With an excess of data, disparate systems, and multiple service lines, transportation and logistics organizations can lag behind other industries when it comes to innovation. Pilot use cases that focus on speed to market and team efficiencies ensure you’ll put your dollars behind only the most impactful changes to your business.
In our transportation and logistics data innovation lab service, we’ll set up an embedded team within your organization to vet, prototype, and scale solutions for innovation. We’ll leverage agile principles, and through a teach-and-do model, you’ll leave our engagement with a self-sufficient internal team to continue adding value.
We’ll stand up a cross-functional team, either embedded or fully independent, within your organization to vet and execute ideas for innovating with your data. With our innovation frameworks, you’ll get to data ROI faster.
We’ll start by taking a look at use cases for driving logistics innovation through a series of discovery workshops. Whether you already have an idea in mind, or need help uncovering an opportunity, our strategy team can help you identify and prioritize an innovation initiative. Whether it's adding predictive analytics into your TMS, surfacing optimized load recommendations, improving your financial dashboards, or anything else — we'll help your team sort and prioritize the right projects to make an impact.
Depending on the identified opportunity, we will then map out a strategy for testing. Our teams use agile frameworks to build a small experiment to test our theory, be it a prototype, pilot AI model, or something else. Once we prove out the solution, we’ll help you “sell” the idea to the rest of your organization.
Once we’ve proven out the prototype, we’ll build out the first iteration of the solution. Working closely with stakeholders across the organization, we have proven ways of gaining buy-in along our build process, so change management isn’t a painful afterthought.
An innovation lab (also known as accelerators, innovation spaces, incubators, or research hubs) is typically a dedicated team, space, and budget focused on accelerating new retail products, understanding market trends, and developing solutions for users — either internally or end consumers. We apply that same concept to data: working with our clients to uncover new ways of leveraging their existing data, prototype concepts for innovative retail software products, and prioritizing data initiatives.
We’ve applied this concept of an innovation lab to data — and tailored it to the T&L industry. Having worked with some of the largest players in that space (J.B. Hunt, ArcBest, Unigroup), we know there is a vast amount of data that can be unlocked for innovation in any logistics organization.
We start every project with a workshop, what we call a Go! Sprint, where we’ll identify a vision for the lab and define the core problems your organization is facing — then put together a proposal for continued engagement.
From there, we typically work as a retained team for innovation labs. We’ll work with you to build a cross-functional team (usually including representatives from operations, tech, and data) to own the innovation lab within the organization. Integrating with the team, we will establish ways of working and frameworks to ideate, vet, and build data innovation solutions to give you a competitive edge and drive change, faster.
It will take us about 3 months to get the lab practice established. From there, we recommend at least a year of our team integrating with yours — so we can tailor the ways of working to your team and transfer any knowledge or skills needed to make sure the lab provides value into the future.
Go beyond warehouse management — improve your warehouse efficiency by delivering actionable insights to managers.
Digitize your route and tracking to gain real-time shipment visibility, address unforeseen issues from loading to unloading, and maximize OTIF.
Better connect shippers to carriers, cutting out manual processes and optimizing truck capacity.
Create your own disruptive technology to advance your operations – from automated load matching to advanced analytics.
Whether your data project involves building a data model, a data visualization, applying machine learning, or data integration, taking an agile approach will get you better results, faster.
RevUnit CEO Michael Paladino recently sat down with Matthew Harding, SVP of Data Science at Transplace, for a dynamic conversation around data integration.
Businesses across all industries can use these systems to create a better experience for customers while also helping employees make more-informed decisions.