Extracted from MS&T Article. See the full artice here
Defense departments have been measuring and evaluating training events since well before this contemporary era. The major news and developments in this learning space find military services sprinting toward more rigorous, technology-based practices and methodologies to certify individuals, units and staffs as mission ready. Of particular significance, training organizations and their industry partners are increasingly using technology enablers familiar to MS&T readers, including artificial intelligence (AI), machine learning (ML) and others, to more quickly, accurately and comprehensively, measure and evaluate training audiences.
Beyond “Check the Block”
Captain Tim Hill, commanding officer of the Naval Air Warfare Center Training Systems Division (NAWCTSD), provided one service perspective on these trends, first calling attention to a “great deal” of senior level interest in better understanding the effectiveness of any training/training system. “We have always measured performance of the individuals/teams that are completing training periods in some way. But the manner and degree to which that is done is always an individual decision for each program or capability,” the Orlando-based community leader added.
The NAWCTSD commander continued his service overview, pointing out in the current/future environment, his command is seeking to harness emerging technologies, such as AI and ML, to measure performance in new and better ways. He explained, “We have an opportunity to measure performance at a much deeper level by collecting data that is resident in our learning management and training systems and analyzing it in new ways with this technology. This will allow us to measure individual or team performance, for a given event and collect trend data for these individuals and teams.”
Further the collected data can be compared to standards to rate the proficiency of those individuals and teams; but this will also allow subject matter experts to begin examining trends across the entire population of individuals and teams in the Navy, so that the service can better understand proficiency across the entire fleet.
“This has the potential to allow us to move from a ‘check the block’ training mentality, where we assume operators are skilled because they completed a training event, to an environment where we’re examining true warfighting proficiency,” Hill emphasized.
Beyond the US Navy’s quest to better understand fleet-wide proficiency and gain other outcomes, more quick-paced developments are occurring.
Cervus Defence’s rapidly expanding client portfolio includes military services in the UK, US, the Netherlands and the Middle East. Alan Roan, the UK-based company’s managing director, reflected on this diverse customer list and noted the main, current, common requirement among his varied customers was descriptive analytics. “A lot of our customers are seeking a better understanding of what they have just done. From a training activity, they want to capture the data and very quickly turn the data around, get it analyzed, and presented back to the trainee through an after action review or part of the learning experience.”
The veteran owned data-analytics company is moving beyond this common datum point, using AI and some of the data science tools, to reach a higher plateau of predictive and prescriptive analytics. This journey allows leaders to take and compare existing data sets against a recently completed event. Roan explained “You can start forecasting where those individuals and units are in terms of performance, and even what might happen if they do different type activities.”
Indeed, one Cervus customer, the US Marine Corps, is starting to explore how to use analytics to forecast where its readiness gaps are situated. “On the workforce analytics side, it can be used to see where Marines aren’t ready to deploy and do their job, and they can start to consider training systems to give them a more efficient use of training.”
Another rapidly emerging trend finds military customers starting to aggregate data. Whereas, heretofore, one training system delivers analytics for that specific system, multiple training systems, from different simulation environments, are delivering data in a common format into one repository. One prime example is travel and related cost-avoidance data for exercise participants. Roan noted, the cost data applied to the training data can provide a much more accurate cost for training readout. “And you can apply other data sources – workforce analytics, engineering analytics and others, on top of those – you are combining these and getting an enterprise approach to data. This is a much more holistic use of these data sets, by joining them together,” he added.
A third emerging defense department requirement trend moves beyond traditional military performance, toward performance for individuals, teams and tasks. “These are often psychological measures,” Roan observed, and noted that the UK military, in particular, has a sharpening focus in some of its training programs in team performance, relationship measurements, how to make teams perform better on specific tasks, and other focal points.
Analytics and Data Storage as a Service
Driven by military end users’ persistent demand, the pace of community-wide practices and requirements, and their enabling technologies, will continue to evolve in the next 24 or so months.
At the top of Cervus’s Roan’s list of evolutionary trends was continued aggregation, whereby more training data sets will be connected to other sources of data. Outcomes from this effort will allow training organizations to measure mission stress and physical loading during a training event. “But this will go much further than that – toward the ‘internet of things’ as military systems become more connected. And when you are doing training or are in operations, we’re going to capture all of this data and we will need to figure out formats by which we can extract, align and store it so we can start doing analysis against it.”
Other concurrent technology enablers to bring Roan’s vision to reality will include increased, remote computing power, quantum computing and cloud-based approaches to allow storage, analyze and process data. Roan concluded, “These will lead to a change in the market – a disruption – reducing costs a lot and giving increased access to smaller companies so they can start putting and building their applications on these cloud-based systems. Things will also go to more of a service model, with analytics, storage or other capabilities as a service.”