Search Only Goes So Far

January 30, 2012

Infocentric Research surveyor Stephan Schillerwein, who presented his findings at the Online Information Conference, released some alarming statistics about enterprise search in his report “The Digital Workplace.” Among the points which jumped out at me were 40 percent of employees use the wrong information when conducting enterprise searches and 63 percent “make critical decisions without being informed,” which results in a 25 percent work information productivity loss.

According to the Pandia Search Engine News Article “Huge Problems for Search In the Enterprise” Schillerwein believes there are a few reasons why enterprise search is problematic. Users don’t account for the fact that enterprise search is different from Web Search, they have unrealistic expectations and there is a clear problem of lack of content. The Pandia article asserted: Schillerwein suggests a solution based on several elements, such as consistent coverage of information flows for processes, bringing together the worlds of structured and unstructured information, and adding context. I would agree as this ability to combine structured and unstructured data while maintaining context is key in our approach. However, when you combine the crowded jumble of tweets, social media and other data that crowd employees’ smart devices the problems with enterprise search could continue to take a downward spiral and “finding a needle in a haystack” could be easier than doing an enterprise search.

These observations triggered several questions and observations.

First, there are a number of companies offering enterprise information solutions. Many are focused on the older approach of key word queries. There are business intelligence systems which provide “find-ability” tools along with a range of useful analytic features. Although search is not the focal point of these solutions, they do provide useful visualizations and statistics on content. The problem is that most organizations are confused about what is needed and what must be done to maximize the value of systems which go beyond key word retrieval. This confusion is likely to play a far larger role in enterprise search challenges than many market analysts want to acknowledge. Instead, many solutions today seem to be making information access more confusing and problematic, not clearer and more trouble free.

Second, the challenge may be more directly related to figuring out what specific business process needs which information. Without a clear understanding of the user’s requirements, it may be difficult to deploy a system that delivers higher user satisfaction. If this hypothesis is correct, perhaps more vendors should adopt the approach we have taken at Digital Reasoning. We make an extra effort to understand what the user requires and then invest time and resources in hooking appropriate information and data into the system. No solution can deliver the right fact-based answers if the required information is not within the data store and available to the algorithms which make sense of what is otherwise noise? We think that many problems with user acceptance originate with a misunderstanding or sidestepping of user requirements and the fundamental task of getting the necessary information for the system.

Third, the terminology used to describe information retrieval and access is becoming devalued. At Digital Reasoning, we work to explain succinctly and without jargon how our next-generation system can facilitate better decision making for financial, health, intelligence, and other professional markets. We have complex numerical recipes and sophisticated systems and methods. Our focus, however, is on what the system does for a user. We have been fortunate to receive support from a range of clients from government and industry as well as the investment community for our next-generation approach. We think our strength is our focus on the customer’s need and not only our unique predictive algorithms and cloud-based solution.

To learn more about Digital Reasoning and our products, navigate to www.digitalreasoning.com .

Dave Danielson, Digital Reasoning, January 30, 2012

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Stephen E. Arnold monitors search, content processing, text mining and related topics from his high-tech nerve center in rural Kentucky. He tries to winnow the goose feathers from the giblets. He works with colleagues worldwide to make this Web log useful to those who want to go "beyond search". Contact him at sa [at] arnoldit.com. His Web site with additional information about search is arnoldit.com.