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Accelerating Your Journey to Knowledge Management

Accelerating Your Journey to Knowledge Management

It’s not a new idea for businesses to use their knowledge to gain a competitive edge. But the bigger they get, the more dispersed that know-how becomes. Technology has taken us some way towards storing and managing that intellectual capital, but all too often employees can’t readily access the knowledge they want. Now, AI (Artificial Intelligence) promises to provide the answer. If, but only if, you’ve got the right foundations in place first.

Document, Information, and Knowledge Management overlap, but all have distinct meanings, and differ in their scope. However, if we strip things right back, beneath each is a simple idea. Businesses that successfully use their, and their people’s, collective know-how will make better choices, quicker, and with less effort. In short, they achieve competitive advantage.

Pooling and managing this know-how, making it accessible, and improving collaboration and workflows has fallen to IT. Some might say, a little unfairly. Simple though the underlying idea is, it has proved far from simple in execution – with reality regularly falling short of the vision.

Before looking at why, and how this can be resolved its worth defining the terminology of the journey from Document, to Information, to Knowledge Management.

Defining Document Management, Information Management, and Knowledge Management

While Document Management deals specifically with documents (there’s a clue in the name!), Information Management takes this further. Documents are typically structured, tangible items such as text files, spreadsheets, presentations, and images. While information encompasses a wider range of structured and unstructured assets, regardless of format or medium – including documents, data, records, multimedia content, and more. Knowledge Management aims to take this a step further. Adding expertise, insights, and experiences to the explicit knowledge held in documented procedures, best practices, and lessons learned.

With Document Management, the emphasis is more about the organisation, storage, and control of the assets held. While as we progress through Information and Knowledge Management, the emphasis on collaborating to improve organisational performance increases.

Regardless of where on you are on the journey from Document to Knowledge Management, the end goal must be delivering on the vision of improving competitiveness. But for most businesses there are two huge hurdles to overcome first.

Twin Challenges: Search and Silos

While IT has provided effective repositories for data (documents, information and even knowledge), retrieval hasn’t always been easy. Many systems rely on employees knowing what they’re looking for, where its stored, and what it’s called. Very often they don’t, and search functions fail to provide them with what they really want.

Added to this, businesses have traditionally stored relevant information across several systems. We regularly encounter businesses with data assets partly in the cloud and partly in legacy, on-premise systems. Although these are systems that could be moved to the cloud but haven’t been. It’s a mixture of not knowing how, ‘if it aint broke don’t fix it’, and project scope creep.

Worse still, in many legacy systems every part of the business is maintaining a separate knowledge repository. Enabling teams in different areas to work on similar projects, with similar challenges, and to separately address similar challenges. Wasting time and effort, and potentially missing out on better solutions. In another case, teams in different countries filed competing patent applications within a couple of weeks of each other.

To date, data silos have been the enemy of effective search, retrieval, and collaboration.

But that could be about to change.

How AI can enhance Knowledge Management

AI offers IT the promise of revolutionising the way data is organised, found, and leveraged as valuable knowledge. We’ll look at these three aspects in turn.

No doubt you already know that AI can process and manage enormous amount of data. This power can be used to make the huge task of centralising and organising separate data sources manageable and achievable. Eradicating troublesome data silos. You can read here how Microsoft Syntex (soon to be SharePoint Premium) can help you to achieve this.

Unlike traditional keyword-based searches, AI combines natural language processing (NLP), semantic search, and machine learning to provide more targeted results. This should make it much easier for employees to tap into existing know-how.

Thirdly, add in AI’s ability to add context based on an employee’s role, department, and previous interactions. This is where the output becomes the actionable knowledge that really delivers performance benefits.

If we think about a staff member commencing a new project. Traditionally, they might be given a project overview to look at or be provided with some background information from one or two people. AI can generate much more extensive insights: reviewing all sources, finding forgotten information, and combining the learnings and conclusions from a multitude of past projects.

Generative AI’s capability to provide fully formed answers to a question can take this even further. But AI is only as good as the data it has access to.

Because . . . rubbish in, equals rubbish out

The more accurate, up-to-date, and well-organised the data AI is accessing, the more accurate, up-to-date, and useful its output will be. There’s more on organising your data here.

So rather than AI, and for that matter machine learning, making knowledge management redundant it is making effective knowledge management more important than ever before.

Achieving Effective Knowledge Management

Regardless of where you currently sit on the Information to Knowledge Management spectrum, your goal should be clear. Enabling your business to make better decisions, faster.

Important though they are, this isn’t just about providing a repository for documents and information, but also about capturing experience and know-how. It also means consolidating your data, preferably in one place. Ensuring that its well-organised, well-managed, and up-to-date, with the right permissions, security and governance.

And all of this can be achieved with SharePoint. Providing a single, consolidated, knowledge repository, and an Information Architecture attuned to your future needs. It’s thoroughly integrated into your Microsoft infrastructure, with the power of Microsoft enabling your business to make best use of AI.

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