Adrian Murillo – Chief Scientist
Before joining B Team, I spent the last 19 years as a scientist for a major pharmaceutical and diagnostic company, researching and developing pathology tools used to create detection methods and novel therapies for many types of cancers. Unfortunately, the typical methodologies for gathering and classifying this information remain subjective and the resulting output is placed into broad categories rather than existing as quantitative data points. This subjective categorization makes it harder for tissue diagnostic companies to develop clinical assays for pathologists to prescribe therapies.
When I was approached with the idea of B Team, I realized that construction has the opposite problem. There are no categorical data groupings; everything is directly measurable, thus removing any subjectivity or variability from data analysis. Knowing this, I was disappointed to learn that, while data analytics has led to gains across nearly every sector, much of the construction industry has remained unchanged for decades and productivity has actually gone down. There is a vast wealth of untapped data waiting to be collected, analyzed, and applied to the advancement of all aspects of construction. B Team wants to build a bridge to take the industry from the industrial age to the digital age by utilizing the continuous data that has always existed but was never measured, analyzed, and modeled. Let’s examine how this is possible.
In cancer tissue diagnostics, novel technologies have been developed to minimize ambiguity in analysis. However, their cost prohibits adoption on a scale that would prove their clinical validity. In construction there is no need to invent technologies to measure the wealth of data that currently exists. Data generated on jobsites can be connected with individuals and subcontractors to make informed decisions on work quality and output. At B Team, our real-time job analysis algorithm tracks progress and cost against schedule and budget. This not only proactively identifies problems before they arise, but more importantly, before the opportunity to correct them has passed. Knowing a problem is coming is valuable to mitigate damages, knowing in time to fix it yields the power to chart a course to success.
Despite the subjective practice of categorizing tumors and protein expression into buckets, pathologists and researchers are at least informed by some data when developing diagnoses and treatment options. Conversely, construction leaves vast amounts of data uncollected, relying instead on a culture of “I think” and “I feel” instead of “I know”. For example, go ask 2 or more superintendents how many jobs they have done that had drywall on them. Then ask them what the production rate is for 1 drywall installer. Despite the virtually ubiquitous presence of drywall across construction, you will not receive the same answer twice. This aversion to data collection dooms many projects to cost and time overruns before the first spade breaks the dirt. Our predictive algorithms give us the knowledge to make data-driven decisions on schedule and profitability in the preconstruction phase; before contracts are signed and the associated risks and expectations are finalized.
In pathology, the emerging trend is to scan stained tissue slides into databases where they undergo A.I. image analysis and pattern recognition. This results in greater collaboration and faster, more accurate diagnoses. In much the same way that these new methodologies empower medical professionals to make more informed decisions, we are applying similar thinking here by teaching our employees the science behind our algorithms and how to use them effectively. Imagine the outcome when entire project teams understand these algorithms and can use them independently from the estimating room to the job trailer. That’s B Team.
Histology and Pathology are obviously sciences; questioning processes and improving methodologies are intrinsic to their nature. And yet, even with this scientific mindset, there remains room for significant advances. Construction has long been the opposite, reluctant to question “how it’s always been done” and reliant on heuristic decision making. It doesn’t have to be this way. For 19 years I had a front row seat as innovations in data collection and sharing gave researchers and clinicians better and better tools to treat cancer. I look forward to helping B Team lead a similar transformation in this industry!
