The cover story of the May 6th, 2017 issue of The Economist boldly proclaimed data as “the world’s most valuable resource,” which is a new reality that has taken shape over the years.
Technology used to be all about products, but the 1990s brought about the rise of products and services. In the early-to-mid-2000s, our attention jumped to social media services that were all about your relationships with other people. Now the technology industry is focused on data and the insights that can be extracted from it.
Many may agree that data is in fact the world’s most valuable resource, but the numbers show that data is actually the world’s most underused valuable resource. The truth is that only 1-5% of all data is actually used. It might be easy for companies to pat themselves on the backs about the valuable data that they’re collecting, but if it’s not being used, then what’s the point?
Part of the challenge with making use of all of that information is that 80% of data is unstructured in content like documents, messages, social media posts, pictures, videos, and audio. Unstructured data is notoriously difficult to make sense of because it’s not necessarily organized in a way that can be easily processed. Simply said, it’s difficult to compute.
At the cross-section of ever cheaper computing and massive progress in pragmatic computing, often referred to as artificial intelligence and machine learning, the type of analysis required to turn unstructured data in to meaningful insights becomes possible.
Even more than that, the promise—and reality—of AI is that the right data insights can be delivered to the right person at the right moment without requiring them to think of or search for anything. Instead of being standalone systems, these AI components can be purpose-built and plugged in to existing enterprise systems such as Salesforce and ITSM applications so that companies can manage their data and insights in a single location that has the correct context.
All companies—large and small—need to investigate how AI and machine learning can help them make sense of the mountains of valuable data that they have access to regarding their business operations, customers, competitors, and industry trends. With each passing day, there is a rapid increase in the amount of fascinating unstructured data that is being produced and collected, so if you’re behind today, just imagine how many new valuable insights you’ll continue to miss out on as time goes on if you don’t make data analysis a priority.
You might think that the point of this article is to encourage you to use all of your data at once, but the best place to start is to try to analyze and act on even just a few more percentage points of data than you’re currently using. The overall goal is to make progress and start treating data like the valuable resource that it is.