Share with your friends










Submit

Analytics Magazine

Forum: A conceptual framework for BI/analytics strategies

Based on research and best practices, the framework aims to bring clarity to the field.

Jay LiebowitzBy Jay Liebowitz

Business intelligence (BI) and analytics programs are among the “hottest” curricula being developed at universities and colleges worldwide. Definitions vary on what entails business intelligence or analytics, and there doesn’t seem to be a universal BI/analytics conceptual framework that is being used by organizations and universities to develop their BI/analytics strategy and associated roadmap. To provide some clarity and based on research and best practices in the field, I developed the BI/Analytics Conceptual Framework as shown in Figure 1.

Figure 1: BI/analytics conceptual framework. Framework author Jay Liebowitz used a Delphi survey of experts for verification. The red items indicate the more important factors based on the surveyed experts.

Figure 1: BI/analytics conceptual framework. Framework author Jay Liebowitz used a Delphi survey of experts for verification. The red items indicate the more important factors based on the surveyed experts.

In order to better understand if these are the right components, I reached out to some BI/analytics experts in industry and universities as part of a Delphi survey. Some of the preliminary comments from those experts in this first round include:

  • Analytics skills mature over time within organizations, suggesting the value of incorporating a CMM (capability maturity model) in your framework.
  • Other business and IT drivers might include: different skill levels in working with voluminous data; visibility into competitors’ moves so competitive responses can be developed; being able to combine customer-provided data with other information we have about those same customers; curating and filtering information into “need to know” slices so confidentiality and privacy are protected.
  • Other BI enablers may include: analytics to become trusted advisors to senior executives (this requires more than technical analytic skills – it requires deep understanding of the business and marketplace, strong influencing and relationship-building skills, organizational savvy, effective storytelling and visualization skills, and a willingness to present candidly even unwelcomed information); organizational design can help or hinder the impact of analytic investments; problem definition and problem prioritization.
  • Other BI/analytics strategy goals: reduce speculation and judgment bias that affect objectivity and barriers imposed by “hidden” factors in the decision-making process.
  • Other BI/analytics success factors: define problems correctly (digging and not just reviewing the surface); preparedness for the analytics process (collaboration); management of expectations about outcomes of analytics processes; applicability of the results; connect key risk indicators with key performance indicators.

The second round with the Delphi experts identified the red highlighted factors in Figure 1 as being the most important in the framework. Before going ahead in further revising the conceptual framework, I would be curious in getting your feedback as to the accuracy and completeness of this proposed BI/analytics conceptual framework.

I welcome input and thoughts. Send comments to jliebowitz@harrisburgu.edu.


Jay Liebowitz (jliebowitz@harrisburgu.edu) is the DiSanto Visiting Endowed Chair in Applied Business and Finance at Harrisburg University of Science and Technology in Harrisburg, Pa. He is a member of INFORMS.

Related Posts

  • 70
    Car dashboards are simple visual indicators of a complex machine with many parts that performs a high-stakes task in a context of many overlapping, conflicting rules and goals: personal convenience, safety, minimum travel time, courtesy to other drivers and so on. The speedometer, perhaps one of the most important indicators,…
    Tags: business, analytics, intelligence, bi
  • 62
    November/December 2010 In their 2007 book, “Competing on Analytics: The New Science of Winning,” Tom Davenport and Jeanne Harris captured for many the powerful potential of analytics to provide organizations with a competitive advantage. The book’s title called analytics a “new” science, but concepts and terms such as “business analytics”…
    Tags: analytics, business, intelligence
  • 57
    On one end of the spectrum, labeled “Do Stuff,” organizations focus on action taking, a laissez-faire approach to project management, with little documentation and loosely defined deliverables, timelines and budgets. On the other end, labeled “Buttoned Up,” organizations take a disciplined approach to planning, monitoring and executing projects, with documentation…
    Tags: analytics, intelligence, business
  • 56
    Car dashboards are simple visual indicators of a complex machine with many parts that performs a high-stakes task in a context of many overlapping, conflicting rules and goals: personal convenience, safety, minimum travel time, courtesy to other drivers and so on. The speedometer, perhaps one of the most important indicators,…
    Tags: business, analytics, bi, intelligence
  • 55
    January/February 2011 CLICK HERE TO GO TO THE DIGITAL VERSION OF THIS ARTICLE The journey from what to who, when and why. By Talha Omer The other day, my analytical team at a major telecommunications company and I were presenting an all-new behavioral segmentation to one of our senior executives.…
    Tags: analytics, bi, business, intelligence


Headlines

Fighting terrorists online: Identifying extremists before they post content

New research has found a way to identify extremists, such as those associated with the terrorist group ISIS, by monitoring their social media accounts, and can identify them even before they post threatening content. The research, “Finding Extremists in Online Social Networks,” which was recently published in the INFORMS journal Operations Research, was conducted by Tauhid Zaman of the MIT, Lt. Col. Christopher E. Marks of the U.S. Army and Jytte Klausen of Brandeis University. Read more →

Syrian conflict yields model for attrition dynamics in multilateral war

Based on their study of the Syrian Civil War that’s been raging since 2011, three researchers created a predictive model for multilateral war called the Lanchester multiduel. Unless there is a player so strong it can guarantee a win regardless of what others do, the likely outcome of multilateral war is a gradual stalemate that culminates in the mutual annihilation of all players, according to the model. Read more →

SAS, Samford University team up to generate sports analytics talent

Sports teams try to squeeze out every last bit of talent to gain a competitive advantage on the field. That’s also true in college athletic departments and professional team offices, where entire departments devoted to analyzing data hunt for sports analytics experts that can give them an edge in a game, in the stands and beyond. To create this talent, analytics company SAS will collaborate with the Samford University Center for Sports Analytics to support teaching, learning and research in all areas where analytics affects sports, including fan engagement, sponsorship, player tracking, sports medicine, sports media and operations. Read more →

UPCOMING ANALYTICS EVENTS

INFORMS-SPONSORED EVENTS

INFORMS Annual Meeting
Nov. 4-7, 2018, Phoenix

Winter Simulation Conference
Dec. 9-12, 2018, Gothenburg, Sweden

OTHER EVENTS

Making Data Science Pay
Oct. 29 -30, 12 p.m.-5 p.m.


Applied AI & Machine Learning | Comprehensive
Starts Oct. 29, 2018 (live online)


The Analytics Clinic
Citizen Data Scientists | Why Not DIY AI?
Nov. 8, 2018, 11 a.m. – 12:30 p.m.


Advancing the Analytics-Driven Organization
Jan. 28–31, 2019, 1 p.m.– 5 p.m. (live online)


CAP® EXAM SCHEDULE

CAP® Exam computer-based testing sites are available in 700 locations worldwide. Take the exam close to home and on your schedule:


 
For more information, go to 
https://www.certifiedanalytics.org.