I must admit I’m overwhelmed by the welter of new flavors of business intelligence (BI) terms. Truth be told, I’m just now getting used to information engineering/management, decision support, data warehousing and predictive analytics. I finally understand and subscribe to The Corporate Information Factory (CIF) more than 10 years after its birth.

I’m currently attempting to tread water with the likes of master data management (MDM), customer data integration (CDI), governance, corporate performance management (CPM), warehouse appliances, unstructured data, pervasive BI, operational BI and decision management. Alas, just when I think I’m starting to swim, along comes software as a service (SaaS), data as a service (DaaS), platform as a service (PaaS), BI as a service (BIaaS) and other aaSs. I’m just not sure I can be saved from drowning.

As a BI practitioner, I’m more a bottom-up than top-down, but I actually prefer a hybrid approach, with top-down providing the framework for bottom-up components. If a compelling business foundation drives that framework, so much the better. For me, that foundation is elusive in BI, so instead, I often turn to the academic business world for guidance.

“Investing in the IT That Makes a Competitive Difference,” an article in the July-August 2008 Harvard Business Review, provides what seems an interesting paradigm for evaluating IT initiatives, including BI. The point of departure for authors Andrew McAfee and Erik Brynjolfsson is research that shows an increase in IT spending from $3,500 per worker in 1994 to $8,000 in 2005, with an associated doubling in worker productivity.1 At the same time, profits from this enhanced productivity have not been shared equitably among competitors in individual industries. Indeed, there is now more performance spread between leaders and laggards, more concentrated winner-take-all markets and more turbulence within sectors than there’s been in 40 years. McAfee and Brynjolfsson attribute this enhanced Schumpeterian competition not to the emergence of digitized products, but instead to the adoption of digitized processes that allow operating models to be consistently and pervasively adopted across an organization. They attribute success among top performers to the standardization and enterprise scope of such process innovations. Successful IT-enabled processes are prevalent in the organization, precise, consistent and enforceable. They also facilitate monitoring, allowing for feedback and experimentation. Gains realized from embedding processes within technologies, such as enterprise resource planning (ERP), customer relationship management (CRM) and enterprise content management (ECM), are especially noteworthy. IT laggards will follow the path of leaders, ensuring process innovations as well as ever-changing dynamism in the competitive landscape.

McAfee and Brynjolfsson propose the mantra “Deploy, Innovate, and Propagate” as a guiding framework for companies seeking differentiation in today’s technology-intensive arena. Deployment presents extreme challenges to senior management as they attempt to implement operating models globally, using technology to faithfully replicate key processes across the organization. The barriers of autonomy and fragmentation from a reluctant organization are often formidable.

While enterprise technology is the means to implement differentiated processes, BI is the vehicle to discover, test and innovate. Interestingly, much like the OpenBI Forum, McAfee and Brynjolfsson note analytics, experimentation and Web 2.0 “crowd wisdom” technologies as fuel for IT-enabled process innovations.

Propagation of digitized processes across the enterprise presents significant challenges for executive management as it looks to simultaneously impose top-down, standardized best practices with bottom-up decision enablement for frontline employees and managers. The new processes often liberate managers from mundane decision-making, fundamentally empowering them to assume responsibility for more important business decisions.

McAfee and Brynjolsson conclude their article by observing that the sharpened differences in company performance related to effective deployment of technology will continue to be a dynamic in not only the U.S. economy, but in world-wide markets as well.

If the hallmark of competitive difference-making IT is technology that promotes business process standardization, centralization and propagation across the enterprise - all the while using intelligence to optimize operations that in turn free up line management for critical strategic decisions - which flavors of BI offer the most promise? Wayne Eckerson, author of the excellent TDWI Report “Best Practices in Operational BI,” and James Taylor, co-author with Neil Raden of Smart Enough Systems, offer important clues.

For Eckerson, operational BI (sometimes called OBI): “moves BI out of the back room and embeds it into the fabric of the business, intertwining it with operational processes and applications that drive thousands of daily decisions. In essence, operational BI merges analytical and operational processes into a unified whole.”2 Moreover, “In its extreme form, operational BI encapsulates business insights into rules and models that organizations can use to automate decisions and responses, eliminating the need for human intervention.”3

Eckerson offers a framework for operational BI, detailing levels that progress from simply analyzing processes with reports, to monitoring processes with dashboards, to facilitating processes that embed metrics in operations and to executing processes that use triggers, analytics, and rules to automate routine decision-making.

Taylor, on the other hand, contrasts operational BI with enterprise decision management (EDM). For him, OBI, while different from traditional BI, still engages people to make decisions. His EDM, by comparison, leverages predictive analytics, mathematical optimizations, business rules, and experimentation (adaptive control) to automate high volume operational decisions.4 Taylor’s EDM seems a close kin of Eckerson’s OBI level four, enabling automated decision-making across the enterprise. Indeed, both high-end OBI and EDM are enterprise-scale initiatives that seek to use IT to standardize, embed and automate business processes, relying heavily on BI components for differentiation. Each flavor captures the essence of McAfee and Brynjolfsson’s deploy, innovate and propagate framework, thus staking a claim to IT that makes a competitive difference.

Advanced operational BI or EDM is a transformative strategy for an organization. The main hypotheses deriving from this strategy are that enterprise, automated focus + analytics + experimentation + business rules > regional, autonomous focus + reporting + expert decisions. And just as they evaluate the performance of other strategies using BI techniques, companies should critically measure the benefits of OBI/EDM. At a minimum, BI can use time series designs to assess performance pre- and post-OBI/EDM deployment. It may even make sense to adopt a more gradual rollout approach, piloting the new processes in select business lines or geographies, while contrasting performance of the new with the status quo over time. The combination of time series measurement with experiments assures a strong design to assess the effectiveness of the OBI/EDM strategy. In the end, prudent enterprises will use BI to evaluate the performance of BI.


  1. Andrew McAfee and Erik Brynjolfsson. “Investing in the IT That Makes a Competitive Difference.” Harvard Business Review, July-August 2008.
  2. Wayne W. Eckerson. “Best Practices in Operational BI: Converging Analytical and Operational Processes.” TDWI Best Practices Report, Third Quarter 2007.
  3. Eckerson. 
  4. James Taylor. “From Operational Business Intelligence to Competing on Decisions.” Business Intelligence Network, July 2008.

Referenced Works:

  1. James Taylor and Neil Raden. Smart Enough Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions. Prentice Hall, 2007.

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