This article originally appeared in the September/October issue of PARCEL.

Thinking five to 10 years ahead, leading North American executives are increasingly turning to multi-modal data science to address the enterprise impact of soaring parcel volumes across the global supply chain. According to leading industry reports, parcel and express delivery volume has surpassed railroads as the second-largest logistics sector behind motor freight. Spending on small-package delivery jumped double digits in the last year. E-commerce sales as a percentage of retail sales nearly tripled in the last decade. And economic analysts predict parcel spending will surge to nearly $95 billion by 2019. These collective disruptions are bigger than the transportation profit and loss. Business concerns related to parcel shipping acceleration and omni-channel complexity have reached the C-Suite. With smart devices fueling parcel growth, smarter supply chains are on the board room table.

Managing disruptive change in logistics networks requires layers of multi-modal expertise supported by risk mitigation strategies. The most successful omni-channel shippers say the real game-changer for managing business growth in light of the e-commerce explosion is access to top-flight intellectual capital across all transportation modes. Smart engineering ensures shipping programs and the end-to-end supply chain are optimized for performance and customer satisfaction.

Successfully reconfiguring transportation and supply chain networks to meet escalating delivery expectations starts with understanding the data behind parcel trends and distribution network changes. High-volume parcel shippers leverage smart solutions, such as advanced analytics, digital technologies, and innovative transformational strategies, to create better alignment to the carrier networks. By understanding how a delivery profile impacts every carrier’s network, companies can adjust their shipping profile to optimize and align for maximum efficiency and serviceability. Companies often begin the process by getting answers to fundamental logistics questions:

Today, more shippers are finding success with a supply chain optimization process that originates from Lean methodologies and adds deep data analysis to the mix. By applying network design tools to leverage data from across the supply chain — from procurement to shipping — shippers can obtain a clear picture of inventory levels, cost to serve customers, SKU positions, transportation costs and performance, raw material costs, and production costs. This deep data analysis reveals opportunities to enhance performance and determine where to focus efforts toward meeting strategic goals. When complemented with rich domain experience, it ensures that the transportation network is agile and optimized for profitability, not just survival.

As part of the evolution of enterprise excellence, leaders who understand the importance of an enterprise logistics approach are taking a holistic, strategic view of the supply chain to gain competitive advantage by following these best practices.

Establish a Current Supply Chain Performance Baseline

• Review the current state of shipping operations from an operational, analytical, and cost-based perspective.

• Develop an understanding of the changing role that parcel plays in the overall network.

• Be realistic about how much e-commerce and customer expectations will change strategy.

• Identify customer service needs and how parcel shipping will change financial goals and logistics requirements.

Leverage Visual and Analytical Tools to Design the Future State