Many thought, or at least hoped, that the 1969 moon landings would herald a new era of space exploration. Advances in the field have perhaps been slower than those promised in science fiction movies, but this is not to diminish its tremendous importance for humanity, and while we may not be living on Mars yet, the knowledge that has been accrued has had a profound impact on our world. Space exploration has been a huge evolutionary step, and data has been at the heart of it.
Ever since NASA was founded by President Eisenhower in 1958, it has been data-driven. Today, the organization collects petabytes of data from thousands of satellites, telescopes, probes and so forth - about both space and Earth - and it has led the way in opening up its datasets to the scientific community at large so that they can be leveraged for insights that could help us in myriad ways - from better understanding climate change to finding a new planet to evacuate to when it takes hold.
NASA’s Lessons Learned database, for example, makes available a vast, constantly updated, mass of information from past missions to everyone from academics to private organizations. The data collected from ‘The Stardust Mission’, a UC Berkeley-based NASA project created ‘to collect samples of a comet and return them to Earth for laboratory analysis’, has also enabled NASA to understand the conditions under which comets were born. This profound scientific discovery was only made possible because of scientifically active citizenry, with a group of citizen scientists isolating two comet particles, each only about two microns (thousandths of a millimeter) in diameter, which were critical in explaining their origin and evolution. These volunteers, who call themselves ‘Dusters,’ scanned more than a million images as part of a University of California, Berkeley, citizen-science project.
It is not just external discoveries that NASA uses its data for, it also uses it internally to reveal insights about how it is run, particularly around its own staff. In a time of decreasing budgets, NASA must ensure that it is running efficiently and that the high calibre of talent that it has always relied upon remains in place.
Stephen Chesley is a member of the National Aeronautics and Space Administration’s Agency-wide Workforce Planning and Analytics Team and is based at NASA’s Headquarters in Washington DC. As the Agency leader in workforce analytics and modeling, Mr. Chesley is a recognized functional expert responsible for building the workforce analytic and modeling expertise throughout the Agency, and he has successfully built and implemented tools to collect and aggregate workforce data that are used as a primary resource for workforce data within NASA and for researchers outside of NASA.
We sat down with him ahead of the HR & Workforce Analytics Summit , which takes place this June 19-20 in San Francisco.
How did you get started in your career and what first sparked your interest in analytics?
When I finished grad school, I was accepted into the US Government Presidential Management Intern program. As part of this program, NASA hired me to do Agency-level workforce planning and to be the keeper of workforce data and reports. As our organization matured, we became more interested in ‘real’ workforce analytics rather than just reports. Since I was comfortable with numbers and understand many of the analytics concepts (and because I could speak a language that our Engineers and Scientists understand) I was asked to build the workforce analytics capability.
Do you feel HR is behind other departments when it comes to implementing data initiatives? If so, why do you feel this is the case and what can HR leaders do to rectify the situation?
I think that in certain sectors HR has been at the forefront of data initiatives from a workforce planning perspective, managing workflow and service delivery including skill and competency modeling. Operational research techniques have been used for years for staffing, hiring and training in industry and military. More recently, however, I have seen a decline in resourcing and budgets devoted to HR analytics; instead, as a cost savings measure there has been a growing reliance on commercial solutions with more limited capabilities. HR leaders need to be more vocal about the importance of data initiatives and ROI for analytical work to build/rebuild their capability.
How is a data-driven culture best achieved?
It is important to set realistic expectations for what data can and cannot do.
What technologies do you see as having an impact in the analytics space in the near future? Wearable devices are an obvious way to collect data on employees, do you think we will see them being used more in the future? Should they be?
Communication channels will be mined more in the future. This includes message content, tone and frequency. The reliance on cloud computing (renting/buying time on a platform rather than buying/up-keeping one’s-own platform) will also heavily impact the analytics space in the future. The idea of using all available data (from wearable devices, web crawlers, etc.) is tempting but could cross the creepiness-factor’ line. I hope we don’t move too far in that direction.
You can hear more from Stephen, along with other leading experts in the field from the likes of Facebook, Airbnb, and Chevron, at the HR & Workforce Analytics Summit. View the full agenda here.
BONUS CONTENT: Hamed Valizadegan, Research Scientist at NASA, on using machine learning in space research problems