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Legalizing the Spread(marts) of Business Intelligence

Originally published November 4, 2008

For many years, inflexible data governance organizations and IT departments have put a stranglehold on the development, distribution and consumption of analytical business intelligence applications – or at least they thought that they did. These analytical applications leaked out of IT’s “walled garden” in an almost intoxicating fashion. Shadow IT departments sprung up to fill the demands of the power users. Taking dumps of data from various places and importing it into desktop applications, the concept of the spreadmart was born.

IT departments and data governance organizations have spent a lot of time and resources tracking down the use of analytical applications in the form of spreadmarts with the goal of bringing them back into the “regulation” of IT under the direction of data governance. Similarly, business-sponsored shadow IT groups and power users have spent a lot of corporate resources to make analytical applications available, despite what might be best for the organization as a whole.

This is much like the prohibition of alcohol during the 1920s and 1930s or, more recently, the “war on drugs.” And much like the “war on drugs,” no matter how much the “regulators” try, there always seems to be a market for the things that users think they can’t have.

Roles to Play

The long-running debate about drug policy in the United States is an interesting analogy to the “war” between IT and power users. In the “war on drugs,” on one side you have government agencies and “moralist” organizations. These groups have decided for various reasons that the production, distribution and consumption of certain drugs are against the social good and, therefore, should be stopped or at the very least regulated. On the other side, you have civil liberty organizations and libertarians. These alliances view the consumption of the aforementioned drugs as personal choice and almost a right.

The groups agree at the extreme ends of the drug spectrum in regard to drugs like crystal meth (very bad) and caffeine (not really worth the effort to stop). In the gray area of illegal drugs, and where you get lots of argument and contention, are so-called soft drugs like marijuana. Many organizations and even some state governments are finding medical and thus socially acceptable uses for marijuana. These organizations have made inroads to relatively safe distribution and consumption of this drug.

One interesting proposal to end the “debate” relating to marijuana is to legalize and regulate the drug. This would be accomplished by having the tobacco industry use its existing manufacturing plants and equipment, distribution systems and marketing apparatus to drive the “street cost” of marijuana to a low level and thus remove the incentive of the illegal/non-regulated drug trade, standardize the physical “experience” of marijuana via standardization of crops, and pull in a tidy tax profit on each pack sold. Setting aside the number of drug cartels that would have to find a new drug to sell, 75% of the stakeholders in the drug debate would find “not unhappiness” with that solution.

Analytics – Soft Drugs of Business

In the world of business information technology applications, the role of government agencies is played by the IT department. Large, and often bureaucratic and slow moving, IT departments are the regulators and “law enforcement” of corporate America when it comes to technology. The moralists are represented by data governance organizations. Strident and driven, data stewards can be orthodox or inflexible in their definitions of and application of technologies. Civil rights organizations are the various and sundry non-technical business units within a corporation like marketing and sales. They are looking for freedom for all and often cannot understand why there are limits placed on them by IT departments and the data stewards. Finally, data-driven power users, or quants, are the libertarians. They want the freedom to live on the bleeding edge of analysis without the constraints of things like compliance, metadata or data quality.

Along the continuum of business information technology applications, you have at the one end core business applications like customer relationship (CRM), supply chain (SCM) and enterprise resource (ERP) management (and it is interesting to link CRM, SCM and ERP to crystal meth… ). These applications are core to the overall business plan of a company. No one debates that these applications are, and should be, “regulated” and controlled by the CIO and the IT department. At the other end, you have “harmless” desktop applications like instant messaging (IM) platforms and web browsers. These applications are relatively harmless to the overall social order of an organization, and most can agree that they do not need to be “regulated” by the IT department unless you have a particularly stringent security policy.

The gray area that has emerged is the class of “soft-drugs” known as analytical business intelligence. To the quants in the organization, analytical applications are viewed as free choice that provides enlightenment to the user and benefit to the organization to “see outside the box” of existing standard operational and financial reports. The business stakeholders or quants fight for the freedom of the analytical applications since they usually provide greater value over the existing IT-sponsored operational or financial reports. To the data governance organization, analytical applications are viewed as something that should be controlled and regulated since they could lead to the “destruction of the youth of the company” or, at the very least, a severe Sarbanes-Oxley compliance violation.

“Medicinal” Analytical Applications

Many software product vendors have tried to establish the “medical marijuana” version of analytical applications and find an acceptable version of analytical applications that would meet the needs of the quants and make IT departments reasonably secure that the data governance rules were not being broken. The general category of this type of software is being called “in memory business intelligence.”

These product/solution categories have become the recent marketing, and thus venture capital investment, trend. Many of those product vendors observed that if people like to use the Excel interface, then they should make their products Excel-like or, at the very least, Excel friendly from the perspective that you can import into and export from it if you like. Similar to the process of dispensing of medical marijuana, using Excel interfaces is designed to make power users more comfortable with the distribution system. I have heard it, or similar technologies, referred to as enterprise analytics (TIBCO Spotfire) or sandbox-based data marts (Lyzasoft).

Big Tobacco of Software

And now we have the rough equivalent of the “Tobacco Industry” stepping into the analytical application arena with Microsoft and their upcoming Gemini offering. For those that do not know, in 2010 Microsoft will launch a comprehensive set of analytical business intelligence tools. Gemini will not just be “Excel-like.” It will be baked right into the Excel interface. This project will exercise their considerable advantage in client application installation distribution and now their growing ability to provide the back-end technology to feed that client application with an end-to-end business intelligence solution. They have the distribution network, the user base and expertise to lower the “street cost,” standardize the “experience” and pull a tidy “license fee” from each pack… err… license sold.

While we will have a while to wait for Microsoft’s software delivery and the reaction by the power users and their backing business units, the early previews are quite impressive and beg the following question:

Should the other analytical business intelligence application vendors be worried/concerned?

If the past performance of Windows, Internet Explorer, SQL Server and other Microsoft applications is indicative of future events, we might just find that the “bleeding edge” experience of analytical applications is replaced with a “mainstream” experience, compliments of the “Big Tobacco of Software.”

  • John MyersJohn Myers

    John Myers, a senior analyst in the business intelligence (BI) practice at  Enterprise Management Associates (EMA). In this role, John delivers comprehensive coverage of the business intelligence and data warehouse industry with a focus on database management, data integration, data visualization, and process management solutions. Prior to joining EMA, John spent over ten years working with business analytics implementations associated with the telecommunications industry.

    John may be contacted by email at JMyers@enterprisemanagement.com.

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