This month, the Defense Logistics Agency (DLA) released an update to a foundational data and analytics document that will direct data governance, acquisition strategies and the incorporation of emerging technologies for the military’s combat logistics branch.
The “DLA Data & Analytics Strategy,” an internal document that GovLoop has reviewed, creates data policies and directions that will instruct every DLA department going forward. The plan also forecasts a future of hybrid cloud, machine learning and artificial intelligence at DLA.
“Harnessing the power and value of data and analytics will require a transformation of our workforce and technological capabilities,” DLA Director Army Lt. Gen. Darrell K. Williams said in a written statement introducing the strategy. “This Data and Analytics Strategy outlines our approach to creating an environment where trusted data is readily available and accessible for exploitation, the right tools and technologies are available and effectively utilized, and our people are empowered enterprise-wide with the training and skills to leverage advanced analytics in all operational activities.”
DLA’s data strategy aims to elevate data as a strategic asset throughout the enterprise to support external stakeholders – namely the United States’ and its allies’ warfighters – and internal business processes. Moreover, the data strategy directly aligns with the “DLA Strategic Plan” that outlines the goals and focuses for DLA from 2018-2026.
Leaders perceive data as crucial to the agency’s mission, which is to manage the supply chain of the military and related organizations, as exemplified by the recent establishment of a Chief Data Office, investments in data visualization and the release of the strategy. Progress in data usage at DLA, specifically through the use of data visualization tools, has already found irregular purchasing contracts and helped identify backorders earlier to ensure that users can predict and respond to possible shortages in material.
Six lines of effort – which “break out the necessary goals and activities to achieve the mission and vision” – are identified in the strategy: infrastructure, security, enterprise data lifecycle management, analytics capabilities, governance and culture. A strategic end state powered by the data and analytics lines of effort will “optimize decision-making and enhance warfighter readiness and lethality.”
A major effort of the DLA Data & Analytics Strategy is to work from a single source of truth across a large and geographically dispersed enterprise, Lead Analytics Strategist Lindsey Saul said in an interview with GovLoop. DLA exists in nearly 30 countries and employs 26,000 civilian and military personnel.
Saul said DLA’s size and expanse has resulted in disparate homegrown tools and multiple supply chains with inconsistent data standards. Differences in data standards hamper efficiency, reduce interoperability and muzzle the effectiveness of emerging technologies.
“We are taking measures to really ensure that our data is standardized, that we have tools to help the community with this effort and that we are all working from a single source of truth,” Saul said.
Of note in the document is that DLA is looking to increasingly turn to cloud computing processes for data and analytics. Specifically, the document identifies Platform-as-a-Service (PaaS), Infrastructure-as-a-Service (IaaS) and Data Analytics-as-a-Service (DAaaS) as models that improve enterprise data and analytics. DLA hopes to support IaaS and DAaaS to allow for easier, faster and more cost-efficient systems where analytics capabilities can exist in a hybrid data environment. Cloud solutions can remove silos and improve standardization.
Data quality, Saul said, is “first and foremost” a priority of the organization and the new strategy, and it is key to enabling disruptive technologies that the department sees being widely incorporated in the next five years. The strategy targets machine learning and artificial intelligence as ways to enhance operational efficiency by improving performance metrics, revenue forecasts and trend predictions. But data standardization will need to come first.
DLA already has an enterprise data warehouse – a system for reporting and data analytics – and a central data dictionary to define and contextualize data, but future efforts will focus on improving their standardization and accessibility. The agency also predicts creating a data lake, where data can be stored in its original format, and fostering self-service data preparation.
The Data & Analytics Strategy, which was released on Aug. 5, is a major addition to DLA’s recent timeline of data initiatives. In December 2016, DLA stood up the Chief Data Office and created the chief data officer position, which Teresa Smith occupies.
Culture toward data – a line of effort in the strategy – is strong already at DLA, Saul said, with operations research analysts enthused to increasingly learn and incorporate analytics to improve business processes.
Recently, DLA’s major subordinate command, DLA Troop Support, evaluated about 10% of its subsistence – including a range of food support from individually packaged meals to full-service dining facilities – contracts by using a commercial data visualization tool. The team identified pricing anomalies that showed money was owed to the government, and DLA has recouped about $10,000 so far.
A recently acquired major data visualization tool is in testing at DLA but will eventually be released to the entire agency workforce of 26,000 people, allowing business leaders to evaluate insights that can be generated by data scientists. Improving data accessibility is a major focus for DLA, Saul said, and the agency is restructuring data dictionaries to make them more business-friendly.
“I don’t feel like it is really an uphill battle in that sense because I think that people already have a basic appreciation for what data and analytics does and how it can help their business,” Saul said, noting that DLA’s business side was especially receptive to data and analytics compared to other workplaces.
A “Data & Analytics Governance Plan” complements the strategy, laying out how the governance line of effort will be implemented and measured at DLA.
Saul said she views the two documents as a map, or “blueprint,” for DLA’s data and analytics future, crafted by both traditional and outsider views of DLA data processes. Furthermore, Saul said creating a framework for the Chief Data Office to build off of is her proudest accomplishment throughout her tenure at DLA.
“I’m really proud of how those documents turned out. It’s been really well received. And I think it sets in motion the guidelines and vision for the organization as a whole,” Saul said.
The documents are effective immediately, and DLA has already begun implementation.