We’re a global independent advisory firm. We’ve got about 5,000 employees globally. Just over $3 billion market cap. And we’re really providing services across a wide spectrum.
Our construction solutions practice has its roots in claims disputes. We decided to take that expertise and apply it to the front end to really prevent people from getting to that position in the first place.
I’m the global leader for enterprise project portfolio management. My team provides services around, you know, enhancing the way that our clients deliver their critical assets. And that’s really doing things like capability maturity assessments, process improvement, selecting and implementing technology solutions, doing analytics and data intelligence services.
We’re still seeing the large projects go over budget consistently. We’re still seeing them go over schedule consistently. We’re still seeing quality issues. We’re still seeing issues with projects, not meeting their stated objectives.
Dell did a study where they looked at data growth from 2016 to 2018 and as part of that, they realized, data had grown 569% in that period. And it’s going to continue to grow at a rate that and more. And so, you know, really, I think the issues that we’re dealing with is how do we get our arms around that data? We have more data than we’ve ever had yet. We’re doing projects worse now. Why is that?
Most of our clients are doing kind of the backward looking reporting and starting to try to analyze why. Why did this happen? Why did we go over? Why did we run behind? But that’s all they’re doing. And you know, when I first joined the project controls world, I had a mentor of mine tell me, you know, it’s your job not to tell them the license plate of the bus that hit them, but to tell them that the bus is coming. And you know, that’s really the predictive, right? That’s the outcome focus view of data. And today, still after all these years, we’re not doing that effectively and consistently across the industry. And that’s really where we need to change that.
The first step is really understanding your data. And so, you know, a lot of times people look at data and analytics and they think garbage in, garbage out. We don’t even know if we can get consistent data. And so they refuse to start or they say, ‘we’re not going to see value.’ But the reality is exactly the opposite.
Starting to answer one question, then you start asking more questions and then you start getting more your arms more around that data. And just don’t go to sophisticated out of the gate. It’s important to see it as a journey, but one that’s going to add incremental value every time you deploy a new model or a new analytic.
People are expecting to get results quickly, and so we’re very big on value quickly, get new data insights, use those new data insights to question the way you’re working, to improve the way you’re doing business, to find out what data you need to collect that you’re not collecting.
It starts to give people, the power of unlocking their data. The power of analytics is you’re moving that into a data warehouse and you’re making it self-service. And now these analyses don’t depend on experts to go dig into and find insights. The modeling still does, but you can take that augmented data, the structured data, unstructured data and put that in the hands of your best assets, your people.
You want a platform that’s extensible so that when you do come up with the more complex analytics down the line, you’re able to augment the standard capabilities of the tool. And then ultimately you need a really strong visualization platform. Something that’s going to allow people to slice and dice really easily, make it really intuitive for them to be able to get the visualizations that they need without making it too complicated.
Projects are having a significant impact on shareholder value. You’re seeing stock prices go up and go down based on great performing projects or based on a project going six months delayed. And so because of that, the imperative is to drive shareholder value by managing that more effectively. When you start looking at your structure data, seeing your basic metrics like a CPI for example, right next to a new KPI that you’ve been able to develop off your dataset that gives you new insights, allows you to predict project outcomes, and the market loves predictability.
If we can shorten project durations, if we can shorten the amount of resources that we need, if we can better spend our resources more efficiently, we should see those benefits. But it also comes back to predictability, accuracy and consistency, better process integration across the different disciplines on the project, and ultimately better insights to support decision makers. No, we firmly believe at FTI that no decision maker is getting information, ignoring it to make a bad decision. So if we gave them good information, we think they’re going to do their very best to go make a corrective action or take a corrective action that’s going to have an impact.