Business Intelligence

Dresner’s Point: Why Do We Need Dashboards for Information Discovery in Business Intelligence?

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Have you noticed that there is a marked difference in opinion as to the purpose of a business intelligence dashboard? I mentioned in one of my Friday #BIWisdom tweetchats that “data discovery” was ranked #6 and “dashboards” were ranked #1 out of 19 technologies deemed strategic to business intelligence efforts in our 2013 Wisdom of Crowds® Business Intelligence Market Study (available at www.biwisdom.com), and the tribe was off and running in a debate about the use of dashboards in data/information discovery. 

Among the perspectives of vendors, buyers and analysts/consultants participating in our tweetchat, there was no dominant view, as reflected in their opposing tweets:

  •  Information discovery goes beyond dashboards and is complementary to dashboards — vs: dashboards are just another variation of information discovery.
  • Dashboards are not part of information discovery — vs. dashboards enable users to drill down to the questions that start information discovery.
  • Dashboards are static displays of end results of insights to users conceived by someone else — vs. dashboards are interactive and allow users to start with known data and then add their own data and enhance or embellish the results.

Is it an important issue? I’d venture to say it is. As vendors continue evolving dashboard and data discovery tools, they need to understand users’ objectives. As we talked through the issues further, my #BIWisdom group made several important observations from their real-world experiences. 

  1. Data/information discovery means tapping into a data source for more/deeper insights.  You could structure those sources and bring them into a dashboard, which helps users who need to start with a fixed point before adding more data to change the view.
  2.  A dashboard can also be a good starting point to give context. The results of innovation and information discovery that add business value need to be folded back into the business processes. But validation must be done before operationalizing the discovery back to the business, and a dashboard can provide that context. A dashboard can actually wind its way through an organization and stop at every level for validation.
  3.  A dashboard limits thinking beyond the dashboard context. 

The #BIWisdom tweets found that the group agreed on two issues. First, dashboards today are less diagnostic and more description. They aren’t yet predictive. So today’s dashboard requester still must focus on queries such as “How’s the plane flying?” or “How much fuel do I have?” rather than “I wish I knew ….” 

Second, dashboards are an important functionality in getting to real insights, as they display what the organization knows. Value in information discovery comes when mixing internal corporate data with other sources (mashups) to get new insights. Clever structuring of data can also help users to discover the most relevant data faster. 

Bottom line: The key to greater value in BI is to use analytics to discover insights and information that the organization didn’t know. But some BI users only want to see “what if” kinds of discovery; they don’t care about the full range of information discovery. Thus, it is necessary to balance the analytics between the business intelligence that users want and the business intelligence that could give the business an edge. Ultimately, the challenge is helping users to “discover” the “right” questions to ask. 

Another challenge is moving the center of gravity for information discovery to the middle and including IT in the process. When it comes to information discovery on demand, IT needs to rethink the BI architecture and needs to focus on managing agility as opposed to managing complexity. IT needs to be a huge enabling partner, providing the “plumbing” or infrastructure, while the business needs to be front and center in making sure the analytics tools deliver critical information and insights that lead to competitive advantages. 

Howard Dresner is president, founder and chief research officer at Dresner Advisory Services, LLC, an independent advisory firm. He is one of the foremost thought leaders in Business Intelligence and Performance Management, having coined the term “Business Intelligence” in 1989. He has published two books on the subject, The Performance Management Revolution — Business Results through Insight and Action, and Profiles in Performance — Business Intelligence Journeys and the Roadmap for Change. He hosts a weekly tweet chat (#BIWisdom) on Twitter each Friday. Prior to Dresner Advisory Services, Howard served as chief strategy officer at Hyperion Solutions and was a research fellow at Gartner, where he led its Business Intelligence research practice for 13 years.

Comments

By Donald MacCormick

Howard, interesting and timely post.
My feeling is that the key value of dashboards lies squarely between their historic “at a glance” roots and fully-fledged data discovery.
All dashboards requirements we see these days call for significant interactivity (drill, pivot, slice, dice, filter, …) but packaged in a tailored interface, which reduces or removes the need for training and so makes then accessible to the non-analyst end user.
My favorite example from the “real” world is the BBC website (or indeed most weather websites). It surfaces the results of applying complex predictive algorithms to a huge data set through an engaging, no-training-required interface. I would argue that this is a perfect metaphor for delivering end-user BI going forward.
(many more details on our blog, specifically at http://www.antivia.com/blog/?p=1569)
For years analyst users have been relatively well served by BI. IMO Interactive dashboards offer the non-analyst end-user the right BI for them and will be crucial in driving adoption of BI dramatically up from its historic plateau of around 20%.
(Disclosure – I am CPMO at Antivia, the interactive dashboard vendor)

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