AI is the new buzzword, and it is seemingly everywhere. Some people are using it; others are scared of it. No longer constrained to the tech world, over the past couple of years, artificial intelligence has crept into daily life, including the U.S. Army Aviation and Missile Command.
To help the workforce better understand topics such as machine learning, data visualization and data cleansing, the AMCOM Business Transformation Office hosted the second annual Data Analytics Day Sept. 10 in the Sparkman Center on Redstone Arsenal, Alabama.
AMCOM Chief Data and Analytics Officer Lisa Hirschler said the goal of the event was to open the minds of the workforce to the different ways data analytics can be applied daily throughout the command.
AMCOM commander Maj. Gen. Lori Robinson told the more than 200 attendees that technology is moving fast and will continue to move fast, so it is essential to embrace it, understand it and learn how to apply it to the work they do daily.
“As I think about data analytics from my perspective, I think about driving decision-making,” Robinson said. “This topic is important. It’s important for AMCOM, and it’s important for the Army.”
Robinson said events like Data Analytics Day are critical so the workforce can learn about the tools and products available as well as how those tools can be applied at AMCOM. She added that although technology is great, the human element cannot be removed. She said it is important to use the machine to do the things the machine does best and use the human to do the things the human does best — cognitive thinking and decision-making.
AMCOM Chief of Staff John Morris echoed Robinson on the importance of data-driven decisions and said the workforce needs to reduce its reliance on personal experience.
“We’ve got access to huge data sets, and some of that data is not helping us the way it probably should,” he said.
Morris asked the attendees to focus on using data to help the command be more efficient in the current resource-constrained environment, either finding ways to conduct business at a lower cost or doing more with the resources available.
“Focusing on how we can do more with what we already have right now should make things more efficient for us, and data can help us do that if we look at it right,” he said.
The Department of Defense released an updated AI strategy in 2023. It focuses strategic efforts on several interdependent goals that support the DoD AI hierarchy of needs — a pyramid with quality data as its foundation and responsible AI as its peak. Hirschler said the key there is responsible.
“We can do a lot of stuff with AI,” she said. “But I want to talk about the bottom of the pyramid, which is quality data, because you can't do anything if you don’t have a good foundation. That is going to be our focus for 2025.”
Quality data continued to be a theme throughout each presentation. Data Steward John Keck talked to the crowd about machine learning, which requires quality data to reveal patterns. Keck described machine learning as a branch of AI.
“It allows systems to learn from data,” he said. “It’s a very large statistical algorithm that combines functional logic with deep data, and it reveals patterns.”
Without context, the topic of machine learning can seem complex. However, Keck told the crowd they use it daily. Facial recognition to open a smartphone, targeted advertisements on social media timelines and voice assistants that provide facts and information are all examples of machine learning. Each is designed to take information, look for patterns, and, in some cases, take action.
“Machine learning increases data availability,” Keck said. “You’ve got a ton of data, but that doesn’t mean it’s necessarily available for insights. It’s just a lot of data. Sorting through that data and creating categories so you can take action is hard when you get big data, but it’s very valuable if you know what you are doing.”
For AMCOM, machine learning can be used to predict maintenance issues. The machine will learn histories and patterns based on aircraft data from sample sets and then make predictions based on the data. Supply chains are another way machine learning can improve efficiency. If a logistician needs to find out why a part did not arrive on time, the variables and models will determine what went wrong and how to prevent it from happening again. The foundation is quality data. With multiple samples and dialed-in data, the machine will continue to learn and identify patterns.
Keck said, “You keep running that same data; that same clean data continues to give you better and better information. That’s why you want repeatable processes with standard applications.”
The Data Analytics Center is now part of the AMCOM Business Transformation Office, established earlier this year. Its role is to empower AMCOM to adapt and thrive in the digital age through the integration of digital solutions, business processes and data analytics. Hirschler said this will enhance decision-making ability at all echelons by providing leaders with data as a strategic asset to outpace enemy threats.
To view photos from Data Analytics Day, visit AMCOM's official Flickr page.