Guest Editorial: Turning Old Data Into New Insights for Better Outcomes

Abstract

_ I recently read about an archeological study at Interamna Lirenas, central Italy, where a very ordinary Roman settlement; thought to be unpromising, ‘a failed backwater,’ revealed new discoveries that have forced historians to rethink what they believed to be true about the final years of the Roman Empire. The study revealed a town that was thriving for centuries after Roman Italy was thought to have been in decline. The study’s author and project lead said, “There was nothing on the surface, no visible evidence of buildings, just bits of broken pottery. But what we discovered wasn’t a backwater, far from it. We found a thriving town adapting to every challenge thrown at it for 900 years.” The project lead goes on to say that many other average Roman towns in Italy were just as resilient, “It’s just that archaeologists have only recently begun to apply the right techniques and approaches to see this.” The story reminded me of the enormous variety and volume of historic data that’s been inaccessible for decades in our industry, trapping knowledge and insights of enormous value. This data is old, but it’s not out of date. In truth, it’s a nice problem to have. If we apply new techniques, we can open a world of new information about an asset, operation, or enterprise. The data includes commercial field development planning, well logs, drilling reports, consulting, unstructured data reports—all the things that combine with the structured technical information that we get from surveys and planning activities. This treasure trove of data is untapped due to various reasons—outdated infrastructure, fragmented systems, storage in filing cabinets, siloed databases, and forgotten spreadsheets … bits of broken pottery, if you will. Often, it’s used once and then never referenced again. Organizations are wrestling with the challenge of bringing this old data into their business. They need to be able to look at the information, to recognize what it is, know what it means, where it should be filed away. They need to be able to bring it together with other relevant information and contextualize it. The end goal is to have it available when people come to act, to make decisions. For this, it must be reliable, trusted, and discoverable—and at their fingertips. By the time it reaches people, or artificial intelligence (AI), it must be ready to use. Connecting Data One challenge companies face is the mechanical issue of connecting the data—getting it out of these siloed and fragmented systems—and into a system where it can be parsed and understood. Thankfully, in recent years a swathe of good technology products for achieving this at scale have been developed. Data archaeology in our industry is now a realistic prospect.