Machine learning is an exciting concept in the construction industry. To us at Enstoa, where we specialize in finding meaning in construction project data, machine learning helps improve processes and project outcomes.
By applying machine learning techniques to the project record, we can improve our understanding of performance trends, identify areas of opportunity for continuous improvement initiatives, and make better decisions faster by leveraging our data as a decision support system.
Did you know you could authorize a $20 million USD capital project without requesting any additional budget?
It’s a compelling way to kick off meetings with clients who have large capital construction programs. Surprisingly, we start conversations like that more often than you’d think. How can we make many millions of dollars materialize? A common problem with large organizations is they have millions of dollars tied up in latent capital. We locate it, liberate it, and let it be spent.
Just because you have data doesn’t mean you’re using it as a strategic asset.
That’s an important distinction. We observe some organizations believe that just because they have enterprise applications, codified processes, and collect heaps of data that they’re exercising all of their enterprise assets to achieve their strategic goals. And yet they aren’t.
Let’s explore why.
