Understanding the Hierarchy of Information Needs - Page 2

Oct 24, 2006

Majid Abai

Having seen this shift, it becomes paramount for IT to recognize the hierarchy of information needs as they plan their long-term strategy of focusing on information and not applications.

So, what are the five levels of an organization’s information needs?

Level 1 – Communication Needs: At this level, an organization needs to communicate internally and externally, and have the ability to capture and disseminate this type of information.

In today’s world, this need is satisfied by emails, electronic documents (such as word processing or spreadsheet documents), and websites that act as brochure-ware for a company.

Level 2 – Operational Needs: At this level, an organization utilizes information as a vehicle for running and/or managing its operations and finances.

Such information includes information about sales, costs, and the ability for some companies to sell, buy, or operate through Web (such as e-commerce sites); practice management systems, accounting systems, enterprise resource planning systems, customer relationship management systems, supplier management systems, etc. all provide information that supports operation and finances of the organization.

Level 3 – Analytical Needs: Analytical needs are focused on when operational needs have been satisfied. Such needs require organizations to deliver information that provides insight into patterns and trends that go beyond information contained in one silo or subject area.

Information needed to perform analytical needs could be stored internal to the organization or externally (by information brokerage companies). This type of information normally results in higher sales, reduced costs, better customer service, or improved operations.

Level 4 – Knowledge Needs: Organizations are starting to recognize the value of hidden information within their documents. So far, most of data utilized within systems has been in structured format: relational or hierarchical databases.

IBM considers structured data to be only 15% of the total data in organizations. This means that over 85% of information in organizations is stored in documents, spreadsheets, emails, audio, video, photographs, and other formats. In addition, there is tons of information about the organization, its products or services, and its people on the Web in the format of websites, blogs, chat rooms, etc.

At this level, organizations are starting to unleash the power of such information. They are empowering their employees to access it in order to make better decisions for the organization.

Level 5 –Simplification Needs: At this level, organizations start to review the internal landscape and move from a silo-mode into an enterprise-information-management model in order to simplify the information landscape.

They will start to consolidate redundant and similar systems, implement information quality techniques for cleansing information, utilize re-useable enterprise-level appliances to deliver reliable information to all users, and maintain governance around each subject area of information.

As a result, information will be delivered as a consistent, clean, and timely asset to any and all who need it and have the right to utilize it. At this level, information is documented, managed, and available as water or electricity is in each of our households. None of us need to know the source of the utility as long as it is available, clean, consistent, and timely.

In conclusion, I’d like to add that in a large enterprise, some departments might be ahead of others from stand point of their information needs. Some could be more advanced (Level 3 or 4) while others are struggling to jump from Level 2 to Level 3. Smaller organizations, on the other hand, tend to remain within Levels 1 and 2 and seldom jump into Levels 3 or 4.

Majid Abai is president and CEO of Seena Technologies, an enterprise information management and architecture consulting firm. Majid co-authored Data Strategy (Addison-Wesley, 2005) and teaches classes in Business Intelligence and Enterprise Data Architecture at UCLA.

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