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Barry Devlin

As one of the founders of data warehousing back in the mid-1980s, a question I increasingly ask myself over 25 years later is: Are our prior architectural and design decisions still relevant in the light of today's business needs and technological advances? I'll pose this and related questions in this blog as I see industry announcements and changes in way businesses make decisions. I'd love to hear your answers and, indeed, questions in the same vein.

About the author >

Dr. Barry Devlin is among the foremost authorities in the world on business insight and data warehousing. He was responsible for the definition of IBM's data warehouse architecture in the mid '80s and authored the first paper on the topic in the IBM Systems Journal in 1988. He is a widely respected consultant and lecturer on this and related topics, and author of the comprehensive book Data Warehouse: From Architecture to Implementation.

Barry's interest today covers the wider field of a fully integrated business, covering informational, operational and collaborative environments and, in particular, how to present the end user with an holistic experience of the business through IT. These aims, and a growing conviction that the original data warehouse architecture struggles to meet modern business needs for near real-time business intelligence (BI) and support for big data, drove Barry’s latest book, Business unIntelligence: Insight and Innovation Beyond Analytics, now available in print and eBook editions.

Barry has worked in the IT industry for more than 30 years, mainly as a Distinguished Engineer for IBM in Dublin, Ireland. He is now founder and principal of 9sight Consulting, specializing in the human, organizational and IT implications and design of deep business insight solutions.

Editor's Note: Find more articles and resources in Barry's BeyeNETWORK Expert Channel and blog. Be sure to visit today!

March 2012 Archives

girl-boy-lego.jpgMany BI vendors now offer collaborative support as an additional feature of their tools.  Unfortunately, that's exactly what it often looks like--an add-on feature to an existing environment.  What I describe in my new White Paper, "iSight for innovation", is how collaborative decision making could (and maybe should) be addressed in a new context.  Not as a bolt-on afterthought to existing business intelligence, but as a new environment of which existing BI tools and methods are but a part.

Fifty years after the advent of decision support systems, and despite two decades of BI, enterprise decision making and, in particular, highly innovative decision making, remain a hit-or-miss affair.  This is because we have bought into a myth that great decisions and innovations spring from the mind of a lone genius.  But if we examine innovative decisions in most organizations, particularly large enterprises, we see most breakthroughs coming from teams--not from some whiz kid.

Business intelligence tools for most of their twenty year history have focused their efforts on the individual decision maker.  Where does he get the data needed and in what form?  What techniques should be provided for exploration and querying?  How will she visualize the results?  All of this is certainly valid, but it homes in on one single facet of decision making, which I call investigation. Investigation begins with a challenge, followed by the gathering and integration of formal information in the shape of documents and databases.  Then she works on it.  And generates further formal information, such as spreadsheets and presentations, in the process.  Her intention determines what information is gathered, the path followed and results produced.  It's a largely solitary process, with peer or managerial review at predetermined points in time--often only at the end.

If we accept the premise that most innovative decisions in business emerge from teams working together--and there is much research that suggests this is so--we see immediately that BI tools, as currently structured, don't fit the bill.  Furthermore, bolting collaborative tools onto them cannot change the underlying process from individualized to team oriented.  The iSight model of collaborative decision making and innovation starts from interaction.  This is the process that goes on between team members.  Having explored that, we can combine it with the investigation process that each individual performs as part of the team.  When we look at interaction, we see that there exists another category of information, labelled informal, that is continuously exchanged between team members and is the source of most, if not all, of the innovation of the team.

Thus, iSight brings together formal and informal information, the worlds of Business Intelligence and Enterprise 2.0, in a framework that drives novelty in decision making.  It presents a high-level architecture that maps to specific tools and methods required to create a systematic process within the enterprise that delivers real, implementable innovations.  This model's strategic power comes not only from assisting in making today's decision well, but also by capturing informal information of the group interactions in each decision-making event so as to make useful recommendations for subsequent decisions.

The goal of this paper, developed in close collaboration with Scott Davis, the visionary CEO of Lyzasoft, is to introduce a new way of looking at decision making in a team context. The iSight model is really just a foundation for the extensive new thinking I believe is needed to define how to support collaborative decision making.  I mean, really support it and facilitate it.  I encourage you to take a look and welcome your comments or questions...

Posted March 26, 2012 9:11 AM
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