Recognising corporate information assets

Organisations today do not maximise their most valuable competitive advantage - intellectual capital. Spread across the organisation in intranets, relational databases, file systems, new and legacy business applications, much of the intellectual capital produced and stored as content eludes attempts to manage it and use it as a competitive advantage.

Part of the problem is the fact that 80% of enterprise information is "unstructured" information in the form of documents, spreadsheets, presentations and Web pages. Unlike the 20% of enterprise information that resides in well-managed databases, most companies don`t even know how much unstructured intellectual capital they have, who`s creating it or who`s using it.

To cope with the deluge of information, businesses typically implement one or more of three solutions: portals, content management systems, and/or packaged business applications. And all too often, the resulting "solutions" actually lower the value of the intellectual capital in a number of ways.

Firstly, portals with difficult navigation and inadequate search facilities create single points of access that make information more difficult to locate and reuse. Secondly, content management systems tag documents from the perspective of the people who created them - not the people who actually use them - impeding access to content and lowering productivity with excessive process. Finally, packaged business applications implemented in isolation create impenetrable information silos instead of breaking them down.

Meta Group says organisations are often unsure which vendors to turn to, how much technology is required to get the job done, and what its costs will be. This is exacerbated by the confluence of requirements from various business units representing internal and external users and usage, says the research house.

This is where data discovery comes in. To make sure the right solution is selected, a data discovery programme can help find the answers to a number of not-so-simple questions, among them: Who creates and uses the organisation`s information? What type of information does the company have? What file formats? How many files? When was the information created? Is it still valuable or is it obsolete? How valuable is it? Where do these files reside? Are there duplicate applications with duplicate files? Why does the company need to manage its unstructured information? What are the business objectives?

Data discovery is designed to identify and access intellectual capital, to understand its value to the business.

Garth Wittles, district manager, Verity

Data discovery is designed to identify and access intellectual capital, to understand its value to the business. It gives a clear picture of the assets that make up the firm`s intellectual capital. Armed with this knowledge, companies can better evaluate alternatives and implement the best intellectual capital management solution to ensure business objectives are achieved.

In addition, a data discovery programme will provide insights into previously unknown areas of expertise; areas in which more knowledge must be captured in order to remain competitive; and who the domain experts are in the organisation.

The benefits of data discovery include more effective intellectual capital management solutions that are tailored to specific information environment and business objectives; more efficient use of the human and capital resources allocated to intellectual capital management initiatives; better software selection; shorter implementation cycles; faster and higher ROI; decreased software licence costs; decreased hardware costs; and decreased total cost of ownership.

A data discovery programme should involve the entire internal team - from technical staff to end-users - to ensure the company has all the information needed to map out the best solution to meet specific business objectives. A number of steps should be included in the data discovery journey:

1. Identify information requirements and assets
Start by working with business-unit owners and end-users to gain an understanding of the types of information important to the organisation`s business objectives (financial data, customer records, or R&D documents). Also identify the content sources that contain this information (Web content, Microsoft Office documents, structured or relational data, scanned documents checked into a document management system). Finally, locate the known repositories in which the content is stored (Web servers; document/content management systems; CRM or ERP environments, e-mail servers; file or archival systems).

This first step forms the foundation on which the following steps are based. In order to optimise knowledge assets, it important to first understand the information and content environment and how it relates to the business.

2. Locate and evaluate information assets
Once companies understand how various types of information are used within the organisation, the next step is locating and evaluating that information. This step involves using spider and indexing technology to "crawl" all of the repositories and index the content residing within them. Once indexed, the content can be thoroughly evaluated. Comprehensive reports can then be tailored to the company`s business requirements and information environment. These reports can include parameters such as the number of files, total size, average file size, file types and the number of duplicate files. This deliverable becomes a valuable tool when it comes to determining intellectual capital management technology requirements.

3. Map information to company-specific taxonomies
In the mapping phase, the data discovery programme should focus on extracting concepts found within the information sources that were identified and analysed in the previous step. These information assets can then be mapped to top-level categories that represent discrete concepts or areas of knowledge within the company. For example, the process of thematic mapping may expose - and map information to - categories such as communications, corporate administration, or legal. This gives an understanding of what knowledge and expertise are represented by information assets. Often, companies are surprised to discover areas in which they have a previously unknown wealth of information, or in which they are in need of broader or deeper knowledge to remain competitive.

4. Cleanse information sources
At the end of the first three steps, companies will have a clear understanding of the current state and quality of their information in terms of duplication, redundancy and latency. Based on this, they can then determine the best way to cleanse repositories. This involves removing duplicates and archiving outdated information and/or information that is no longer of value. For example, in some cases each revision of a document must be kept for legal reasons, while in others only final versions are required. Depending on the eventual intellectual capital management solution, the process of cleansing can significantly reduce software licence fees and hardware costs. Or, if unstructured information would benefit from structured organisation at this point, the best meta-tagging solution for the environment will be identified. This may be a content management system or an automatic classification solution.

5. Connect people to the right information
The final step of the data discovery programme is to connect cleansed and structured information sources to the right people. To do this, information must be integrated with the top-level categories defined in the mapping stage. At this final stage, it is possible to obtain a detailed description of the lifecycle of intellectual capital within the company. This is crucial to ensuring that new content is accurately mapped to the correct categories as it is introduced to the system, tagged and delivered to end-users.

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