Rich data is about finding information faster

In our previous post, we already said that companies with advanced analytics make better decisions, take them faster and execute them better, leading to better results and value. This is only possible if we manage to convert raw data. Because as long as the larger part of information remains unstructured, rich also means poor information. If it isn’t smart, it’s not usable. On average office workers spend 1.5 hours a day looking for information. In 42% of the cases they get their answer from colleagues and not from information systems. People don’t find information, remain uninformed and there’s no value to grab.

‘Meta’ data management on common definitions

How do we structure the unstructured? “Data classification is one of the most crucial elements of an effective information governance process—yet it’s also one that many companies fail to implement well. Our brain uses cognitive tags, absorbing information that is linked to your personal status. So everyone has different ways of working or interpretations. To structure your unstructured data, you need to agree upon common definitions in your organisation. Data management becomes meta data management. Agree on meta tags to add to content automatically, because people don’t do it themselves”, explained Hans van Heghe, the Managing Director of Knowliah, at our latest CIO Global Perspectives.


On average office workers spend 1.5 hours a day looking for information.

That common contextual enrichment allows organisations to search through a meta data lake above all its information sources, via so-called context facet filters. “By that we are able to collect intelligence from different sources without human intervention. The challenge is not about searching, it is about detecting a context the collaborator is working on, map it to your context model and present relevant information to him automatically”, said van Heghe. “Rich data is about finding information faster and creating a 360° view for the business user.”


Three of Knowliah’s recent data classification projects:

1. For a certification agency it is presenting, after storing and autoclassifying e-mails, reports and so on, the right information to the claims handler for every step in the claims management process.
2. For a construction company, it is processing all the e-mails and construction site reports, autoclassifying them on risk elements linked to construction. If there certain profile of risk, a project manager is notified and for estimated severity top management too.
3. For Doctors without Borders it analysed 1 million e-mails and 300,000 reports on the three-year Ebola crisis. Based upon a context model of 45 families of tags, the e-mails and reports were auto-classified and the organisation was then able to analyse the subcollections, and write wiki recommendations, adapt processes and procedures, and so on. Rich data can save lives…