The November 19 edition of The Wall Street Journal ran a front-page story about how insurance companies use online purchasing data to identify individuals to whom they can sell life insurance and make a better than average return. The next time you buy a $2,000 elliptical training machine, your friendly insurance sales representative may just knock on your door and try to sell you a life insurance policy. Your purchase indicates that you are taking steps to improve your health and that you are, therefore, likely to be a better than average insurance risk.
The article explains in detail how data from online purchases are collected and analyzed to provide insurance companies with information that is cheaper, more readily available, and within limits, just as useful as the information that they obtain from medical examinations.
What does online purchasing and insurance salesmen have to do with equipment? Let’s imagine a world where an online parts-procurement system records data on the parts purchased throughout the life of a machine and where telematics provides data on the age of the machine when the part was replaced. Let’s imagine a world where we bring together these two data sets and write the rules needed to turn parts-purchasing data into information on reliability, economic life and the repair-rebuild-replace decision.
It is not difficult to believe that buying a windscreen indicates that there has been some kind of accident. It is not difficult to believe that buying a second hydraulic pump within 4,000 hours of the last purchase indicates there is something wrong with the way we store and handle our oil. The possibilities are endless. The technologies are available, and I am betting that creative and imaginative companies have made a start.
The first step is to have good, comprehensive parts-procurement data. The insurance companies reported in The Wall Street Journal article bought data showing the purchasing patterns of individuals by name from various sources and, of course, raised a number of privacy issues. Our world is simpler: There are no privacy issues regarding our equipment, and all we need is a good, competent online parts-procurement system that can collect, store and analyze data on the parts we buy. We use different vendors, so the system will have to source parts and supplies from many locations and standardize the data in a common, easily searchable database. We will need smart electronic parts books so that we can pick the necessary parts in a way that identifies the part number as well as the assembly or component for which the part is being purchased. Systems capable of doing this are in daily use, and it is only a matter of time before they become the norm. Suffice to say, if an insurance company can gather data on buying patterns, then an equipment manager should be able to gather data on the parts purchased for the machines in the fleet.
The next data set that needs to be created and maintained relates to machine age or, more accurately, how long and how hard each part or component has worked. Now is the time we can use all the data generated by the sensor and tele-matics systems built into many machines. We know that transmission life is affected by hours worked as well as the number of shifts. Fusing this data with data on buying transmission parts, assemblies and components can give valuable information for repair before failure, rebuild and replace decisions. As with online procurement, the technology is in place and well understood. It is ready for use. Procurement systems tell us what we bought; telematics systems tell us when we bought it in the lifecycle of the machine.
Rules recommend actions
The last two parts of the system relate to the rules that need to be developed to draw inference from the data and recommend the action that needs to be taken. Lots of smart people work on this sort of thing, and there is ample knowledge and experience available. It is not rocket science to use data about lights, glass and body panels to provide information on abuse and safety violations, but it will take some time to understand the parts purchasing patterns indicative of more complex situations. But it can be done, and there is no doubt we could further the state of the art by exploring this frontier.
Online parts purchasing and e-commerce have proven their potential to reduce parts costs, streamline business practices, and improve repair efficiency. The insurance industry has shown how purchasing data generated during online transactions can be used in many creative and innovative ways. This undoubtedly holds true for equipment management where we constantly struggle to keep accurate records and equipment histories. Consider the following three possibilities:
1. Warranty administration. Surely our parts-procurement and accounts payable system can be made smart enough to tell us when we replace parts, assemblies or components that are under warranty.
2. Component life control. The parts-procurement system should be able to record the time when major components are replaced and provide the information needed to manage component life, reduce downtime, and lower cost.
3. Machine history. The current process is to record what we have done and go to parts invoices to confirm the accuracy of our records. Why not do it the other way around and let the procurement system automatically produce the records that show when cylinders, pumps, batteries and undercarriages were last replaced.
E-commerce and online procurement are being embraced by leading-edge companies. They are here to stay; the benefits are proven. Mining the data collected when using these methodologies has the potential to dramatically change the way we keep records, analyze trends, and manage our fleets. It is time we let the parts tell the story.