Bold Questions over Big Data: An Interview with Matt Coatney


In this interview, Matt Coatney discusses the importance of asking bold questions, the big misconceptions behind big data, the best way to start your approach to big data, and his vision for a future where technology and big data make the world a better place.

Cameron Philipp-Edmonds: Can you start us off by telling us a little about yourself and your current role at WilmerHale?

Matt Coatney: First, thanks for the opportunity to talk about something I love. I have always been fascinated with advanced technology, especially how we interact with computers, how they learn, and how teams of humans and machines work together to make sense out of a sea of data. It might seem odd to find someone with such a passion for cutting edge technology working with traditional institutions like law firms, but there is a lot of exciting work going on in the industry. Pricing pressures combined with advances in machine learning have led to transformational changes in areas like document review, billing, and pricing. At WilmerHale, I lead a team of IT management consultants responsible for leading significant change initiatives. Our recent focus has been on what Gartner calls the nexus of forces (big data, mobile, cloud, and social), and we have introduced a number of new capabilities to help our lawyers better manage their practice in these challenging and ever-changing times.

Cameron: You recently wrote an article that was featured on LinkedIn which was titled "Thinking big data? Think Bold Questions Instead." What led you to writing this article?

Matt: I have seen firsthand how organizations can rush to implement the latest technology fad without having a sound understanding of how to use it, and what business objectives and questions they need to address. I wanted to sound a warning alarm for those contemplating significant investments in big data to pause, take a deep breath, and understand first how and where they can use it to drive better business decisions.

Cameron: Your article starts off with somewhat of a polarizing analogy. You take the well-known expression of a hammer looking for a nail and claim that big data fits this analogy in some ways. Why is the analogy appropriate?

Matt: In many industries, most of the data they deal with is actually "small data" or "medium data" at best. In those cases, the questions businesses need to answer are often more straightforward, and they can use traditional tools like reports, dashboards, and trend analysis. Using sophisticated tools and techniques like a Hadoop or neural nets is significant overkill. Perhaps a better analogy might be using a bazooka to kill a mosquito.

Cameron: So, how should someone start their approach to big data?

Matt: As I mention in the article, you should start by understanding what key business questions support your most important objectives. These need to go beyond surface level metrics and get to the heart of what really drives your business. You can think of the Five Whys of Six Sigma or the Lean Startup’s focus on actionable metrics like Cohort Analysis. Once you have those "bold questions," you need to look at your systems to determine what data and tools are needed to answer them. At that point, either a large volume of data or the need for sophisticated data mining can guide you to big data tools. The nice thing is that investment is just in time. You do not spend the money on infrastructure until the need arises.

Cameron: Why is today better for bold questions as compared to the past?

Matt: This is the part that I really get excited about. If you look back fifty to sixty years in computer science, pioneers had many of the same theories and ideas for practical applications that we do today, but two things hampered their ability: lack of sufficient computing power and absence of rich, complex data to analyze. The convergence of exponential improvements in hardware, proliferation of data analysis tools, and increased acquisition and storage of data makes it possible to ask thought-provoking questions and either get an answer or explore the data in near real time, at prices that are affordable to even medium-sized businesses.

Cameron: When asking bold questions with their big data, how quickly can a team expect answers?

Matt: It is really a factor of people and process more than technology. If you have talented individuals that understand the business need, have a can-do attitude, and are empowered with access to the necessary data and other resources, I have seen answers come back in weeks or even days start to finish. What kills momentum more than anything else is well-intentioned but misguided bureaucracy. I have seen the process bog down for months as a group struggled to gain approval for accessing the needed data. The irony is that gaining approval took ten times as long as the time to actually deliver results.

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