How often do people use a travel agent anymore? Websites and apps make it so easy to book flights, hotels, rental cars and even travel packages, that agents have largely gone the way of the dinosaurs.

Travel agents still do exist though — and they can be helpful when a travel itinerary is so complex that you’d rather have someone else do all that legwork for you.

It’s an analogy that applies to parcel rate negotiations. The old-school way of doing things was to hire a consultant, admittedly an expert, who was in a position to negotiate discounts with carriers like FedEx and UPS, in exchange for as much as 40% of the savings over a years-long engagement period.

But just as travel apps have disrupted the agency business, developments in data science and software are changing the relationship between parcel shippers and their carriers — and doing the work at a fraction of the cost of a consultant.

Consultants might still be useful in dealing with complex, multi-carrier situations, but a different kind of complexity — the sheer number of parcels consigned to carriers and the intricacy of parcel rate agreements — makes the application of technology, powered by machine learning and artificial intelligence (AI), a great value proposition for parcel shippers. Algorithms allow a shipping intelligence platform to comb through massive quantities of data to derive better insights than a traditional consultant can provide — and a lot quicker, too. An app can analyze a full dataset on a $150 million shipper inside of three minutes — a consultant could take two weeks to perform the same analysis.

Besides the money and the time that shippers can save using technology instead of consulting, they also derive benefits from an app that never stops working.

Consultants often demand a share of a shipper’s savings over a three-year period, but their work is done in 90 – 120 days. Companies that engage these consultants often experience payment fatigue — they fail to see the value in writing checks once the consultant is gone. They won’t renew the engagement for that reason — retention rates in the industry are horrendous — and go into the next round of rate negotiations by themselves. The result is that their rates will rise, motivating the shipper to re-engage a consultant — and the cycle starts all over again.

Software, on the other hand, does its job on day one, but it doesn’t stop there. Unlike consultants, it doesn’t leave users to their own devices, but constantly looks for more opportunities based on new data.

A modern shipping intelligence platform crunches shipper data, and as it compiles more and more data, it is able to provide more valuable insights through the use of machine learning and AI. The more data that is made available to the platform, the better the insights it provides the user. Six months down the road, it may present the shipper with new actionable insights — after a consultant is long gone.

Parcel shipping, in particular, lends itself to this kind of analysis because of the sheer volume of the data involved. It’s a lot more complex than, say, less-than-truckload (LTL) shipping.

This complexity is expressed not only by the large number of shipments, but also in the agreements between shippers and carriers. The terms of a FedEx or UPS agreement can take up a document 30 pages long. In these agreements, the carriers may offer different discounts for different services in different zones. The discounts may expire over time and they may not be applicable at all if the shipper doesn’t meet specified volume thresholds.

FedEx and UPS, which control 94% of the parcel market in the United States outside of Amazon and the Postal Service, may offer different base rates to the same shipper. So, for example, a 50% discount from FedEx may not be the same as a 50% discount from UPS. It’s difficult to compare apples to apples and to derive meaning from a comparison of agreement documents.

A shipping intelligence platform allows users to simply drop a PDF into the app so that it can digest agreement data. Once the documents are analyzed, shippers can compare agreements side by side. By analyzing the agreements, the platform can prepare a package-level analysis for each agreement, pinpointing the exact savings each agreement would provide to the shipper, based on its individual dataset, right down to the penny. For any sizeable shipper, it would be next to impossible to perform such an analysis without the latest technology.

Armed with a better understanding of agreement documents, shippers are better able to negotiate with carriers. That’s another element of the disruption taking place in the industry — shippers are dealing directly with carriers with the aid of technology, instead of hiring a consultant to run the bidding process for them.

The new technology is also instrumental in recovering credits on behalf of shippers. FedEx and UPS both credit shippers for billing errors and late deliveries, but it doesn't happen automatically. The shipper must proactively find errors and late packages, and then approach the carriers through their websites or by calling them on the phone to get refunds. It’s not easy to find that information by combing through data manually, and the return on investment for paying someone to do that job usually isn’t there.

But a shipping intelligence platform performs this task automatically. Its powerful data capabilities allow the software to uncover data on billing errors and late shipments and to communicate with the carriers directly to get refunds.

As data science, machine learning, and AI progress, parcel rate software will only get more powerful. It will be able to integrate shipper data with general economic data and other macro-level datasets, such as weather, to produce better insights and identify performance issues.

Parcel shipping consultants had better take notice. If they are to survive, they will need to work on revising their value propositions by focusing on the most complex shipper/carrier scenarios. For single or dual-source shippers, technology is delivering the same value and more, in a lot less time and at a fraction of the cost.