If you've followed any of my writings in the past, you'll know that I've made numerous arguments against the “time and materials, bill by the hour” business model. It’s the predominant business model in the environmental engineering and consulting industry. If you know me, it’s no surprise that once again, I'm going to make a similar argument. This time I'm going to be more specific that it's not just a bad business model, it could be the end of your company.
With new artificial intelligence (AI) products like Microsoft’s” ChatGPT” and AI embedded Bing, Google’s “Bard”, Amazon’s new “Bedrock” AI, and Twitters recent entry into the AI market with “X.AI”, the ability to get things done quicker will be widespread. Companies that are first to utilize these and other new technologies will win market share and drive the slow adopters out of business.
Even the most hardened skeptics and detractors of AI will agree that in the future it’s going to be harder to compete against this type of automation using the “manual” methods that most companies use today.
Here is the problem though, even with this knowledge most companies will still resist the transition to these innovative technologies up until the very last moment, and it might be a moment too late for many of them. I have to admit though, in the late adopters’ defense, and by no fault of their own, it might make financial sense to wait until the very last moment. You see a lot of state programs (Michigan’s MUSTA program for one) and many corporations currently pay for environmental services based on the “time and materials, bill by the hour” method. It's the way they have always done it and as everyone knows people tend to resist change until forced into it. So, for these late adopters, it's simple logic, if they use these technologies and get their work done faster, it means less revenue for them. When technology is developed that gets a job done quicker and faster, but it means that the user of the technology be financially punished, less users will adopt the technology.
I'll give you an example and it has nothing to do with AI or any of the services or our technology my company offers. There is a site investigation technology commonly called “high resolution site characterization” or HRSC for short. In summary what this technology entails is a probe that has a multitude of sensors on it that can detect everything from electrical resistivity of a soil, porosity, hydrocarbon impact, color, and numerous other parameters. The data is collected both horizontally and vertically and upon completion of each borehole the ability to view a 3D model of the resulting data allows the user to instantly see soil types, soil layering depths, presence or absence of contamination, relative concentrations, and water tables, etc… This technology has instantaneous feedback and, once on site using this tool, the extent of contamination can typically be completely defined within 5 to 10 days of initiation.
HRSC technology is not cheap when looked at on its own from a daily rate perspective. But when compared to the traditional method of determining the extent of contamination using the labor intensive and time intensive method of installing monitoring wells, doing the traditional soil boring, installing a monitoring well, and then sampling the well a few days later, HRSC ends up being significantly cheaper.
The one-by-one method of traditional soil boring using the split spoon and geologist evaluating these soil types with varying levels of expertise and using a photo ionization detector (PID) to determine relative contaminant concentrations and then deciding whether or not to install a monitoring well at that boring location, can often take months and sometimes well over a year and beyond. Not to mention the costs of a single monitoring well is not cheap, and the placement of these wells are for the most part not optimal in terms of placement within the contaminated area. I can’t tell you how many times I've seen where an engineering firm is chasing what they thought was the contaminated plume in the wrong direction. Many of the wells installed were wasted and because now they are there, they need to be sampled repeatedly before they can be reliably removed from the sampling protocol.
Even with what seems to be a significant advantage for HRSC in both overall cost and data resolution and fidelity, the majority of contaminant delineation projects still use the soil boring and monitoring well placement method. Granted monitoring wells are going to be needed for the ongoing monitoring of a particular site, however when up to half of the monitoring walls at a typical project are poorly placed and become obsolete almost immediately, it seems obvious to me that it's not just slow, it's wasteful.
So why is the soil boring/well installation method the predominant method used to this day? The only answer I can come up with is that it puts more cash in the pocket of the engineering firm over HRSC. Now don't get me wrong, this is not a front of mind conscious decision, but it's also not a decision made without financial bias to the benefit of the company/individual making the decision. When technology selection and financial considerations conflict with one another, the financial benefit to the entity deciding, always seems to win.
So, what's the answer, how do you get people to select efficient technology over inefficient methods that benefit financially? The answer lies in the business model method of payment. When being compensating by time, it's natural that it will take longer to get the job done. When compensating by a defined scope of work with a lump sum price for that scope of work, efficiency aided by technology, is financially rewarded. I've used this analogy in the past because I think it's a good one. If a roofer placing shingles on a roof was getting paid by the hour, the nail gun technology would have never been invented. Roofers always get paid a lump sum for a given roofing project, making roofing using a nail gun more profitable.
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