Data Training for all Echelons is Worth the Investment

Drowning in the Data

By Cpl. Mitchell Rasmussen, 555th Engineer Brigade

Article published on: April 4, 2025, in the Army Communicator Spring 2025 Edition

Read Time:< 7 mins

In 2020, International Business Machines (IBM) estimated that the world generated an immense 2.5 exabytes of data daily (IBM). To visualize this, consider that a modern CD has a diameter of 4.72 inches and a thickness of 0.047 inches, with a capacity of 700 megabytes. The interior dimensions of a standard 20-foot shipping container are 19 feet and 4 inches long; 7 feet and 9 inches wide; and 7 feet and 10 inches high (Stoltz). A stack of CDs measuring 7 feet, 10 inches high would contain 2,000 CDs, totaling only 1.4 terabytes. One 20-foot shipping container could hold 931 such stacks, amounting to around 1.2 petabytes. To match the daily data generation of 2020, one would need 2,134 shipping containers or 3.9 billion CDs. 2,134 shipping containers is enough to cover 5.9 football fields. Annually, that number soars to 778,910 containers, 1.4 trillion CDs, or 2,153.5 football fields.

A leading cybersecurity company, Imperva, comments on this massive wave of data, revealing that 49.6% of 2023 internet traffic came from bots; more than half of which were built for malicious intent (Smith). Global network Cloudflare reports a daily average of over 25 million HTTP requests per second, with 57% of their total traffic coming from API interactions (Cloudflare). This massive and increasingly malicious flow of data directly fuels the cybersecurity challenges of the Army. Furthermore, managing data has become challenging due to the growing volume of cyber threats and inefficient training. Addressing this requires improved education and more effective use of available tools.

This is not a new issue. As early as 2004, Professors Martin Eppler and Jeanne Mengis from Switzerland introduced the concept of information overload on an interdisciplinary basis (Eppler & Mengis). Even though it was a literature review, the paper showed that this information overload was a multifaceted problem not just limited to specific areas like accounting. Back in 2004, American internet users were still switching from dial-up to broadband, so even archaic data flows could be overwhelming. Now, for obvious security reasons, the United States military does not publish its data footprint size. However, signs indicate that the military also struggles to manage the current data flow.

In 2017, Commander J. Lee Bennett of the U.S. Navy called for modern software improvements to help Sailors avoid information fatigue syndrome, caused by the vast amount of maintenance-related data (Bennett). In his 2024 article “The Coming Military AI Revolution,” Col. Josh Glonek explains that artificial intelligence (AI) is the only way to handle the data, as the human mind cannot process and analyze such immense volumes (Glonek). The Army has already proven success of AI through use of Army Vantage, the data platform of the Army Data and Analytics and Platform (ARDAP). In 2020, Army Vantage helped contracting officers recoup over a billion dollars in unsettled funding commitments. One can imagine what AI could do to a backlog of work orders.

However, relying solely on technology is not enough. Lt. Col. Brian Forester proposes that while future success will depend on AI-driven analytics, leaders must avoid overanalyzing and instead focus on cultivating effective data analytic knowledge (Forester). One of the better indicators of data analytic knowledge is the use of Microsoft Excel.

The Army often misuses Microsoft Excel, treating it as a one-size-fits-all solution without fully leveraging its capabilities. In the 2024 Fall/Winter edition of the Army Communicator, Maj. Donald Ingham and Capt. Noe Lorona criticized the Army's lack of innovation, attributing this partially to the failure to fully utilize available tools, including Excel (Ingham & Lorona). Excel is mentioned as a "powerful tool for organizing, analyzing, and automating data" (Ingham & Lorona). However, having personnel trained on the software may not be in the picture.

A 1995 research paper by Jonathan Pemberton and Andrew Robson found that, in a sample of 57 office staff personnel, roughly 50% had only basic spreadsheet skills, 25% lacked any skills, and the remaining 25% had advanced but not expert-level skills (Pemberton & Robson). When 75% of an office staff lacks the skills to properly utilize Excel, mistakes are bound to happen. From 1990 to the present, numerous companies have lost hundreds to billions of dollars due to Excel user errors.

