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    IDC’s research report on knowledge workers and information findability is often quoted when people are trying to build the business case for information management initiatives.  The study showed that the average knowledge worker spent almost 9 hours per week searching for information and another 8 hours analyzing it. The report ascribed a dollar value to the difficulty or inability to find information. The recent update similarly established a cost of $5.7 million annually to a firm with 1,000 “knowledge workers” who searched for (but could not find) information they needed.

    While these are reasonable arguments to make, they rarely hold sway over a savvy executive, and are typically cited in funding requests to bolster the arguments for funding rather than operate at the core of the argument.  The “time wasted in searching” method for business justification has several limitations.

    1. It is difficult to quantify across the enterprise
    2. It is difficult to establish a linkage to specific business value
    3. Incremental improvements are not meaningful when prioritizing limited resources
    4. Incremental savings of time do not necessarily translate into value producing activities

    The Enterprise Perspective

    When speaking about “the enterprise,” I frequently quote a colleague who said, “There is no budget for the common good.”  Though an information management project can and should broadly impact the organization, the cumulative impact on diverse processes and activities cannot be measured easily. 

    “There is no budget for the common good.”

    A project such as improved search may have enterprise wide impact; however, search is about finding specific answers to specific questions. It requires definition and characterization of a target audience and specific changes to the content they search for. The changes may include structuring or editing the content and vetting and clean-up of content sources.  When attacking an enterprise problem, a focus on specific kinds of users and their particular data and content needs through task analysis, use case and scenarios is required in order to be successful.

    Linkage to value  

    Similarly, value needs to be defined in the context of a process.  The improvement may very well be time savings or greater levels of efficiency; however, specific baselines focus on tasks and processes that can be impacted. An enterprise approach has to be broken down into projects and processes that can be defined in terms of interventions and outcomes.  Even in situations where large-scale transformation requires new technologies and long time frames, quick wins can be achieved that demonstrate value and help people understand the purpose of a program. In some circumstances, no clear or quick wins are apparent, and all of the outcomes are incremental. It is still important to document baselines and incremental improvements.   Those incremental changes can have a collective impact that is significantly greater than their sum of each of the contributions, but each of the contributions can still tell a compelling story.

    Resource prioritization

    These incremental improvements need to be documented, but they may not stand up to a program review committee evaluating candidate projects for investment.  It really depends on positioning.  If the incremental benefit is described in generic terms (“each person will save 12 minutes per day x 5 days x 1,000 people x $50/hr loaded costs = $50,000 per week”), it will not hold up under scrutiny because there is no way to monetize (or track) that benefit.  If on the other hand, the time savings is tied to a discrete process that has associated metrics (call centers are an obvious example), that time savings argument will be easier to defend.

    Value-producing activities

    Giving people an extra 12 minutes per day could mean they get more useful work done, or it could mean more time on unproductive e-mail. The extra time rarely leads to head count reduction.  Small time savings for a call center or field service organization with large headcount could very well translate into reduced head count or slower head count growth as the business grows since there is a direct correlation with measured productivity. The impact of global efficiency gains is more difficult to justify in a business case. The ability to respond more quickly to a change in the marketplace or the ability to get products to market more quickly may not be easily measured or directly correlated, but they are end results of improvements in information access.  

    Under-acknowledged content

    According to IDC, even though 90% of all information is unstructured organizations have underinvested in unstructured information management. Enterprise-wide information management initiatives have been relegated to corners of the IT organization and typically make do with small budgets for deployment and whatever money is left over from large structured data programs such as SAP.  After deployment, little provision is made for for core architecture, change management, or ongoing governance. 

    This approach appears to be changing, however.  More enterprises are realizing that digital capability entails much more than an e-commerce site.  Customer interactions are increasingly online, even for organizations that did not consider digital channels viable for their business models.  For customer interactions to be digitized, upstream processes need to have the same efficiencies as customer facing systems and have faster clock speeds to keep up with customer demands. Customer engagement begins long before a customer purchases a product or sets foot in a store.

    Engagement through digital channels requires that internal expertise be exposed to the customer in multiple contexts and through multiple channels.  Marketing helps to inform and educate prospects, sales, service, support and billing handle later stages of the lifecycle.  Each process requires efficient management of content and data.   Business-to-business organizations are beginning to realize that if information management of supporting processes is not effective, missing data means that products are invisible on distributors’ web sites. Where does that data come from? It  typically begins its life in unstructured engineering or design documents.

    These are just a few examples of the implications of poor unstructured information management.  When internal processes get bogged down because of poor findability, customer-facing processes can break down. 

    Board-level funding of projects requires a very strong business case.  The organization might be comparing 20 internal projects in order to make investment decisions.   Bandwidth and management focus is limited even when funds are not.

    The IDC study was recently updated by conducting a survey of 2155 organizations about their information management processes.  The responses were divided into two groups – those deemed to have “high knowledge quotients” (or KQ Leaders) were organizations in the 90th percentile with regard to following best practices in information management.  The analysis revealed consistently higher performance in key areas of business operations.

    As IDC reports, “Organizations with top KQ scores are five times more likely than others to experience benefits that exceed expectations. In other words, KQ Leaders are significantly more frequently able to unlock the value from their organization's information assets.”

    The following are example practices embraced by KQ Leaders and are consistent with the practices that EIS brings to its client projects:

    • Develop an overall information architecture strategy.
      • Organizations should consider the development of a search-driven information architecture that uses a unified index as the virtual layer that connects all their information throughout their information technology infrastructure.
    • Maximize value from existing information assets.
      • Enterprise-capable information access and analysis systems have the ability to locate, find, and utilize these historical assets, improving overall productivity and knowledge reuse and unlocking the hidden value of all this information.
    • Provide senior management support for information sharing and reuse projects.
      • As KQ Leaders, business executives and managers view information as the key asset for research, analysis, decision making, and operations for their business. Senior managers need to create and encourage a culture that values information and provides support and authorization for information access and analysis projects.
    • Understand and plan for security requirements while promoting information sharing.
      • The default strategy should be to share information as widely as possible within the organization and with external stakeholders to promote collaboration, reuse, and innovation.
    • Utilize information access and analysis systems that include text analytics and entity extraction capabilities.
      • The ability to identify, extract, and "unlock" these themes and entities from the text of the documents is what separates the best of the latest generation of systems from traditional search applications.
    • Develop methods and procedures to measure benefits.
      • To get the maximum leverage out of these technologies, organizations have to develop strategies, methods, and procedures for measuring success. Success metrics can also become key tools in the hands of top managers when promoting the use of information access and analysis solutions.

    EIS's client Applied Materials was one of the organizations studied in depth as part of the research program, and provides an excellent case example of how to succeed with an enterprise knowledge architecture that integrates multiple information sources.  The project provided $50 million per year in savings.  See "Applied Materials Promotes Knowledge Sharing and Reuse with Information Architecture and Taxonomy Capabilities" to learn more.

    Seth Earley
    Seth Earley
    Seth Earley is the Founder & CEO of Earley Information Science and the author of the award winning book The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions. He has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance.

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