For many years, shipping consultants have largely operated under a gain share business model in which they received a percentage of the savings they uncover. This percentage, the consultant’s pay if you will, stemmed from a variety of sources, among them savings generated by the more favorable shipping contracts with carriers they helped negotiate and secure, changes to shipping protocols and processes that delivered savings, and audits of clients’ shipping operations – an exercise that almost always uncovered savings of 1-3% of total shipping spend. The consulting firm would then typically receive a percentage of these total savings over an agreed time period, often in perpetuity.
For many years and in keeping with the industry norm, Reveel used this very business model; however, two years ago we set off to explore what we believed would be a far more advantageous approach for our customers. It was a process that would require us to transform the company from a pure business consultancy into a technology company and shipping data analytics firm – one able to arm customers with the actionable insights they need to make money-saving decisions in real-time.
It goes without saying that this decision was not taken lightly. Being the first to tackle shipping data was a complex and intimidating endeavor. It was also one we knew we were not qualified to take on ourselves. Our expertise in the shipping industry honed through many years of experience in the field would only take us so far. To that end we acquired a software development firm and assembled a world class team of data scientists. The result was Reveel’s Shipping Intelligence Platform™. Because of it, today shippers at many of the world’s best- known companies save money on millions of shipments made each day.
While many of our customers still request and require direct support from our consultants to ensure that their shipping operations continue to deliver the performance and margins they want, we learned a lot over the past two years in our transformation into a shipping data analytics firm. Some of these lessons undoubtedly reflect our own experience at Reveel, but others are equally relevant to all shippers. Some of those lessons and validations include:
- True shipping intelligence was long overdue; now it is crucial: Business intelligence tools that enable organizations to collect, organize and visualize vast amounts of data in order to make informed decisions are ubiquitous across industries. The shipping sector was a significant exception for several reasons. First, there is no standard data format for the many criteria that must be tracked. This presented Reveel with a very steep first hill to climb – which we did.
- Secondly, most companies historically were not focused on efforts to optimize their shipping. Other business imperatives reigned supreme and shipping spend was rarely an issue of c-suite concern outside of a smaller subset where shipping was inherently a core function of the business. Several factors, including the dramatic increase in e-commerce that occurred because of the pandemic, and the radical shipping cost increases imposed by carriers like FedEx and UPS that accompanied it, changed everything. Today, whether or not you effectively manage your shipping operation is no longer a question of a few additional points of profit. It’s often the difference between a transaction being profitable or a loss.
- Every shipper needs data science: At its core, shipping involves a complex web of variables governing numerous criteria, from the weight and size of the parcel, to the zone it must be shipped to, where it originates and of course how fast it must get to its destination. Given that any company can ship many thousands of parcels that by their very nature can differ on every criteria except size and start point, there are few cookie cutter solutions.
- This is particularly true in e-commerce, where parcels rarely contain the same SKUs. And even if you are a manufacturer shipping a product that is always the same size and weight, those same parcels are going to different locations. What all of this means is that shipping is simply too complex to decipher without data science. Yes, there are still many things we can do to help manually – for example reviewing your shipping contracts and analyzing your shipping spend to look for specific discounts or areas where you should negotiate – but for shippers to really optimize their operations they must have access to their shipping data and the tools to understand it.
Perhaps most importantly, we have learned – or perhaps more accurately witnessed – the transformation of the shipping profession itself. Our mission has always been, and continues to be, to level the playing field and bring pricing transparency to the parcel shipping industry. There is a ground swell of clients that desire to be independent from consultants who now have the BI tools they need to be able to actively manage their shipping operations. For those that still want our assistance, we will be happy to continue as your trusted consultants, while also providing the industry’s first analytics and decision support tools.
Yes, our industry will always be one of warehouses, distribution centers, diesel and jet fuel. Those who are adept at managing teams and keeping complex operations up and running will always be in demand. But now they will increasingly need to be data experts in their own right – professionals who understand and who can act on the actionable insights hidden in their shipping data.
Because of this many undoubtedly will ask a new question: With data at my fingertips, can I finally break away from gain share? At Reveel, we believe the answer is unequivocally yes.
The Reveel App uses AI and machine learning to provide an unparalleled look into what’s impacting your bottom line. Through invoice audits, peer benchmarking, and rate modeling/simulations, you can see the health of your operation and assess pricing changes from parcel carriers like FedEx and UPS. Sign up for a free Reveel account today to see how you can leverage automation to synthesize your data, ship more for less, and reduce the time needed to identify issues and action items.