One Defense Department office used workforce analytics to more easily determine which soldiers would succeed and which would drop out of an advanced training course.
The Defense Department trains its service members to be the best in the world at what they do. Just getting accepted into some DOD courses is an achievement, and those who pass are considered the best of the best.
Individuals selected for one intense defense course must complete a grueling six-part training process that can take one to two years, depending on the candidate’s primary job field.
At the start of the process, candidates are assessed both physically and mentally to determine whether they can continue the training, but with such rigorous requirements, the graduation rates can be low. Only about 40 percent of those admitted to the course actually complete it.
Although some drop-off is expected, DOD wanted better insights into the assessment process with an eye toward identifying those individuals most likely to complete the program. If instructors could focus their attention and resources on the most promising students, DOD could improve course completion rates and save money. To do so, the department turned to workforce analytics.
Workforce analytics empowers agencies to do more than simply analyze employee pay or discover how much work a typical employee can complete. It can also fundamentally change how employees work and are evaluated. The DOD office conducted a workforce analytics project that emphasized the most important tests in order to weed out individuals unlikely to pass the course earlier in the process, thereby improving its training and selection process.
Using data from 13 training courses, the office analyzed selection practices so it could move from a model of anecdotal and intuition-based reasoning to one that produced decisions that were repeatable and defendable. The analysis considered physical, mental and peer evaluation metrics collected during the course to determine which most correlated with success.
By altering the order of its training exercises to move the most important ones earlier in the course, DOD could more easily determine which soldiers would succeed and which would drop out. Having that insight earlier in the training process could save money and minimize the disruption to the candidates unlikely to complete the course. Because it costs $30,000 to train each warfighter and an additional $15,000 to relocate those who are unable to complete the program, even a 10 percent improvement in outcomes could save the battalion an estimated $10 million per year.
Further use of workforce analytics
As the nation’s largest employer, DOD employs approximately 2 million active-duty service members and civilian employees. Each position stands to benefit from an increased use of analytics to improve efficiency, operations and recruitment.
The true value of analytics comes in learning what is not already known. Although analytics can surely improve how the Pentagon maximizes employee value, there are other areas yet to be discovered. Analytics can provide insights into how employees work, what type of employee fits best into a specific role and even what positions might not deliver expected value.
Although the defense budget has seen an increase under the Trump administration, Pentagon officials must always keep costs in mind. Funds that are saved in one area can be reinvested into others, giving DOD the financial flexibility to adjust as times change.
Analytics offer a wealth of advantages to DOD organizations that pride themselves on a top-notch workforce composed of the world’s best-trained warfighters supported by a deep and committed civilian staff. Analytics can only improve the productivity of this workforce, helping defense agencies streamline and enhance operations to better support the mission.