I’ve posted a couple of articles at my company’s blog site that reflect my view on data quality efforts:

  • Yes, there is a business case for improving data quality, and I’ve got real business value examples. If you look for real money where you anecdotally know there are data quality problems, you’ll likely find it in high costs of data correction and rework, and savings related to business process improvements that reliable data enables.
  • There are distinct things an organization can do to reap benefits of improved data management and data quality.  (1) Get started in the first place, (2) find the tangible benefits, (3) cross the departmental silos that exist in every large organization, and (4) promote sound data management practices.

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In the past I’ve never understood what people really mean they say “think outside the box” but Jim Harris, in a recent OCDQ blog post, helped me figure it out.

Mr. Harris ends with this provocative line: “the bottom line is Google and Facebook have socialized data in order to capitalize data as a true corporate asset.”  The post starts with a cold war analogy and proceeds to describe how Facebook and Google have made big money as “internet advertising agencies:” offering free services with which users (like us) serve up personal data in return for use of the service, then selling advertising space based on our data (hopefully anonymized).

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Who would want to be a national health care administrator?  Who would want the responsibility for managing health care and formulating health policy for tens or hundreds of millions of people?  It seems obvious that such decisions would rely on quality data.  A recent interview impressed upon me how much data managers can learn from a field where data recording millions of separate life and death decisions aggregates to support decisions on the future allocation of health care resources.

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“Our goals can only be reached through a vehicle of a plan, in which we must fervently believe, and upon which we must vigorously act. There is no other route to success.” – Pablo Picasso

It is an old story: about 30% of IT application projects succeed, 45% are “challenged,” and the other quarter fail altogether.   That’s the consistent result over the years of the Standish Group Study of Project Outcomes.  Jorge Dominguez, here, displays a chart of the remarkably similar results since 1994.  Not a pretty picture, right?  Some question the validity of the Standish studies, but Scott Ambler parallels the Standish story in a recent Dr Dobbs column called “Lies, Great Lies, and Software Development Project Plans,” which itemizes the strategies commonly used by IT project managers to “stay out of trouble” when schedule/budget results don’t match initial estimates.  For example, “18% change the original schedule to reflect the actual results”. Continue reading »

 

The March 2010 issue of The Atlantic features an article called “Management Secrets of the Grateful Dead.” It’s a great read, especially the second half, which tells of the band’s innovations in organization, fan loyalty, and, perhaps counterintuitively, creating value by freely giving away their product. The success of these measures seems self evident: the Dead were “one of the most profitable bands of all time” and almost singlehandedly created an entire product category, jam bands. As a result, the article recounts, the Dead are replacing companies like Southwest Airlines and GE as management training examples of strategic innovators.

As good as it is, to me the article conjured an unlikely vision of the Dead as business men in hippie drag self-consciously making strategy decisions that altered the marketing landscape. I agree that the Dead took the actions cited on purpose, but I believe core product, not marketing strategy, consumed the band’s energies during its formative and peak years.   Could it be that their innovative market strategies grew organically from a quality product, where quality included the entire fan experience? Continue reading »

 

Here are three things to remember when putting together a BI business case:

InformationManagement

Excerpt from "Show Me the Money: A DM/BI Business Value Primer", Bob Lambert and Tri Truong, Information Management Special Reports, March 24, 2009

  1. Intangible benefits don’t count.
  2. BI has no inherent value.
  3. Senior managers often make decisions about future outcomes with insufficient data. Continue reading »
 

It is a commonplace to say we should manage data like a resource. But when you think about it, data is an asset but not a resource.  Data isn’t a thing like real estate, employees, or customers, but rather it represents all of those things.  In data-geek-speak, data is a meta-resource that holds information about resources.  That makes data a lot like money. Continue reading »

 

In a recent very thoughtful post on data quality, Paul Erb plays out an analogy comparing data users with Don Quixote and data quality professionals with Sancho Panza, then reverses the analogy to cleverly coin the “Sancho Panza” test of data quality professionals.  He encourages data quality professionals promoting the critical role of data quality to apply a what would Sancho say test to ensure that they are aligned with the needs and interests of data consumers. Continue reading »

 

While many organizations understand the value of managing the information resource, for many others information management remains abstract and difficult to define.  In an effort to make it concrete here’s a hypothetical proposal to provide an Enterprise Information Architect for a hypothetical organization that really needs one. Continue reading »

 

History is littered with IT application projects that end late, go way over budget, or abandoned altogether.  I was fortunate enough to see one work out really well (almost – please read on).  It was no mistake.  It came down to a simple method advocated by a gentleman named named John Carpenter.

The project was an HR management software conversion from one commercial off-the-shelf software (COTS) package to another.  The company concerned was conservative about spending money.  A previous business case had proposed a similar project.  The problem with that business case was that the benefits were really tough to conceptualize, so the cost/benefit analysis relied on soft benefits like “improved access to information” and “more consistent reporting data”.  The folklore was that the CFO had physically thrown that business case out of his office. Continue reading »

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