Resilience begins with final-mile visibility and ends with prescriptive analytics to forecast and plan for demand swings. Here’s a breakdown of the major challenges.

 Getting the final mile right.

Now in its third year, COVID-19 is putting fewer people in the hospital but keeping more of the workforce out sick and reluctant to return to work, as inflation and recession pressures curb consumer and business demand. Labor shortages, stranded equipment and associated port and rail congestion persist. In short, supply chain capacity and demand remain badly misaligned.

Most shippers, meanwhile, still lack the actionable shipment visibility and insights into their broader operations which they need to quickly respond as conditions change, let alone an ability to anticipate disruption and recommend corrective action.

Final-mile visibility is a principal concern as B2C and B2B e-commerce now extends beyond online sellers to brick-and-mortar manufacturers, wholesalers and retailers. The final mile is increasingly where the bulk of shipment cost and capital spend is concentrated in managing more and smaller shipments, multiple fulfillment options and high customer expectations for on-time, in-full (OTIF) delivery.

Current inflationary cost pressures in trucks, fuel, wages, warehouse space, automation and packaging materials compound the challenges. “You can’t pass all of those costs on to customers,” explains Mathew Witte, senior vice president with Atlanta-based supply chain optimization software platform and consultancy ORTEC. “The last mile is a last chance to grab meaningful savings.”

 Retail’s unique needs.

Universal final-mile goals are to increase profit, improve service, and reduce risk. Final mile is the last chance for an organization to offset costs, make up for an earlier failure, or make a final impression for that customer to buy again.

“For retailers this involves controlling frequencies and load capacities as well as asset utilization. Those who effectively use the right analytics tools are the ones who are ahead of the game,” adds Witte. Retailers are particularly vulnerable to capacity-demand dislocation from COVID, inflation and other external forces. A lack of granular demand forecasting has prompted frantic seasonal restocking of goods, just as consumer spending is shifting to travel and to basics like gas, groceries and utilities. From Walmart and Target to small specialty apparel or electronics brands, retailers are left to sell off unwanted inventory at steep discounts to avoid high storage costs.

Larger retail players enjoy a greater degree of control delivering to their own stores, reconfiguring space for B2C and B2B fulfillment and managing inventory internally. Beyond that, omnichannel complexity poses unique risks in warehouse pick and pack, route and load planning, parcel pricing and return logistics, all making optimization of assets, facilities and processes a top priority for improving performance, managing costs and meeting delivery commitments. 

 Getting the most out of a TMS.

Transportation management systems (TMS) aren’t designed to provide the level of last-mile visibility required for a modern, agile, resilient supply chain. Their MAIN focus is completion of discrete steps in an order fulfillment rather than shipment track and trace, resulting in significant end-to-end visibility gaps. To achieve full savings potential, existing TMS users gain additional efficiencies through a robust optimization and analytics platform.

Today’s supply chains need more precise, timely detail to predict and update arrival times (ETAs) or redirect assets or inventory to meet service-level agreement (SLA) or other time-definite delivery commitments. That same level of detail, over time, is also needed to sense and interpret demand signals early, track supplier and carrier performance and identify operational chokepoints.

“The value of a conventional transportation management system (TMS) is in mid-mile, inbound freight audit and pay, and there is tremendous value in those features,” Witte says. “The last mile often tends to be an afterthought, but that’s where much of the cost is now, where you really want to make an impact.”

 Visibility in the cloud.

Modular cloud-based software-as-a-service (SaaS ) solutions, layered over a TMS or other enterprise software, fill in the shipment visibility gaps, tracking end-to-end shipment location and status, and generating exception alerts. Analytics modules continuously monitor shipment and contextual data – traffic, weather, market events – to assess performance against established key performance indicators (KPIs) and recommend improvements. Customizable, user-friendly dashboards and visualization tools make real-time data accessible when, where and in the format needed.

Supply chain platform solutions first attracted investor attention in response to e-commerce. COVID accelerated investment dramatically, but many startups have been slow to develop the requisite partner relationships, in-house expertise or understanding of organizational change management on the business and supply chain sides, and integration can be a challenge.  

“The success stories, the companies that have adapted to COVID and come out stronger on the other side, are the companies that embraced technology and change management early,” Witte explains. “But also weren’t afraid to ask the all-important question, ‘what if?’ What if we reduce service frequency to meet demand growth with the same number of trucks? What if we can get one more stop on a route, or load one more pallet or 1,000 more pounds on a truck?  The answers to those questions will be data-driven. 

 Forecasting and demand planning.

The Holy Grail, beyond real-time visibility or predictive analytics to forecast demand and anticipate disruption ahead, is prescriptive analytics that can instantly assess facts on the ground in the context of the supply chain current state and then recommend both immediate responses to disruption and longer-term operational and resource planning options based on company-specific capabilities and business objectives.

Aligning capacity with demand isn’t just central to competitive advantage going forward, but in many cases to survival in an emerging post-COVID environment. That will require breaking the current cycle of disruption and getting out in front of future crises by optimizing people and processes, in order to begin proactive longer-term planning for future growth.  

“Nimbleness is the key to success in today’s world,” says Witte. “Looking back to the start of COVID, where the economy seemed to simply stop in its tracks; those companies who had the foresight to conduct basic modeling of their operations  - the tools to plan even a 10% change in their business – were the ones who performed the best. Companies that did not have the tools or discipline to forecast the final mile have had difficulty surviving, as they were not prepared when business returned.”

ORTEC Sees Supply Chain Optimization as a Math Problem

“Change management and change leadership are often overlooked in technology investments. There is a well-known resistance curve in any organizational change and having the resources to manage this change at all levels of an organization is a key indicator of success,” adds Witte.

ORTEC, headquartered in the Netherlands with U.S. operations based in Atlanta, is a leading global supplier of mathematical optimization software and advanced analytics, with some 1,200 employees and offices in 13 countries. Established in 1980 by mathematics faculty and students, it has helped more than 2,000 customer locations optimize their business processes.

ORTEC offers manufacturing, distribution, retail and logistics clients supply chain software solutions and consulting support. Its platform solutions add shipment visibility, optimize routes and loads; reduce cost per mile and service failures, manage vehicle capacity, and improve OTIF fulfillment, sustainability and customer satisfaction; and fully integrate with conventional TMS, WMS and other enterprise software systems.

A retail workforce scheduling module for stores and warehouses incorporates customer preferences, business requirements and labor regulations. Scalable analytics and machine learning leverage big data and internet of things (IoT) capability to generate insights about customers, margins, fleet mix and workforce, and to make critical decisions about personal marketing, dynamic pricing and media buying.

Major worldwide clients include Carrefour, Tesco, Procter & Gamble, Coca-Cola, Ben & Jerry’s, and Georgia-Pacific. Through its Analytics Academy and university ties in the US and Amsterdam, ORTEC helps to develop industry optimization standards and performance metrics.