Case Study : Major Transportation Company Saves Big with Predictive

TRANSPORTATION CO. SAVES BIG WITH PREDICTIVE DATA
STAND 8 helps transportation company streamline maintenance and operations by predicting which truck parts will fail.
CASE STUDY/
Topics:  
By  Rich Lucas  June 03, 2022
CHALLENGE/

STAND8 Managed Services came to the aid of a major transportation company with a unique problem.

The client, a transportation and trucking conglomerate, acquired dozens of commercial-grade large truck brands. The business was booming, but a persistent issue arose that was hurting their bottom line.

Before we dive into the problem it helps to understand the business. The client basically operates like any major car brand. Dealers sell trucks and buses. Those vehicles are used by other companies to run their businesses and make a profit, and when those vehicles need service (like all cars need service for maintenance or repairs) the trucks are brought into a service center.

With so many different makes and models of trucks in operation, It was difficult for their service centers to keep needed parts in stock. There were more parts than there was space to store them. We're talking about thousands if not hundreds of thousands of parts. There is simply not enough storage space to keep every part on hand.

But here's the real problem, if a part is not in stock, the commercial truck remains out of service. If trucks are out of service, owners are losing money, an average of $4k/day, and their angst is directed at the truck manufacturer.

STAND 8 Data Services teamed up with the trucking titan to devise and deploy a solution that was the next best thing to a crystal ball.

SOLUTION/

One of the great things about the trucking industry is the data. These trucks are not your mom's station wagon. They travel millions of miles, hauling thousands of pounds, and they're tracked the whole way. The client also kept meticulous service records for each truck. That means data points.

Using this trove of data, our team constructed life cycle graphs for each part used on each commercial truck brand. From there we developed a model to predict part failure. We applied the model to ALL client-branded commercial trucks currently operating. What does this mean?

The client is now able to predict the average failure time for each part and thus better stock part inventory to meet projected demand.

$4k
Daily lost revenue for downtime
6
Days lost if a part is not stocked
1
Day repair if part is stocked
TRANSFORMATION/

Needless to say, this solution exceeded expectations.

Previously, the client was forced to make little better than a guess regarding part inventory. Those results? Excessive wait times for service and angry customers losing revenue.

With STAND 8's predictive model, the client could anticipate demand and order parts before they were needed. This meant less time in the shop, more time on the road, and more profit for customers who could expand and buy, you guessed it, more trucks.

Reach out to our Data Services team to learn more about this solution and how we can help your business.

author photo
Rich Lucas
Director, Data Science and Advanced Analytics
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