03 Nov Construction Bids: 3 Ways Data Can Help You Predict the Future
Hindsight is usually 20/20. Like most specialty contractors, if you think about all the construction jobs you’ve bid and won over the last several years, you probably have a “gut feel” on the ones you should have passed on or the ones you might have bid differently. But could you accurately pinpoint the best GCs, most profitable project types, or the proper estimators to put on every job? Would you be able to forecast which jobs would produce the best outcomes, including minimizing project execution risk, certainty of margin, and optimized pricing? Could you predict which ones offered the best opportunity for winning and which ones to pass on?
The answer to these questions would be a confident “yes” if you had a proven process to capture this type of data consistently and use predictive analytics to allow you to make more informed decisions when looking at new jobs to bid.
Before you stop reading, let me say this, data is not a replacement for experience, intuition, or having talented people in your company. The fact is the construction industry will continue to get more competitive. Our experienced labor force is starting to retire, and construction project volume continues to grow. Because of that, the trade contractor of the future MUST begin using data to augment decisions that previously made them successful.
Here are the three key areas you want to focus on for using this data and why it matters:
1. Use Predictive Data to Reduce Project Execution Risk
There is only one way to remove all the risks from your business: you have to have no employees or clients. (Even then, there might still be some debate.) What are the drivers of risk in your projects? The list is too long and is probably changing even as you are reading this. Here is where data comes in.
The things we can have the most control over to minimize that risk are:
1) Who we work with. Architects. GCs. Superintendents. Other trades.
2) Project types. Are we better at building schools or stadiums? Do we have better success rates on projects over $1M or under $1M?
3) Who are our best estimators and best project teams to execute?
These are known elements we can control. Project by project, it changes. Sure. BUT over a long enough period, trends begin to develop. If you consistently capture this type of data on projects and start to look for these trends, you might be surprised at how obvious the outcomes are. Good, bad, and ugly.
2. Use Predictive Data to Increase Margin Certainty
My job as the CEO of RhinoDox is to predict the future and execute on it. I ask the same thing of everyone in our company, whether they are in sales, marketing, development, or finance. The importance of this is evident when we underperform and ask ourselves why it didn’t go as we planned. While more positive, outperforming versus how we predicted has consequences as well. It’s mainly in the missed opportunities to use more resources for a positive outcome. It can also strain capacity when we have too many leads or close too many deals.
The same thing holds true when it comes to predicting and executing what projects you take on. Tracking performance on projects you win (especially tracking margin) is a window into future performance.
If you take a specific project type of a certain size with a certain GC at 10%, how confident are you that it will land at 10%? Yes, many things can affect it:
- Material cost
- Change orders
BUT again, over time, there are patterns.
To be clear, we aren’t talking about margin certainty to win at the highest margin. There are reasons projects are taken at lower margins:
- Keep your workforce busy
- Additional phases of a project
- Maybe you know a project will have a ton of juicy change orders
At the end of the day, the issue isn’t getting the highest margins; it’s about delivering at your predicted margins.
3. Use Predictive Data to Optimize Pricing
Let’s tie this together when it comes to pricing. A client told me that in one of their markets, they have a 20% win ratio and deliver those projects at an average margin of 23%. “That’s great,” I told him. “Not great,” he said. He explained that he would have rather priced jobs higher, won less, and done less work, AND make more money on higher margins. Less work obviously lowers execution risk because fewer things could have gone wrong, and, well, who doesn’t want to make more money?
When I asked this client how he knew about these numbers, he explained that once a year he spends a couple weeks crunching spreadsheets. He’s pulling it all from several different sources not readily available at his fingertips. So when it’s all together, that information is accurate but only for a single moment in time. What he’s looking for is to have that visibility in real-time on every job he decides to bid on.
One more thing
“Those who do not learn from history are doomed to repeat it.”
There is an abundance of data in your company that you can use right now. It’s most likely spread out, not easily accessible, and therefore not leveraged. Think about your company’s future and what driving a consistent bid process means. Leverage your past success and institutionalize those successes to create the data set that can be used to help you build a better future.