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Here’s why you’re not getting enough value from your unstructured data

Imagine your technician having a “conversation” with your equipment data to troubleshoot failures and system problems. Or automatically analyzing accident reports and camera footage to make your employees safer. 

These applications are available today for companies that use AI to interrogate their unstructured data—the event logs, images, customer feedback social media posts and reports that technicians and managers create each day. Without powerful technology, it’s difficult or impossible to analyze at scale, making it effectively invisible to your teams. 

There’s an immense amount of data in the world—both structured and unstructured—and it increases significantly every year. Globally, organizations generate about 403 million terabytes of new data each day. In fact, 90% of humanity’s total cache of data is from just the most recent two years. And as much as 80% of that data is the unstructured sort.  

How can managers and executives tap into their unstructured data to deliver greater operational insights that lead to better performance, lower cost and reduced risk. Natural language processing (NLP) is the key. 

  

Natural language processing extracts value from unstructured data 

You’re probably experiencing NLP every day. Applications like predictive text and autocorrect in word processors, chatbots that respond to our questions like humans, email filtering, text dictation, real-time language translation and even the targeted ads you might receive after a verbal comment over breakfast—all depend on NLP. 

Companies save time and money through effective and efficient analysis of unstructured data and also create safer workplaces, higher quality products and more satisfied employees and customers. By automating workflows around unstructured data, NLP helps streamline high-value business decisions, minimize operating costs and reduce human error. 

NLP technology teaches machines to understand language the way humans do. But the real benefit of NLP is its ability to read and understand the immense quantities of unstructured data created by day-to-day industrial operations. 

   

NLP delivers actionable real-world results 

You may be using NLP to 

  • Improve safety by automatically analyzing incident/injury reports 
  • Enhance customer experience by reviewing customer communications like social media posts, emails and customer feedback documents 
  • Identify strategic business opportunities by interpreting analyst reports, partner contracts, news coverage and press releases 

In the industrial sector, Avathon customers are using an aircraft maintenance application that empowers technicians to conduct machine-to-human dialog for troubleshooting asset failures and mechanical issues. NLP enables high-accuracy work, assessing faults using natural language queries, optimizing workflows and delivering relevant documentation more quickly. This solution reduces the cost of maintenance and improves aircraft availability by up to 10%. 

 

Natural language processing meets the challenge of optimizing performance 

By creating structure and gaining actionable insights from such data, NLP enables faster, more accurate decision-making. By organizing documents into logical groupings, it’s easier to find answers to your specific questions.  

NLP interprets documents through a variety of lenses (topic, author, time/date and location) to maximize the likelihood of identifying actionable insights quickly. Also, NLP understands industry-specific jargon and uses this understanding to find answers without the need for additional programming or training. 

By analyzing vast amounts of unstructured data with NLP, customers have improved operating efficiency and worker safety. NLP discovers the meaning embedded inside the data and makes it available to operators and managers, unlocking insights faster and more efficiently, reducing operating cost and optimizing safety and profitability. 

Powerful language-based AI tools are here today, and industry leaders worldwide are using them to improve their operations. Prepare now by understanding your existing data assets and the variety of cognitive tasks and roles in your organization that could benefit from extracting all the insights contained in those assets. 

To learn more about Avathon’s Natural Language Processing technology and how it can transform your operations, contact us to schedule a demo. 

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General John R. Allen (Ret)

Board Member

General John R. Allen is a retired four-star Marine Corps General and former commander of NATO and U.S. forces in Afghanistan, leading a 150,000-strong coalition force at the height of the war. He was the first Marine to command a theater of war. Following his military service, General Allen served as Senior Advisor to the Secretary of Defense on Middle East Security and later as Special Presidential Envoy to the Global Coalition to Counter ISIL, where he helped grow the international coalition to 65 member nations.

A career shaped by global complexity and high-stakes diplomacy, Allen’s combat and operational tours span the Caribbean, Balkans, Iraq, and Afghanistan. In Iraq’s Al Anbar Province, he played a pivotal role in supporting the Sunni Awakening that contributed to the defeat of Al Qaeda.

Allen also served as Deputy Commander of U.S. Central Command (CENTCOM), where he helped oversee strategic security across the Middle East and Central Asia. Earlier, as the principal director of Asia-Pacific policy in the Office of the Secretary of Defense, he helped shape U.S. regional policy, including involvement in the Six-Party Talks on North Korea.

He is currently a Strategic Advisor to Microsoft and a member of its Advisory Council, a Senior Fellow at Johns Hopkins Applied Physics Lab, a Fellow of the American Academy of Arts and Sciences, and a permanent member of the Council on Foreign Relations. He previously served as President of the Brookings Institution (2017–2022).

A published author and thought leader in emerging technology and global security, General Allen co-authored Turning Point: Policymaking in the Era of Artificial Intelligence and Future War and the Defence of Europe. He is also a co-inventor of several AI-related patents and advises technology startups.