Modern Intranet Metadata And AI

Why A Modern Intranet Needs High-Quality Metadata And How AI can Help

A modern intranet will be at the core of a digital workplace. And search is arguably the most important feature of any intranet. But for any intranet search to succeed, it needs to have two critical components: good quality taxonomy and metadata. In this article we’ll understand the reasons behind this and how Artificial Intelligence (AI) technologies can help in metadata management and enable an intelligent and powerful search for your employees.

Decision Making In Your Organization Is Dependent On Search

The importance of search in the digital workplace can’t be overstated. Knowledge workers consume and create massive amounts of content every day. They need to find the needed documents faster to take timely business-critical decisions.

However in most organizations, search lacks good user experience and provides duplicate or obsolete results, leading to employee frustration.

Knowledge workers spend an average of 2.5 hours every week finding the information they need within their enterprises, says an IDC report.

Consequently, they resort to workarounds like asking colleagues to find specific information instead of using the intranet search. At times, they find it easier to recreate a document than trying to find the original one – leading to duplicate information.

Search Doesn’t Understand What People Want

A common criticism about most enterprise intranet search solutions is that they don’t understand users’ intent. But the fact of the matter is that these solutions don’t have the capability to understand in the first place.  In order for search to be successful and deliver relevant results, it must be equipped with several supporting technologies like text analytics, metadata, taxonomies generated by humans, classifiers, tagging and many more.

But the most important thing to consider is optimizing the content for search. This starts as soon as an employee creates a new document. Every new information that is being saved must follow particular guidelines and have the right metadata. This means all these guidelines, best practices, governance rules, metadata and taxonomy definitions must be established and users need to be aware of them.

What is Metadata?

Metadata can be described as the ‘information about information’. It contains details about a particular document, page or profile. Metadata usually involves a title, keywords and description which need to be filled. It improves the quality of search results and helps promote the right and relevant content to the top of the search results.

Why High-Quality Metadata and Taxonomy Are Needed

Having the right information architecture and metadata enables users to find and access the right content swiftly. Lack of good quality metadata reduces the usefulness of search.

Without an effective search, an intranet will just be a glorified shared repository with random files. The number of duplicate files will increase exponentially. And you’ll find yourself creating a bottomless pit of dark data and content silos. This not only results in under utilization of data but also non-compliance risks.

Many organizations also face the issue of inaccurate and inconsistent metadata. This is usually because no two users read, comprehend, and describe the documents in the same way. Bad metadata makes information findability even more difficult. Inconsistent metadata is messy and hard to correct.

Challenges With Manual Metadata Management

Knowledge Mining Are Expensive And Error Prone
Organizations usually deploy “metadata owners” or taxonomists to manage metadata. These users create and maintain metadata in the organization’s knowledge management system. Very well, then, what is the challenge, you may wonder! The challenge is the very process of users associating metadata with the documents. This process is not only costly but also depends on the ability of humans to read and describe the documents accurately. A Hoover’s report estimates that the average cost of manually tagging one item runs from $4 to $7. And this doesn’t not even take into account the fact that this human-heavy process is error-prone, and often results in mis-tagged content. IDC estimates that it costs you $180 to recreate a document that is not tagged correctly and can’t be found. This translates to millions of dollars for a large enterprise. With the growing volumes of unstructured data, this approach also poses scalability challenges. The approach is time-consuming as well. By the time, the information is identified and classified, it loses its value and is fit for only archiving.

How AI Can Help

With the rise of Artificial Intelligence (AI), manual tasks involved in metadata management can now be automated. AI bots can crawl through your documents, understand them, generate metadata, classify and tag them automatically. The process will be highly accurate, cost-effective and extremely fast. Consequently, your documents become easily discoverable through enterprise search.

Since the same bot interprets all your content there will be consistency in the document classification process. AI bots not only tag your documents but also transforms your taxonomy into a living and breathing entity that automatically evolves along with your enterprise.

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Acuvate’s  Mesh 3.0 – World’s First Autonomous Intranet built on SharePoint is equipped with powerful AI-powered knowledge mining features and delivers super powerful search experiences for users. Mesh is built with the best of Microsoft AI solutions and leverages Azure Cognitive services. Mesh’s Cognitive Search feature connects all your third party enterprise apps together and acts as a one-stop search in your organization.

If you’d like to learn more about this topic, please feel free to get in touch with one of our AI and digital workplace consultants for a personalized consultation.

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