As a leading systems integrator, our advanced analytics teams are helping the U.S. government using innovative technologies, including techniques in artificial intelligence, machine learning, and other data science services. In particular, advances in robotic process automation (RPA) are resulting in mission efficiencies.

'We've spent a good portion of the past two years designing, delivering, and investing in breakthrough custom digital solutions for the national security missions of Department of Defense and the Intelligence Community,' said Dr. Don Widener, Director of BAE Systems' Advanced Analytics Lab. 'Specifically, RPA is delivering quantifiable results on one of our existing programs. We are seeing a 98% increase in efficiency with the implementation of a custom-built RPA for information dissemination across domains. What used to take 3 minutes, now takes 4 seconds - which, when multiplied by the number of actions, enables our customers to save 17.5 hours over the course of one week.'

Don Widener, Ph.D., Director, Advanced Analytics Lab, BAE Systems

BAE Systems has a strategic partnership with UiPath to deliver machine learning and automation capabilities to the intelligence community and defense agencies through its robotic operations center.

'We have a unique role between the automated result and the UiPath tools,' continued Dr. Widener. 'We integrate the RPA tools that function as multipliers, automating day-to-day business processes through human-machine teaming. We are aligning RPA technology with an analysis program, which is resulting in an incredible amount of time savings on the production side of the operation.'

What does success look like?
First, our developers have a deep understanding of our customer's business, mission process, and the operational, technology, and governance environment in which bots can be deployed. Through this understanding, we then design the bots - automation models - to address repetitive tasks. Dr. Widener's reference to a custom-built RPA includes a bot that is trained to open a password-protected PDF file from one domain and send the same formatted text via email across to another domain.

In addition to our deep understanding of the mission, another key to the success of RPA is that it can be updated as the mission or software tools change. Our team understands which bots to build and how to successfully gain deployment approval. Plus we ensure the savings is greater than the effort to build or deploy the RPA.

'We have leveraged our knowledge of the customer's mission to architect appropriate bots,' said Dr. Widener. 'Our custom automation is delivering a huge advantage to our customers as a lot of people now want to work from home while they perform unclassified actions. This automation, if implemented more widely, could permit more production in the future to take place remotely.'

Training our data scientists
We've trained more than 150 BAE Systems employees in how to utilize cutting-edge technologies, like RPA, to increase production efficiencies and save time.

'We have seen the value that RPA can bring in helping our analysts do some of the repetitive tasks, allowing them to focus on higher-priority and mission-critical tasks,' said Dr. Widener. 'This in turn has been beneficial for our customers.'

BAE Systems employees have access to hundreds of training courses through the I&S University, Advanced Analytics Lab 'Build-a-Bot' program, and through the company's partnership with UiPath.

Integrating RPA into your operations
If you're looking for more information on our data science services, or would like to request a demonstration on our leading capabilities, please contact Michelle Fling at michelle.fling@baesystems.com.
Opportunities to join a winning team!
If you're interested in a career leading the pace of data science services and IT innovation, while helping to protect national security, then join us!

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BAE Systems plc published this content on 18 November 2020 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 19 November 2020 21:26:00 UTC