Information Valuation: Reinvention of Knowledge Management or is there more to it?

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Recently, the term Information Valuation popped-up in various leading industry reports and in a few blogs, but the term is so new, there isn’t even a Wikipedia entry for it yet (as of June 11th, 2010)! The term does however make a lot of sense and it made me think: it is this just a new term for Knowledge Management or is there more to it and should we worry about it? Because, isn’t Knowledge Management all about valuating, organizing, categorizing, sharing and reusing information? Wikipedia defines Knowledge Management (KM) as comprising a range of strategies and practices used in an organization to identify, create, represent, distribute, and enable adoption of insights and experiences. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organizational processes or practice. Apparently, KM has been an established discipline since 1991 and many large companies and non-profit organizations have resources dedicated to internal KM efforts, often as a part of their 'business strategy', 'information technology', or 'human resource management' departments. My take is that Information Valuation is not just another word for Knowledge Management. It is the bridge between records management, retention, information governance and eDiscovery on the one side and knowledge management on the other one. Let me explain this in more detail. Knowledge management is not possible if your data is no more than an unstructured data-dump. We cannot ignore the fact that we live in an information society and that all of today’s workers are information or knowledge workers. Information is one of the most valuable assets of many organizations and next to financial information; there is a lot more additional unstructured and multi-media information that is just as important to determine what is really going on. I believe this is a major difference with the past where information was a derivative of some kind of physical production process, nowadays, information is the main product. All this information needs to be managed, from the personal to the departmental and enterprise level. Information needs to be accessible, there need to be information archiving policies based on information governance rules and legacy information needs to be cleaned up for both legal reasons, but also to prevent that the ongoing information explosion covers and hides all valuable information with irrelevant information and data. This is where the relevance of periodic data valuation comes in. Next to normal regulatory efforts to implement information retention, transfer and destruction, we also need to valuate, categorize, enrich and disclose our information to help knowledge workers to be as productive as possible. This is also where text-mining and content-analytics can play a great future role: there is so much information out there, that it is almost impossible to classify and valuate it all manually. By using text-mining and content-analytics, information can be tagged with relevant information automatically. These tags can then be used to classify documents automatically into folders, to create facets for search and to link and organize information intelligently. By making information valuation part of a records and retention policy, relevant information can be identified, modified (for instance redact if needed or generalized by specialist) and then shared into the user community for future knowledge sharing to increase effectiveness, productivity, optimize business processes and prevent future errors. This is why Information Valuation is not just another word for Knowledge Management. It is the link between and an essential component of records management, retention, information governance, eDiscovery and knowledge management!
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Phil Ayres

Johannes, I like some of your thoughts.

I am concerned that having text / content analytics classifying information that falls into a corporate records scheme. It feels like all this new information could dilute the value of transactional records if you're not careful. For example, if I'm working with a financial services firm, their view of corporate records is limited to the information that backs up the clients, transactions, brokers, licensing and so on that the regulators want to see evidence of. The research, discussions and innovation that is going around the core business (which could benefit from Information Valuation) are documents for analysts, but from a record-retention standpoint are explicitly excluded from being treated as corporate records, instead being treated as working documents. Perhaps Information Valuation can help me persuade this firm that they really need to destroy these documents routinely.

I see so much of the value of content analytics being applied to transient content - information that is relevant for only a very short period of time. Having technology organize it and highlight it while it is still relevant is where the real value lies. Destroy it soon after so it doesn't become a distracting corporate record.

In your new wikipedia entry for Information Valuation, I'd consider adding the concept of ageing. Not an original idea I know, but one that is easy to overlook when your doing a one-hit analysis of content for valuation.

Nice post!

Phil
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Swinitha Nawana

Very interesting. New knowledge is the product of evaluating, analysing and using information. i.e. from data to information and then knowledge.Todays knowledge is tomorrows information and people use information, share information and then they become knowlegeable and come up with new ways of applying them(New Knowledge).

Records, and documents contain information and technology provides the medium to transfer and store information in different forms. It is the individual who turns it in to knowledge and may be gain visdom from it.
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Johannes Scholtes

Hello Phil, I fully agree with your concerns. Two quick additions to my views:

1. I am a huge fan of content analytics for many different applications, such as eDiscovery, Records Management and Enterprise Information Archiving in general. But in all cases, there should be a human verification of the automatic process based on random sampling to make sure that the automatic process performs at least as good as a human process would.

2. Content analytics would primarily add additional information that is used for the knowledge management part. The core records management components and transition schemes can best be assigned when a document is created. Should content analytics be used determining the location of a document in a records management filing plan, then that will probably only be the case with a legacy (non categorized) information clean-up. In such a case human classification is often too expensive and also not always consistent. Content analytics can help, but here too, there needs to be human valuation of the quality of the content analytics.

Thanks for the feedback!


Johannes
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Rich Blank

While there are still KM projects in the traditional sense (e.g. a pharmaceutical online research library).....I'd also add that many organizations seem to view KM initiatives today as a solution that combines both structured data with unstructured content together into one aggregated & searchable online workspace (e.g. a portal, team site, dashboard, community). For example, in customer support or sales proposal development or an IT PMO/project management....you have data and you have content and it seems organizations are seeking ways to achieve productivity gains and "business analytics" (not necessarily just content analytics)........and they're looking for increased & flexible responsiveness to internal and external customers) through KM initiatives like this.
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Hi, As a META Group (now Gartner) analyst about 11 years ago I started working on valuation models for information assets and consulting to organizations on this. These models have since been refined. There are a variety of ways to compute the value of an information asset.
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