Building an Asset Value Engine

Working in the car sharing industry means you own something like a car and let others use it for a while before taking it back. But how do you keep track of this whole process?

Client
Automotive Subscription Service
Services
Individualized Data Model
Year
2023
Location
Austria

Fun fact & Intro

Let's get Cyber-Physical. We can't teleport like in Star Trek because it's not the year 2152. So, we need to use things like vehicles to travel. When a business deals with these vehicles, it's important to know how valuable they are, how they're doing, and their condition. This is super important, especially in today's world where we often share resources and need to know what's happening with them right away.

The challenge

Working in the sharing industry means you own something like a car and let others use it for a while before taking it back. But how do you keep track of this whole process? It starts with adding the asset to your records, understanding how it's used, factoring in depreciation (how its value decreases), and eventually removing it from your records.

Your company already has lots of important information internally, likely spread across different departments. However, to stay connected to the asset while it's being used by others, you need more details about its condition and usage out there in the field.

Project Image

The solution

To make things easier, bring all your important company data together in one place. Then, add more details from the asset while it's being used and combine that with helpful info from outside.

Let's break down the kinds of data you're dealing with:

Stuff Inside Your Company:

  • What you paid for the asset, how much it's worth in your records, its brand, model, version, all the costs of having it, money you make from it, and the agreement details.

Information from the Asset Itself (Using Sensors and Telematic Units)

  • Where it is on the map, how it's being driven, how many miles it's covered, how good the battery is, if it needs maintenance soon, and how it's typically used.

External Facts:

  • What the roads are like, how traffic is, what the weather's doing, and where charging stations are.

Once all this data is gathered in one place, the fun begins. You can dig into how your whole fleet is doing and double-check that everything's going smoothly. This isn't just interesting — it also helps with:

  • Figuring out how much the asset is worth over time, which helps with money and accounting.
  • Choosing the right insurance based on how the vehicle's doing and how it's driven.
  • Finding chances to offer more services to customers who've used the asset a lot.

The result

We're just getting started. All that data we talked about? It's the foundation for using clever algorithms that learn on their own. They don't just look at what's happening now; they predict what's coming, a bit like how Gene Roddenberry imagined the future.

These smart algorithms can answer questions like:

  • What will my asset be worth in six months?
  • How much can I sell it for in the future when it's not brand new anymore?
  • We've got a special plan to predict this, called "Residual Value Prediction."
  • They can even suggest what you should do right now with the asset or the contract.
  • Keep it as it is, change the price, or take it off the fleet.

It's like having a crystal ball for your business assets.

Summary

When you tap into cyber-physical data, you're never far from knowing how your assets in the field are doing. We honed in on a particular example earlier, but we've used this same approach for other things too, like High-Temperature-Fuel-Cells. They send back all sorts of info about their well-being, temperatures and cell stack activities, and anything else that helps fine-tune R&D to making sure production is top-notch.

There's a vast realm of possibilities waiting to be discovered. If you're managing a fleet of anything, steer your focus into uncharted data territories. Explore where no one has gone before.

And this is how it looks

The beauty of data revealed:

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