Parcel Shipping Economics and Operational Requirements Have Evolved, so Should Your Approach to Data Analysis

Here are nine use cases to help you understand the value of simulation modeling techniques

By: Jesse Gates, Co-Founder, Forerunners Consulting

To keep up with the growing complexity of e-commerce fulfillment and the supporting logistics operational requirements, parcel analysis techniques and the enabling software have been forced to modernize. As the questions being asked have become more nuanced, so have the ways we think about modeling the answers. Typical legacy problems were limited to understanding service selection and time-in-transit decisions during a sourcing project. Once those answers were determined in a complex spreadsheet scenario analysis, static business rules were then translated into classic shipment execution systems, like a Ronco rotisserie chicken – ‘set it and forget it’.

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Today, there are so many more variables to consider (and fortunately better options for analysis than Excel): dynamic omni-channel fulfillment locations; more diversified carrier service options; frequent surcharge changes; more complex carrier incentive levers; more packaging options; and advanced operational capabilities to consider. With more complex variables come a proliferation in possible outcomes in terms of bottom-line savings or cost increase minimization, as well as service level improvement opportunities. To optimize insights and results, we need analysis tools that can evolve with the business. Logistics managers need more control without having to rely on costly custom programming and long project timelines which no one has time for.

Here are nine use cases on how to enable simulation capabilities using Sendflex’s parcel TMS solution.

Omnichannel fulfillment has driven the first two use cases: distributed order management and adding (or removing) nodes.

  1. Network design and transportation design are two very different disciplines that are commonly confused with each other. When considering a network change, decision makers need to distinguish the incremental benefits of moving closer to (or further from) their customers versus pulling a transportation lever, such as service level expansion or rate sourcing.

With tools like Sendflex, you can quickly, and incrementally, model multiple network strategies using the same transportation rates/service to establish a baseline to compare alternative transportation strategies against (like rate sourcing or service level changes).

  1. This same approach can be applied to distributed order management by comparing transportation outcomes against multiple order sourcing strategies. Whether making changes to your network footprint or how your network directs volume, what-if analysis coming directly from your shipment execution platform will give you the most practical outcomes to execute against.

The next four use cases are intimately intertwined: mode conversion, service-level modeling, regional carrier diversification, and revenue attainment tier FOMO.

  1. Mode conversion analysis involves understanding how shifting between express, ground, and less-than-truckload while keeping the same service commitment, will impact the cost and logistics operation. Mode conversion analysis should come first as it carries the most significant operational implications (i.e., pick up times, dock doors, pack/staging needs).
  2. Service-level modeling is about throttling speed of delivery based on what the consumer is promised and the desire to subsidize free. Applications like Sendflex can model various service-level scenarios because it executes those same scenarios day in and day out.
  3. Regional carrier diversification has become more and more popular as they improve on-time delivery, technology, and geographic reach all while FedEx and UPS increase prices and create shipper volume caps during peak periods as to optimize their networks. These regional networks add value because they are different than legacy national carriers, and therefore their rate structures, accessorials, and transit times are different as well.
  4. Revenue attainment tiers or earned discounts is fear mongering to increase reliance on a single carrier, or at least significantly limit the number of packages manifested/tendered to other carriers. Regional carrier variation and revenue attainment optimization is accommodated by applications like Sendflex but very difficult to replicate in excel or static carrier assignment modules in an ERP. Simulating one or many of these in tandem is only possible, at scale and with speed, on an application like Sendflex.

The next three use cases are applicable to both the shipper and the logistics service providers: containerization for package engineering opportunities, zone skipping, and understanding regional partner network optimization.

  1. For simplicity’s sake, we see most companies choose a limited number of shipping box sizes and then stick with those for the long-term. A parcel analysis tool and execution tool which can analyze and optimize packaging size, without involving an industrial engineer, is a game changer.
  2. Assuming operational, one of the most impactful cost and speed maneuvers is the zone skip, however most parcel-focused applications are shipment-centric, meaning they assume a one-to-one relationship between the order and the shipment, and therefore do not have the architecture to consolidate shipments into load, shifting the parcel-package origin to a downstream facility (such as a carrier terminal) reducing the effective ratable zone of said shipment. Also, most zone skipping scenarios are faster due to the direct linehaul segment (assuming we are comparing long-haul ground or regional express).
  3. Finally, many logistics service providers have multiple partner options per large region, so having the ability to optimize injections at a macro-level can improve their margins – a capability unique to tools like Sendflex.

An all-in-one what-if simulation modeling, planning, and execution in single application like Sendflex, improves analytical capabilities and the ability to execute against the desired future-state. This type of tool can maintain high-quality historical shipment data in one place for on-going simulations – no more cleaning and porting data from place to place. Like the transactional data, the pricing / historical rate and transit information is in the same place as well. No more baseline price / rate establishment necessary. For speed purposes, those are native, so there is no reliance on API latency or throttling or associated fees or penalties during peak rating periods.

Best of all, Sendflex features no-code business rules configurations that enable logistics managers or analysts to define optimization constraints at a more granular level than could otherwise be accomplished by hard coded programming. Configure in minutes what would otherwise take weeks of development and testing to accomplish.

Lastly, there is no need for duplicated business rule configuration or maintenance between different applications. Having these capabilities in one place allows for quick and consistent analysis, and therefore reduced business case discounting on simulated versus expected savings. Insights gained during the simulation modeling process can immediately be operationalized in planning and execution processes.

In conclusion, external pressures from the consumer environment and underlying technology delivery methods have created a great opportunity for those responsible for supporting decision making – better tools to support more complex scenarios. In most transportation and logistics technology landscapes, understanding ‘what is possible’ across applications usually gets more convoluted. However, here we have a situation of simplicity through convergence; Sendflex has on-boarded folks like Forerunners rapidly to create value for several clients across various use cases, with low friction on-boarding, powerful software, and great outcomes for the clients.

About Jesse Gates:

Jesse Gates is a co-founder at Forerunners and is a subject matter expert on Shipper/3PL strategy, logistics systems, specializing in transportation management (TMS) and shipment execution. He spent the first part of his career as an operator at CH Robinson. He then moved on to implementing software for Movement Logistics before moving back to an operator role at a large fresh produce distributor in the mid-Atlantic. After completing his master’s in information systems, he joined enVista in the small parcel and LTL sourcing practice, focused on carrier strategy, sourcing, and implementation. He then moved into more strategic roles, developing strategies and implementing transportation, global trade, and routing systems for many complex multinational shippers and logistics service providers.

Some of his previous clients include CVS Health, Lasership, C&S Wholesale, M Holland, Whirlpool, Nivel, Lutron, and 1-800-Flowers, CJ Logistics, Lululemon, and Koch Industries. Jesse graduated with a BA in Agri-Business from the University of Maryland, College Park and has a MS in Information Systems from the University of Maryland, University College.

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