Three examples of how this technology solves problems for builders and developers.
As I’ve said in previous columns for this magazine, unless you have no business problems to solve, some version of AI can help your company. AI can help you do any number of things better, including:
- Growing sales leads and closing more deals
- Controlling or reducing operating, indirect and costs of goods sold
- Increasing the amount of product or service you can deliver in a specified period of time
- In general, making better business decisions
All of these require data, and the more accurate and relevant the data, the more likely your decisions will be good ones. What if you could find real-time, accurate data more quickly than ever?
What follows are three examples of how AI can enable that. They are all examples of Generative AI; that is, AI that generates data about things happening now that will impact your current business decisions.
What Market Should We Enter Next?
Let’s look at a modular manufacturer that wants to expand. Is Omaha, Nebraska a more promising market for a new factory than Tulsa, Oklahoma? I’ve included the query and the results, as generated by my colleague Ken Gendrich.
Variables this manufacturer needs to consider include income, demographics, population growth, the number of existing homes, unmet demand for new homes, as well as how many modular factories are already serving the area. They will want to know if there’s a large enough labor pool to meet their hiring needs, and enough of the right type of transportation available. Other questions might include how geography could impact transportation and set work, and whether the ground freezes in winter. Of course, there are also codes and regulations to be considered.
A lot of small businesses don’t investigate new sites at this level of detail, which is part of the reason why so many fail. How many times have we all seen a retail store open in a location where several others have come and gone? The nail salon didn’t make it, the dry cleaner didn’t make it, and now the donut shop has closed. What’s wrong with that location? An accurate answer will require a lot of research and analysis.
It’s painful enough for a small business to fail. But a modular factory is not a small business, and the financial risk can range from catastrophic to complete personal financial ruin.
Cost-Effective Queries
Even if you spend $25K to $250K on sophisticated and powerful AI solutions, if that saves millions of dollars by preventing what would have been a loss, or even a poor-producing location, building design or overall operation, it’s a good investment.
Fortunately, most companies don’t need to spend nearly that much. AI investments are generally small and made in stages. In the case of choosing where to site a factory, you might use the AI to do a preliminary screening of potential sites, then, if it gives you a green light, you go back to it and refine the query for more in-depth analyses of different issues. You’re not investing a lot of money upfront.
The quality of the data you get from an AI platform will depend in large part on the query. A query is a set of instructions, or marching orders, that’s fed into the AI platform. With a good query, the AI platform will do in seconds what humans take days to accomplish, and will do it a lot more accurately. The AI will find and analyze data, and use that to rank the choices. It does all this without emotion.
Note that crafting a good query takes strategic thought, time and expertise. The first iteration likely won’t give you exactly what you need, so you will have to keep tweaking and resubmitting it until it returns the type of results you want.
You can get training for your in-house people to teach them how do this work, but good training can be hard to find and then they will have to keep up with the technology as it evolves. That’s why most companies end up outsourcing the work to a solutions provider.
What Land to Purchase?
Let’s say you’re a developer looking for land. What is the right parcel for the specific community you want to build?
To answer that question, you will want to see current and projected population numbers, along with demographic information. You will need data on the above and below ground infrastructure, including roads and utilities. You will want to know about water rights and water quality. And you will need to understand the applicable city or county permit requirements, zoning regulations and building codes.
When seeking answers from the AI you will use the same process as when choosing a factory location. However, the query will be different.
The AI will score land choices based on the developer’s needs, and those needs will be written into the query. A developer in Alabama may not ask the same exact things from the AI platform that the developer in Oregon does. That’s the beauty of AI — it doesn’t care; it just does what you tell it to do. It delivers data that helps you make accurate decisions but you, the human, still make those decisions.
Developable land can cost millions of dollars, so the ROI here can be uber-extreme. The AI solutions company might have a base minimum charge of, say, $24K a year, but that fee will give you the ability to analyze several parcels and potentially save millions by helping you avoid land that could cause horrible problems.
Who Needs A Builder?
Let’s say you’re a custom builder. Consumers often buy land for a custom home before seeking out a builder, so you could use an AI platform to identify new landowners, then you could contact them proactively, before the competition. This gives you time to sell them on not only your company, but also on the benefits of offsite construction, and to do so before the competition contacts them.
The problem is that, until the deed has been recorded, the fact that there was a sale isn’t publicly available. And once the deed has been recorded, every builder in town could be contacting them. You want to be first.
Some private databases collect data about recent land transactions, and if that data is available in your market an AI service provider might be able to purchase access to the relevant database and write a query that gets the needed information.
Let’s say the AI does this and finds out that Mr. and Mrs. Jones bought land. Now it needs to go hunt for their contact information and return back to you as much as it can find. Even if that is just an email from social media, you are ahead of the game. You can run queries like this every day, and it only takes seconds to a few minutes for an AI platform to return results.
Conclusion
There are many AI platforms to choose from. In fact, a Google search for “AI Platforms for Business” returns at least 30 companies with different capabilities and fee structures. A good service provider can help you sort out which ones to use.
There are also many AI service providers with different fee structures. Some of them, such as Snowflake and Databricks work with general business, while others, such BuilderChain work specifically for builders. Some charge by the computed second, and some charge a basic minimum monthly retainer until you are using several AI solutions. Do some research and make some calls before deciding with whom to work.
As I already mentioned, this column has described a few examples of what’s called Generative AI. In future columns, I’ll get into Predictive AI. That said, I encourage you to reach out to me if you have a question or there is a particular AI topic you want to know more about.
Erik Cofield is a business process and strategy consultant for residential construction companies that provide products and services to offsite, modular, custom and production builders. He has also provided insight to builders of all types and sizes for nearly 30 years. He has 3 books available on Amazon. He may be contacted at [email protected].
