Q:How did you become interested with numbers? My career started as a hydrogeologist working in the environmental field. We would use statistical analyses to determine risk-based cleanup levels for various types of contamination in specific media (soil, groundwater, etc.). Later in my career as a manager, I learned that I could use numbers that I tracked on the technical/operational side of things to make decisions for cutting costs and I used this knowledge to explain to upper management using their language (dollars) to get capital-intensive projects approved showing return on investing. In the first year of tracking operations, I was able to cut cost by over $1.5M and I was hooked on numbers/data ever since.
Q: How do you use data on a daily basis? I currently work on the Information Technology (IT) side of Geographic Information Systems (GIS). As such, I use a lot of spatial and non-spatial data daily. From an IT perspective, I use several data-logging tools that provide metrics to analyze the performance of servers in real-time, as well as test servers under load for predicting future performance. I run several queries in databases to verify record counts as a smoke test for whether various processes have completed. On the GIS side, it is much more exciting. I can take normal data describing what something is (attribute data) and combine it with spatial data describing where something is and then layer the data, spatially analyze the data, and arrive at something much more meaningful. So instead of looking at data in tabular form in a spreadsheet, for example, I can create a heat map showing high cost areas or high frequency areas to visually pinpoint specific areas needing optimization.
Q: What do you believe is the importance of data in terms of productivity? In our current and foreseeable future, data is everything. If a business isn't paying attention to specific metrics and comparing where they are in relation to their competitors, they won't be in business much longer. Data, when used properly, can be used in virtually every aspect of every business to find ways to focus on problem areas that equate to higher costs, whether its rework on an assembly line or determining placement and number of additional stores for expansion, it all comes down to data. And it's not just productivity with business. With the advent of FitBit and smart wearables, we are now constantly gathering and analyzing our own personal data from the amount of exercise we get with the number of steps we take or flights of stairs we climb to determining our peak and resting heart rate. We can use these data to improve our own personal productivity and to improve our health, etc. Data can be used on virtually everything.
Q: What are the benefits of data utilization? I feel "data utilization" is a broad and generic buzz term that gets overused. It is usually equated with monetization of data whereby, for example, the higher number of clicks on a website equates to higher priced ads a company can charge to bring in greater revenue. I also see the term used in conjunction with other overused terms like evidence-based or fact-based decision making. For me, data utilization is really just a term to mean a mindful use of data for making decision that yield continuous improvement. It is an iterative process and really comes down to collecting the right data, using the right tool to analyze the data, and as an outcome of good information, arriving at appropriate actionable items that, if acted upon, will in turn make improvements. And the entire process starts all over again collecting data on the process that now has the newly implemented improvements, which then should tell you whether your improvements worked as expected and where you can make additional improvements.
Q: How has the use of data in your work allowed for you to better interpret information? Data by itself is meaningless and more data does not necessarily mean better information. It is only when we collect the appropriate data, put it into context and derive relevant meaning from it does it become useful information. With this understanding, it has allowed me to not get bogged down with collecting too much data and allows me to focus on a specific set of data relevant to answering a specific question and not get too distracted with irrelevant data (noise) that may lead me towards a bad decision. My best days at work are when I combine seemingly disparate sets of data spatially and patterns emerge that provide information that tells a story that otherwise would not have been told.