How to capture accurate data from equipment—it’s one of the biggest fundamental problems that construction companies can face today. Simply collecting equipment data such as meter readings, fuel consumption and more can be an arduous task, let alone effectively processing that data to make more informed equipment management decisions.
Dexter + Chaney Marketing Director, Wayne Newitts, breaks down these challenges and the best practice approaches leading companies are taking to improve their construction equipment management practices in a special blog for Construction Business Owner magazine. Here is a brief look at some of the areas he writes about:
Heavy equipment can comprise a significant portion of a project’s budget as well as a company’s financial footprint. Even small inaccuracies in cost tracking can result in large cost overruns.
If repair, maintenance, ownership costs and accurate meter readings are diligently recorded for each piece of equipment, a company can actually predict, rather than guess, their equipment lifecycles and optimal returns on investments.
There is a key difference between owning and operating costs for construction equipment. Owning costs are fixed annually and are mostly established when a machine is purchased. They are based on factors including depreciation, interest, licenses, insurance and taxes. These are the costs of owning the equipment that one occurs regardless of if or how one uses it. Operating costs, on the other hand, go up over time due to factors like an increase usage of fuel and oil, to wearable part replacement, to unexpected repairs.
There is a so-called sweet spot that occurs when the increasing cost of operations overtakes the effect of the decreasing cost of ownership for a machine.
Better equipment data collection and analysis is key to knowing the real total costs of operation of equipment over time.
There are leading edge software applications specifically designed for equipment management that simplify and even automate the collection of equipment data, analyzing it, trending and reporting on it. These solutions make it easier to see the full life cycle of equipment and decide when a piece of machinery can be repaired or when it’s at the end of its life.