Matt Shearer, CPO of Data Language, discusses how knowledge graphs can bolster organisations’ content reach and engagement
Since the advent of the internet, publishers have had their business models upended by the sheer pace of change. Some have acted quickly to adapt to the digital world, but many are struggling to keep up with the flux of digital publishing processes, and the move from a document-centric landscape to a data-led one. They may understand the challenges facing them in a competitive and disruptive world, but many publishers remain unsure how to unlock the value of their content to improve reach and engagement.
Publishers with strong subscription bases should be in a strong position to track and measure content consumption patterns and to provide well-informed customisation and tailored experiences for their customers. However, many of them are not able to truly leverage this because they do not maintain a single view of the important subject data in their knowledge estate. This can be described as a ‘Single Subject View’ — similar to the concept of a Single Customer View — and is applied to the view of the things that are important within the publisher’s content — their core knowledge assets. A lack of a Single Subject View prevents publishers from giving their subscribers the content that interests them, at a time when their intent is at its highest.
Many publishers are looking to knowledge management as a tool to reach and engage audiences. Efficient knowledge management speeds up the publishing cycle and improves content intelligence by removing duplication, and enabling a Single Subject View across a publisher’s entire content estate. This also enables more rapid innovation, as it makes it easier for a publisher to launch new ways of presenting the content, without having to rework the knowledge foundations.
Here are three best practices to achieve effective knowledge management:
Create a shared ‘living ‘map’ of the business
Like other areas of digital transformation, best practice information management is best informed by developing a living ‘map’ and shared vision of your organisation’s data landscape. Many use a ‘domain model’ — a conceptual model that incorporates both the important elements of your business and, crucially, how they relate to one another. Collectively understanding what challenges need to be resolved and which gaps need to be filled, will help you prioritise the next steps. Involve your employees in this; spend some time and tease the information you need out of them — they may not understand the importance of the information they hold. The value locked in their heads is a large part of your core business advantage and something that will be more challenging to access if people aren’t always together in the office.
Develop an information backbone
One fundamentally important element that is so often neglected in favour of deploying exciting new technology is a strong information backbone. Once you have established your shared map, the next step is to move this into use so that your staff and systems can connect the valuable information across your business processes. This is commonly referred to as ‘information architecture’. This crucial work is required to enable data portability and interoperability — the ability to use and move core business data between different applications. Without data portability, it is challenging to connect assets across company silos, which is critical to quickly adapt to changing market conditions. As organisations store growing quantities of data and move data from one use case to another, they need to have their information assets in portable, structured formats that can be repurposed quickly to help them adapt.
Utilise knowledge graph technology
A particularly powerful way to structure your information backbone is to use a knowledge graph. They are fast becoming an integral part of organisations’ data landscapes as they provide a human and machine-readable database of all the things of interest to the enterprise in their domain. Using a knowledge graph, a single metadata allocation on one piece of information could then be used to connect that information with other groupings and contexts automatically, even several logical steps from that original piece of metadata. Truly agile organisations will increasingly use knowledge graphs to enable more devolved innovation.
Smart knowledge management is a worthy undertaking as part of the journey to drive increased efficiency and reach maximum audience engagement. It is crucial to consider elements such as a well thought out strategy and portable knowledge assets because, without these aspects, a publisher’s data strategy will not be set up for ongoing success.
Related:
Mastering migration: top tips for reining in content sprawl — Neil Jones, director of cyber security evangelism at Egnyte, discusses how organisations can rein in content sprawl to master data migration.
Why CIOs are turning to knowledge graphs for critical business help — Maya Natarajan, senior director, knowledge graphs at Neo4j, delves into why CIOs are looking to knowledge graph capabilities for critical business help.
