Updated: Jul 23, 2020
Author: Nathan Chang
A little introduction to Quantico The term data science has entered mass adoption world-wide and every company in every industry is clamoring to leverage the practice strategically. Unfortunately or fortunately, depending on your perspective, Quantico Energy Solutions happens to be in the E&P space and this industry iterates rather slowly. It’s actually an incredibly technical space dominated by science and engineering, but when it comes to digital technology the upswing can feel slow in comparison to adjacent verticals. Nonetheless Quantico is striving to become a leader in the application of subsurface AI in E&P and we’re looking ahead to transitioning data science practice and process into applications and platforms.
How did we decide we need a focus on data science? From its founding Quantico decided to apply machine learning to the problem statement of predicting sonic and density logs without direct measurement tools downhole. While the initial success Quantico achieved in reaching that goal did indeed apply machine learning as a consulting service (MLaaS, or AIaaS), the data science needed to evolve before it could become a global, enterprise-grade, commercial software application. The same could be said about QEarth - our Earth modeling product. While the initial design is sound, it is a data science process and not yet democratized enough to translate into enterprise software . How were we, an AI company, going to pivot into delivering data science driven software without a greater focus on automation and user experience?
What attributes did we prioritize and WHY? We started to build a people strategy! How are we going to attract the right talent? What did the right talent look like? How does a small AI company, looking to market data science tools to the G&G, D&C, and reservoir engineering groups of the world’s largest oil companies, how could we not be made up of the same domain experts? Questions like the on
e above, can hold great companies hostage behind prison bars of mediocrity and we’re anything but . We started thinking about what we wanted. We needed agility, adaptability, passion, curiosity, intellect, energy, commitment, dedication, but most of all, we needed trust. When we decided to go recruiting, we found an incredible amount of interest, which was very encouraging for our leadership. We focused on four key traits:
Trust and honesty
There is one final trait that we felt needed to be overarching across the team. DIVERSITY
What did we end up with? We hired across the age ranges. From 25 through 63 years of age. We hired a signal processing specialist from Halliburton with over 40 patents and a recent grad from the insurance industry. Furthermore, the passions of this group span far and wide. One resource has decided to lead all project management via SCRUM/Agile, and overall R&D. Another has decided to lead our entire digital marketing program, and another through decades of experience, has introduced our team to data science approaches to enhance process automation . It’s truly a technical team like no other and there isn't a problem they couldn’t solve - I would pit them against any team from any vertical and any company. Data science has always been the heart of our company, but great software delivery is becoming our second core capability.
How do we retain and continue to build in a competitive landscape? Now comes the real work. Having built a team that has compassion for each other, mutually respects the diversity of capability and passion each person brings, looks to support each other in the eleventh hour and loves our weekly Friday happy hours at Cobble and Spoke - how do we continuously produce gravity to hold this group together? How do we keep their gaze fixed firmly on the problems of our industry and clients? The answer is engineered autonomy. We will not confine them to problems that don’t draw out their creativity and curiosity. As a management philosophy we let the group ebb and flow between R&D, marketing, and production projects, but they all have to contribute to some extent in each area. While it’s impossible for each of us to constantly have the work that drives our passion every day of every year, we do afford our team the freedom to take on assignments that either interest them or allow them to be creative in how they approach them. Each member of the team enjoys working with all the others and collaboration is sparked daily by mutual trust and respect. Finally, the team knows how capable they are together and so far (fingers crossed) they continue to rally as a team to meet every challenge.