Almost everybody hates filling out forms. That’s why you write a note instead. You send an email or text. You record an audio message. You create a video.
You communicate in an unstructured, humanized way.
Unlike metadata in forms, which are structured, these other methods of communication are unstructured. Unstructured data lacks metadata, and semi-structured information has limited metadata.
The real value of unstructured data like an email, for example, is in the body of that email. You and I can often make sense of an email and other semi-structured and unstructured information. However, for a company, and for search, understanding the essence of a message is not that easy.
With the right approach and technology, however, you can mine that gold — eliminating waste, improving experiences and surfacing new opportunities to win and become more competitive.
Leverage Existing Structure To Address Lack Of Structure
You need to connect the silos in your enterprise to gain value from all your information. To get started, use the structure that already exists to extract value from the unstructured.
Here’s an example of how this can work. Your business probably has an Active Directory or any other directory service in place. When Terry logs into your enterprise, that directory knows who Terry is. The directory’s metadata also helps it understand other details about Terry, such as Terry’s department. This indexed directory doesn’t have to guess, and you don’t struggle with accuracy problems.
You can also leverage this resource and many more of that kind to understand that Terry is also mentioned in an unstructured document and that it’s the same Terry. It immediately knows with almost 100% accuracy that Terry is mentioned in this document. This works in the same way for tons of other data.
Let’s say you have a product or component list. Your company works with partners or subcontractors, and you have customer contacts. All that information is typically structured. If you employ a machine learning model, you can employ that structure to connect the dots of those customers, partners and subcontractors mentioned in other communications. That can help you gain a 360-degree view of these relationships and determine how to optimize them.
This enables you to be more intelligent as an organization. For example, you can now see that a high-value customer nearing the end of his contract has emailed you asking for help. Understanding the full scope of the situation can enable you to identify and prioritize this opportunity to connect with the customer at this pivotal time and provide expert assistance.
Use Intelligent Tools To Understand Usage And Clean Your Data
To enable efficient knowledge management, you’ll also want to clean your data.
The data in your organization is akin to the possessions in your home. Much of it may be old and possibly outdated. It may even be wrong. You need to clean your data to address that wrong information that can lead to inaccurate conclusions and actions at your enterprise.
Use the tools in insight engines and enterprise search to clean up your information ecosystem. Employ these tools to understand what data your people are and are not using, and leverage these tools to compare frequently used data to information in old, seldom-used documents. Old documents might contain different messages — or opposite meanings — than current data.
Data cleansing will enable you to get rid of that data — or at least assign it a lower rating. The latter will ensure the data doesn’t appear in top results when employees search for data.
Know That Migration Alone Does Not Create Transformation
One of the worst mistakes that organizations make is thinking that data migration enables business transformation. That’s just plain wrong. Yet I see it happen again and again.
Here’s a typical scenario. An organization uses one CMS. Its CMS system does the job, yet the organization targets it for migration. The organization does the project without changing its workflow and without identifying any transformational business benefit that will originate from that migration. Many organizations love to migrate from one data silo to the next or to consolidate, but that alone doesn’t do the job for enterprise users, and plain migration alone doesn’t lead to business transformation at all.
Before you migrate your data from one silo to another yet again, consider why you’re doing it. Such exercises are cost- and resource-intensive, and they alone do not deliver any enterprise user knowledge management benefits — which is what your business needs to be more effective.
See What’s Possible And Make It Happen
When you focus your time and resources on adopting technology that allows you to analyze and visualize all your data, you can understand relationships that you didn’t know existed.
This is valuable whether you’re trying to develop a vaccine to prevent Covid-19, find solutions to address climate change, better compete with industry disruptors or become a disruptor.
Technology is changing everything — including how consumers purchase goods, how supply chains work and how products are created. Consider 3D printers, which enable anybody to generate a prototype. They are disrupting new product design and the $12 trillion manufacturing industry.
Knowledge management and insight engines can provide similar power to knowledge workers.
Consider how your organization and the people in it can benefit from the power of artificial intelligence and knowledge management. Think about how you can do things differently by using and connecting all of your enterprise data. Use AI and knowledge management to visualize what’s happening and what’s possible in your business, your relationships and your market, and use that understanding and intelligence to build something transformative.