On the other hand, using Excel beyond its limitations also hinders operations. For instance, the Army Digital Training Management System can export mandatory training summaries as Excel files, which can be reformatted into pivot tables. However, creating a unit training tracker database remains a laborious task involving multiple Excel files. In that case, having the option to export the data as either an Access or Azure database file would be more suitable for the task. The 93rd Signal Brigade solved this problem by developing the Training Tool Tracker Application to help their training manager track training more efficiently. This tool uses Microsoft Power BI and SharePoint Online to provide both an overview of unit and individual training status.

Developed by 93rd Signal Brigade, the Training Tool Tracker Application enables training managers to check training records efficiently. (U.S. Army photo)

Enlisted personnel need more opportunities to develop data science skills, like the examples above, to better support their leaders. Officers have numerous opportunities to acquire data science skills through various programs and certifications. For example, the Army Talent Management program allows STEM degree holders to commission as network or information systems engineers and work as data scientists. Additionally, the functional area (FA) 49 Operation Research/System Analysis (ORSA) is available to officers with graduate STEM degrees or those who have completed the ORSA-Military Application Course (MAC) (Henry & Smith).

In contrast, enlisted personnel have fewer opportunities for official training in data science. The closest option is the Knowledge Management Qualification Course (KMQC), which is limited to battle staff personnel and focuses on managing organizational knowledge rather than data analysis. Apart from the KMQC, enlisted personnel are left to self-study and earn certifications for promotion points and better productivity. However, structured training programs are essential for developing comprehensive data science skills. Without adequate training, NCOs struggle to support their leaders effectively, ensuring they have "maximum time to accomplish their duties" (NCO Creed). The specialized 1st Stryker Brigade Combat Team Raider Analytics, Innovation, and Data (1SBCT-RAID) team is open to individuals with relevant talents in data analysis. However, retaining these specialists is challenging, as they often find the private sector more appealing than military life; a recurrent issue that started as far back as the Industrial Revolution. The Army must invest in more training opportunities for enlisted personnel to develop data science skills, ensuring they can effectively support their leaders.

Implementing any solution will be challenging. The simplest approach is to exempt a selection of data analytics-related certifications from the Certification Assistance (CA) three-certification-per-10-year limit. This way, enlisted personnel will have more incentive to pursue data analytics proficiency without sacrificing a certification slot for career-advancing certifications like the CompTIA trifecta of A+, Network+, and Security+. Microsoft already offers a robust data science program with diverse pathways. Additionally, Microsoft Excel training could be included. However, once these certifications are earned, how will the new skills be utilized? For instance, if a network communication systems specialist (25H) earns the Azure Data Scientist Associate certification, they will be equipped to build machine learning models on Azure. Yet, the 25H career progression remains unchanged. The specialist will eventually become a sergeant with extra knowledge that might be useful in the training room but largely unnecessary otherwise. The specialist is left to manage these skills independently. To truly incentivize data training, there needs to be a way to recognize these efforts, such as creating a data additional skill identifier (ASI). This ensures that when relevant job roles open up, there are already trained personnel ready to fill them.

Alternatively, creating a data-focused military occupation specialty (MOS) presents a more complex solution. This new MOS could be developed from scratch or adapted from existing ones. For instance, the Military Intelligence (MI) field already has analysts specializing in specific areas. One of these specialties could be data analytics. The MI field could model its analyst training after the prime power production specialist (12P) training, where all 12P specialists receive the same fundamental electrical education before branching into specialties. Similarly, MI analysts could undergo basic data analytics training before moving on to different specialties.

Another field already has data analytics built into their job responsibilities: human resources specialists (42A). Using the Integrated Personnel and Pay System-Army (IPPSA), 42As can generate human resources (HR) metrics with Microsoft BI. However, this is a gross underutilization of their potential as data analysts. Creating a new 42 series MOS dedicated to HR data analytics could ensure proper utilization of this specialty. If new data specialty MOSs are created, units should receive educational briefings to understand the full scope of possibilities and use these specialists effectively. The goal is to avoid the situation that occurred with the cyber network defender (25D) MOS, where units misunderstood their scope of practice and underutilized their cyber expertise by assigning them to Communications Security vaults.

Managing the advancing tsunami of data is a critical issue in cybersecurity. Service members need more data analytics training to effectively handle this challenge. Available tools must be fully utilized to maintain operational effectiveness. Leaders and operators need to complement each other within the data science field. Addressing these issues will require a concerted effort from leaders and operators to stay ahead of the data curve and ensure the security and efficiency of military operations. If the Army fails to invest in comprehensive data training, the consequences will extend beyond inefficiencies – the Army will drown.

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