You’re So Vain, You Probably Think Data Quality Is About You

March 30, 2009
63 Views

Don’t you?

“Data Quality is an IT issue because information is stored in databases and applications that they manage. Therefore, if there are problems with the data, then IT is responsible for cleaning up their own mess.”

“Data Quality is a Business issue because information is created by business processes and users that they manage. Therefore, if there are problems with the data, then the Business is responsible for cleaning up their own mess.”

In response to these common viewpoints (channeling the poet Walt Whitman), I sound my barbaric yawp over the roofs of the world:

“Data Quality is not an IT issue. Data Quality is not a Business issue. Data Quality is everyone’s issue.”

Unsuccessful data quality projects are most often characterized by the Business meeting independently to define the requirements and IT meeting independently to write the specifications.  Typically, IT then follows the all too common mantra of “code it, test it, implement it into production, and declare victory” that leaves the Business frustrated with the resulting “solution.”

Successful data quality projects are driven by an executive management mandate for the Business and

Don’t you?

“Data Quality is an IT issue because information is stored in databases and applications that they manage. Therefore, if there are problems with the data, then IT is responsible for cleaning up their own mess.”

“Data Quality is a Business issue because information is created by business processes and users that they manage. Therefore, if there are problems with the data, then the Business is responsible for cleaning up their own mess.”

In response to these common viewpoints (channeling the poet Walt Whitman), I sound my barbaric yawp over the roofs of the world:

“Data Quality is not an IT issue. Data Quality is not a Business issue. Data Quality is everyone’s issue.”

Unsuccessful data quality projects are most often characterized by the Business meeting independently to define the requirements and IT meeting independently to write the specifications.  Typically, IT then follows the all too common mantra of “code it, test it, implement it into production, and declare victory” that leaves the Business frustrated with the resulting “solution.”

Successful data quality projects are driven by an executive management mandate for the Business and IT to forge an ongoing and iterative collaboration throughout the entire project. The Business usually owns the data and understands its meaning and use in the day to day operation of the enterprise and must partner with IT in defining the necessary data quality standards and processes.

Here are some recommendations for fostering collaboration on your data quality project:

  • Provide Leadership – not only does the project require an executive sponsor to provide oversight and arbitrate any issues of organization politics, but the Business and IT must each designate a team leader for the initiative.  Choose these leaders wisely.  The best choice is not necessarily those with the most seniority or authority.  You must choose leaders who know how to listen well, foster open communication without bias, seek mutual understanding on difficult issues, and truly believe it is the people involved that make projects successful.  Your team leaders should also collectively meet with the executive sponsor on a regular basis in order to demonstrate to the entire project team that collaboration is an imperative to be taken seriously.

  • Formalize the Relationship – consider creating a service level agreement (SLA) where the Business views IT as a supplier and IT views the Business as a customer.  However, there is no need to get the lawyers involved.  My point is that this internal strategic partnership should be viewed no differently than an external one.  Remember that you are formalizing a relationship based on mutual trust and cooperation.

  • Share Ideas – foster an environment in which a diversity of viewpoints is freely shared without prejudice.  For example, the Business often has practical insight on application development tasks, and IT often has a pragmatic view about Business processes.  Consider including everyone as optional invitees to meetings.  You may be pleasantly surprised at how often people not only attend but also make meaningful contributions.  Remember that you are all in this together.

Data quality is not about you.  Data quality is about us.

I believe in us. 

Don’t you?

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