Knowledge mining, one of the buzzwords that you see more and more, but what does it actual mean? There are many different definitions, personally I prefer to define knowledge mining as the possibility to extract valuable insights from existing information. This previously unknown information consists mostly of (large data) sets in multiple sources.
Many organisations produce a lot of documents or have a huge archive, where they manually have to search through. Reported by Harvard Business Review, 82% of the companies mention that exploring and understanding their unstructured data in a timely way is a significant challenge. Examples of unstructured data are scanned pdfs, images and audio files. Formats which are hard to consume and most of the time they are also spread across multiple systems...
68% believe knowledge mining is important to achieving their companies' strategic goals in the next 18 months. (source: Harvard Business Review)
Spotting the opportunity
Knowledge is power! A good knowledge mining solution saves money for the company by reducing time employees are searching for business-critical information, automating redundant tasks, and eliminating the need for teams to process unstructured data.
The opportunity and the value you can bring to your customer is huge, so why doesn't every company make use of it yet? Every company has hundreds of documents saved somewhere, right?
Knowledge mining is a difficult topic, since the value of a knowledge mining solution ties to the use-case, which is most of the time very industry specific. Just deploying a default search engine on top of all their documents could already enhance the experience, but in order to make it a game changer, you will need a solution that solves a business case for a particular industry.
Does your customer have a lot of unstructured data, spread across the company? Get the conversation started around their current pain points and see if they can benefit from a knowledge mining solution. Let's start with some real world customer cases in three key industries to give you a better understanding of the scenarios.
Financial Services & Insurance
Contracts contain some of the most important information in business relationships, but their complexity has limited the ability to search and learn from them. Icertis is changing that with its Icertis Contract Management (ICM) platform enhanced with cognitive search, a recent capability of Microsoft Azure Search. With this capability, ICM customers can use AI-infused search to easily uncover hidden insights in contracts. This reduces time in contract negotiations, lowers risk, improves contract compliance, and increases revenue. read more
The healthcare industry is drowning in data — but much of it is siloed, hampering scientific breakthroughs and driving up research costs. Vivli is an independent, nonprofit organization that partnered with Insight and Microsoft to create an innovative, global data-sharing and analytics platform for clinical research. Working together, they successfully created a robust platform, powered by Microsoft Azure, to share and analyze clinical data among academia, healthcare organizations, and the pharmaceutical industry across the globe. read more
Manufacturing / Oil & Gas
With a history steeped in Dutch shipbuilding since the seventeenth century, Royal IHC designs, builds, and services complex vessels and equipment for the offshore, dredging, and wet mining markets. Its customers’ projects are hugely complex, and downtime can have a big impact. To relieve its engineers from time-consuming manual data searches across disparate sources, Royal IHC sought an AI-assisted solution. The company now uses Microsoft Azure Cognitive Search to search more than a million documents in under two seconds, speeding time to resolution and improving its customers’ experience. read more
Need more inspiration? Have a look at https://aka.ms/ocp-we/knowledge-mining, with scenarios in retail, media, oil and gas, legal, financial services and manufacturing.
Looking forward to learn more about this technology? Next week I will tell you more about the technology and the skills required to start building knowledge mining solutions. Any topics you would like me to cover in this series or do you want to brainstorm about possible solutions? Let me know in the comments!