How partnerships between IT and the business breed success

The stakes are high in the world of analytics and reporting.  According to Gartner: through 2016, only 10 percent of self-service business intelligence initiatives will be sufficiently well governed to prevent inconsistencies that adversely affect the business.  Without appropriate processes and governance, self-service capabilities can introduce multiple versions of the truth, increase errors in reporting, and leave companies exposed to inconsistent information.  So how can an organization find the right balance between the traditional IT development process and more innovative data discovery in the business?

Many organizations struggle to find the right approach.  Everyone wants access to data, and they don’t necessarily want to rely on IT.  But on the other hand, they want to be able to rely on the quality of any reports / dashboards they are leveraging.  Make it a partnership!  Invest in BI and analytic environments that allow experimentation and data discovery.  Then follow up with resilient operationalized analytics solutions where repeatable value is identified.

Organizationally, the right business / IT partnership can make this work.  One approach that I’ve implemented successfully incorporates the concept of a matrixed organization. 

Create a BI Competency Center (BICC) in IT that can develop certified enterprise reporting using a standard iterative (and agile) approach with the business, including user acceptance testing and sign off.  These certified reports should be visually identifiable as such.  This is a typical structured IT approach that provides high quality, consistent reporting to an organization – reporting that can be relied upon as producing key, trusted information.    

In addition, allow data analysts in the business to explore data, and to produce and share results.  This can be from any number of sources and can be produced using BI tools or spreadsheets — whatever works best for the business.  Their results are extremely useful, especially for driving innovation and new ideas.  Their exploration and discovery is much needed in any organization, and results can help to drive actions.  However, these results are not “certified”, and everyone in the organization who uses these results is aware of this. 

The business / IT partnership is then created by matrixing a subset of the IT BICC developers to specific business areas.  These developers still report in to IT, and continue to leverage all of the standards that IT requires.  They also embed themselves into the business and work to understand the types of information that’s important to them, and why.  As the data analysts in these areas discover useful information, they team up with the BI developers to create certified reports and dashboards that can be leveraged across the organization.  It’s a great win/win situation. 

Of course, the key to the success of this matrixed approach is getting the right people across IT and the business working together.  The BICC developers and the business team they are working with need to be collaborative, responsive and adaptable.  They all need to be strong in the areas of critical thinking, problem solving, execution, rapid and iterative development, and communication.  And, they need to understand the value that this matrixed organization can bring.

This approach ensures that there are enterprise reports and dashboards that people in the organization, including senior leaders, can continue to rely upon as “certified”.  Every organization requires a certain level of robustness and operational repeatability and auditability.  However, the organization is not limited by what this BICC can do.  Individuals across the organization can freely explore data and develop great information to drive innovation. 

This is the first of several articles that will explore ways that an organization can encourage a business / IT partnership that will improve that balance of structure and flexibility organizations struggle with today in the world of data and analytics.