We are conducting a BICC research study over the next month. If you have any information you would like to share on BICC org structures or any other best practices and/or would like to be a part of this research study, please drop me a line here.
Some of the preliminary content we will be looking at for the research study include:
I would be happy to hear any feedback/comments on this research study, drop me a line on this thread and I will contact you for more information.
Forrest Palmer 270001YU2V firstname.lastname@example.org | | Tags:  bicc data_goverance data_quality bi | 0 Comments | 535 Visits
I often get asked about the importance of having your data in excellent shape - accurate, complete, relevant, etc - before you start using BI. The conventional wisdom, usually in IT, is that the data has to be right or the users will not trust it. Of course, that's true - to a point. The success of any reports, dashboards, scorecards or analytics often rests on the quality and trust people have in the data they see through that BI content. But the reality is that the data is never perfect. The "single version of the truth" (something I question as a goal but that's another day) is a journey that will never be reached 100%. So waiting until the data is completely trustworthy before rolling out BI is a folly that, in fact, will slow down the realization and need for data quality to be addressed where it needs to be addressed - in the business.
The truth is that data quality is often improved because of BI. While the first reaction might be to "blame the messenger" - the reports or tools that were used - the reality is that exposing data quality issues and discussing how to address them is essential to establishing the sense of ownership in the business and the subsequent need for governance programs that will continually improve the quality over time.
To be clear, we cannot build BI on top of truly bad data and expect that to be acceptable. Our data warehouses and data marts must meet a sufficient level of quality to make the use of that data valuable and meaningful. But don't let the quest for "the best" prevent us from starting our journey towards "the better".
Which means we need to move to both a information governance mandate and a BI governance (e.g. BICC) mandate that work in concert and alignment with each other. And that means that our information management strategy and our BI strategy have to be viewed together. Each depends on the other.
And yet too often companies are more focused on one or the other. Some companies start headlong into a BI strategy without any real consideration of the information management strategy that goes with it. The result is a truly failed BI initiative that will struggle to regain credibility. And there are probably just as many companies who invest a tremendous effort on data warehouse design and development, MDM, and data governance with little attention to how the business can effectively use all that data with BI.
So which comes first - the need for information governance and information strategy or the need for BI governance and BI strategy? Chicken or egg?
Tracy Harris 2700026WJ9 email@example.com | | Tags:  community competency business excellence of center intelligence | 0 Comments | 589 Visits
Organizational design around business intelligence and business analytics has been evolving over the last few years. We have seen many different types of formations and naming conventions around the business intelligence competency center (BICC), the Business Analytics Center of Practice, the Center of Excellence. They may be virtual or structured. They may report to the CIO, CFO, the CEO or a line of business. However, in a recent survey by the Business Applications Research Center, it has been found that organizations who have this formation in their organization outperform in every area that was measured.
And, regardless of the exact details of how it is configured, it appears that the most successful design is when there is both a shared service center and a larger community of stakeholders that keep in regular communication. Perhaps is it a Business Analytics Community of Excellence? We would love to share thoughts, organizational design ideas and best practices in this area. How is your organization currently structured for success?