The Defense Department is seeking ways to use data more effectively for improved decision-making on the battlefield and in its business practices, Deputy Defense Secretary David L. Norquist said.
Norquist and DOD Chief Information Officer Dana Deasy met with data analytics industry experts in the Pentagon today to discuss the way ahead for the department.
"This is the core of what we need to do under the National Defense Strategy," the deputy secretary said, noting that better use of data leads to increased reform and lethality. At the most basic level, data from everyone's salary and every piece of equipment could be collected and reported in a data set to which analysis could then be applied, Norquist said. This information would be especially useful in the DOD-wide audit and reporting to lawmakers, he noted.
To accomplish this, he said, DOD has to determine internal methods of data identification, collection, organization and how it can be used most effectively for operational and business decisions.
"This is an area where there's a great deal to be learned from industry," Norquist said. "We don't have to be ahead of industry. We just have to competently follow industry and take advantage of some of the things they've already done."
Deasy said data accuracy is especially important to making informed decisions and allowing individuals to trust the data.
Although the way industry uses data may differ from the way the Defense Department does, he said, DOD could borrow some of industry's methods.
Juliana Vida, industry representative and retired naval aviator, said data collection could come from sensors embedded in machines, weapons platforms and facilities to predict outages, material failure and other information, thereby saving money and making things safer.
Data analytics is so important for the department, she said, because the margin for error is shrinking, the decision cycle is shortening, and the attack surface is growing. "There are more bad guys out there looking for vulnerabilities," she added.
Anthony Perez, industry representative, said data analytics collection and processing could be automated to operationalize the data so humans in the process can make informed and critical decisions.