respondents (52 percent) in a recent survey rated their organization's current last-mile delivery planning effectiveness as below “excellent” or “good.” Additionally, the survey found that nearly 40 percent of respondents need to adjust delivery routes multiple times per day due to unexpected delays, emphasizing the pressing need for innovative solutions.

Understanding the Role of Software Optimization

One of the primary challenges in implementing AI and software solutions is the lack of a holistic view of retail logistics. Many companies focus solely on individual components, such as inventory management or last-mile delivery logistics, without considering how these elements interact within the broader ecosystem. Unfortunately, a siloed approach often leads to inefficiencies and missed opportunities for optimization across the entire retail supply chain.

Data quality and integration pose additional challenges. AI and machine learning algorithms rely heavily on accurate, comprehensive data to generate meaningful insights and recommendations. However, many retailers struggle with data silos, inconsistent data formats, and outdated information, which may undermine the effectiveness of even the most sophisticated software solutions.

Furthermore, there's often a lack of alignment between the metrics used to measure success at the C-suite level and those used by operational teams. This misalignment can lead to conflicting priorities and a failure to realize the full potential of technology investments.

Related story: How AI and Automation Are Leading Retail Supply Chains Into the Future

Smarter Load Optimization

Moving beyond these implementation challenges, let's examine the critical area of shipment load optimization in warehouses. Many retailers today are utilizing optimization software that focuses solely on downstream processes at the inventory level. While such strategies yield some benefits, they significantly limit flexibility and responsiveness to changing market conditions.

Forward-thinking retailers are recognizing the need for more sophisticated software solutions that allow for upstream optimization. Such strategies enable retailers to make last-minute changes to orders, responding dynamically to shifts in demand or supply chain disruptions. By optimizing shipment loads upstream, companies can better align their operations with real-time market conditions, improving efficiency and shopper satisfaction.

A key component of upstream optimization is the ability to perform dynamic builds, reconfiguring truck shipment loads with proper “stackability” to ensure each axle is weight-optimized. This capability allows retailers to maximize the number of pallets loaded onto trucks without risking fines during road checks. By reconfiguring the way pallets sit in a trailer, and taking axle weight into consideration, retailers can consistently build to 45k lbs. vs. the industry average of ~40k lbs., often resulting in additional shipments per load. This, over time, reduces the number of trucks on the road required to fulfill store orders.

It's imperative to optimize the loading process by maximizing cube utilization, ensuring that every inch of available space is effectively utilized. By leveraging advanced algorithms and real-time data analytics, these solutions can calculate the optimal arrangement of products within a shipping container or vehicle, taking into account factors such as weight distribution, product dimensions, and handling requirements. This not only minimizes wasted space but also enhances overall operational efficiency by reducing the number of trips required for deliveries. As a result, businesses can lower transportation costs, improve delivery timelines, and increase customer satisfaction by ensuring that products arrive in a timely and organized manner. With load building solutions, companies can achieve a more sustainable and cost-effective approach to logistics, ultimately driving greater profitability and competitiveness in the market.

The shift toward upstream optimization represents a fundamental change in how retailers approach their supply chain operations. Instead of reactively optimizing based on fixed orders, retailers may proactively adjust their strategies based on a holistic view of demand forecasts and order builds. These strategies not only improve operational efficiency but also enhance the retailer's ability to respond to market fluctuations and customer orders.

However, implementing such sophisticated optimization systems requires more than just software investment. It demands a strategic overhaul of existing processes and a willingness to embrace data-driven decision-making at all levels of the organization. Retailers must be prepared to reevaluate their entire supply chain strategy, from demand forecasting to order fulfillment, to fully leverage the benefits of upstream optimization.

Is Your Routing Truly Dynamic?

The final piece of the puzzle in retail supply chain optimization is dynamic routing. Many retailers still rely on static routing methods, which lack the flexibility and agility required in today's fast-paced retail environment. Limitations of static routing become particularly apparent in the face of unexpected events, such as traffic disruptions, weather conditions, or last-minute order changes.

Dynamic routing offers a solution to these challenges by continuously optimizing delivery routes based on real-time data and changing conditions. However, simply investing in dynamic routing software isn't enough. Retailers need to build the right strategy to adopt and implement this technology effectively. Strategy vs. implementation is where the disconnect between C-level executives and operational teams often becomes most apparent.

While C-suite leaders may be eager to invest in cutting-edge routing software, operational teams need support in refining their processes before the software may be truly effective. A detailed refinement process involves a deep analysis of current routing practices, identification of bottlenecks and inefficiencies, and development of new strategies that fully leverage the capabilities of dynamic routing technology.

Moreover, retailers must focus on leveraging the right analytics and metrics to make ongoing adjustments to their routing strategies. Many organizations fail to implement a system for continuous improvement, missing out on opportunities to further optimize their operations over time, an oversight that significantly limits the long-term value of their technology investments.

While AI and machine learning play crucial roles in dynamic routing, it's important to recognize that they're not silver bullets. These technologies are powerful tools, but they require human expertise to interpret results and make strategic decisions. For instance, learning drive times and stop times is critical for accurate routing, but understanding how to analyze the cost of each store delivery based on various variables requires human insight and strategic thinking.

By combining AI-driven insights with human expertise, retailers are able to make more informed decisions about customer service levels. A revised approach may mean reducing the frequency of deliveries to certain stores from four or five times a week to three, based on a comprehensive analysis of costs and benefits. Adjusting service frequency is just one facet of a strategic approach to routing optimization that leads to significant cost savings and improved overall efficiency.

The key to successful retail supply chain optimization lies in the seamless integration of technology and strategy. Retailers must bridge the gap between C-level vision and operational realities, implement sophisticated upstream load optimization, and embrace dynamic routing with a focus on continuous improvement. By adopting a holistic approach, retailers may truly optimize their supply chains, improving efficiency, reducing costs, and enhancing customer satisfaction in an increasingly competitive marketplace.

Aaron Geiger is the managing director of manufacturing and CPG/retail for ORTEC, a leading provider of advanced analytics and optimization solutions.