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Big begets big: The information governance challenge

How does one deal with the types of information Forbes says are found within an organization? The archived or legacy information is important. Why recreate from ground zero the quarterly financial briefing when the previous quarter’s PowerPoint serves as a template? With that older version, pulling information from the different sources becomes easier. In theory, the extraction of information from the financial system, the legal department and the marketing unit seems like an ideal task for automation.

Information governance approaches

Information governance (IG) should identify that task, locate the data sources needed and make it possible to get a developer to write a script to do the data extraction and formatting. Some organizations already have systems and software in place that can do the job. If not, integration engineering companies, normalization and federation software vendors like Kapow Software (kapowsoftware.com), and vendors of integrated content processing storage devices can make certain recurring information tasks easier and more efficient.

One example is GridBank, a firm that provides storage and information governance services. The company bundles tools for searching and discovering high-value information from the big data processed. The need to take advantage of large volumes of data has sparked interest in data as a service (DaaS). Wikipedia describes DaaS as “a cousin of software as a service. Like all members of the ‘as a service’ family, DaaS is based on the concept that the product, data in this case, can be provided on demand to the user regardless of geographic or organizational separation of provider and consumer.”

The organization now has another layer of information management with which to deal: the internal information, which continues to be a challenge in many organizations, and the reality of having flows of third-party data.

The solutions that I have heard discussed at conferences and in client meetings fall into two categories. The data management or information governance requires a new initiative. Most organizations lack the resources and, in my experience, the will power to do much more than push deck chairs around as the Titanic begins to sink.

Another approach is to segregate the information and address each chunk in an appropriate way. Companies like BAE Systems, Leidos, Raytheon and others provide solutions that work on specific data sets. The idea is that those systems deal with specific data flows, provide tools appropriate for those data flows and are implemented to handle certain types of questions. Geofeedia’s ability to display in a geolocation specific messages in real time is representative of those solutions. The organization opting for what I call a next-generation information access (NGIA) solution narrows the scope of the NGIA system to solve carefully articulated problems.

Evolution, not revolution

Where do big concepts knowledge management (KM), master data management and information governance provide value in big data? For traditional search-based and content management-centric solutions, search and retrieval and identifying colleagues with particular expertise are handled with existing work processes. Employees know how to search. When the required information is not available, employees ask colleagues and resort to traditional methods like browsing files or examining hardcopy documents. The KM, MDM and IG solutions improve access to some degree. Overall, the fast moving nature and the behavior of humans mean that modest progress is made regardless of management statements and budget.

For the NGIA approach, the narrowness required to deal with big data, often arriving in real time, forces the organization to rethink storage, methods of processing and outputs. An NGIA system imposes governance on a licensee. No one installs a BrightPlanet DaaS for specialized Web content or a Geofeedia when one has a problem with locating PowerPoints within an intranet.

A shift from traditional information management methods is taking place. The shift is not revolutionary. The change is evolutionary. At some point, enterprise knowledge solutions give way to newer, smarter and predictive systems. If I am right, consultants anchored in the tradition of keyword search and records management will find themselves recommending software systems that ingest, normalize, process and output information automatically. Users will interact with next-generation systems in a way that is comfortable to the user. Some users will prefer to use a graphic interface. Others will write scripts or use visual programming tools. Others will consume what the smart system determines is what the employee needs to know to complete a task.

In short, today’s problem is shifted from a search-centric model to an actionable information model. Knowledge management, therefore, becomes “the wing wherewith we fly to heaven.” KM, MDM and IG do not become massive projects that are too expensive and complicated to implement. KM, MDM and IG emerge from adoption of next-generation information access systems.

Looking at today’s problems in terms of a 1960s view of computing and work processes ensures the persistence of the frustrating and soul-deadening approach to information. Focusing on solving specific problems using the best available technology delivers a substantive payoff. Big ideas are difficult to implement in most organizations in my experience.

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