This is the second post in a two part series on how Perficient helped to support ProHealth Care in operationalizing their BI program, data governance, and the Business Intelligence Competency Center. In the first post, I talked about the workstreams and the roadmap. Below, I’ll cover the members of the data governance steering committee as well as the initiation of data governance and data governance priorities.
The anatomy of a data governance committee
One of the first things I’m often asked when I’m engaged in the delivery of a roadmap around data governance, is “Who should be on the data governance steering committee?” Because of that, I thought it would be interesting to share with some highlights from ProHealth Care’s governance oversight team.
We have senior executive sponsorship of the data governance program that I can’t emphasize enough – it is critically important. In this case, the Chief Innovation Officer is our executive sponsor.
The committee chairs are driven by both IT and Performance Excellence, so that gives us good representation across IT and Business domains. We have a good cross section of representation from Finance, HR, Operations and clinical domains, with respect to our standing members (some of which are data owners, some are data stewards, others are key stakeholders and decision makers).
We also have representatives from the BICC that sit on the data governance committee, and this is to provide a bridge between data governance and the tactical operational execution of the decisions the data governance committee makes.
We also join in ad hoc members, data owners and data stewards, and enable work groups based upon the specific initiatives we’re trying to address at the time.
Data governance initiation and priorities
So what did we do to initiate data governance? Well, as I mentioned earlier, we actually started with the fundamentals, and that’s the charter and scope and the guiding principles on which the data governance committee would make decisions.
What we defined are scheduled activities, and we put some definition around the voting and decision rights. This particular committee does not only serve in the role of data governance but also serves as a steering committee helping to inform data strategy and make decisions about prioritization of BI projects. This means they get involved in prioritizing project requests. They also are principally involved in address data quality, information assurance concerns, and approving business metadata. The business terms and definitions are defined and stored within a business glossary, so that the information may be used and referenced universally across the enterprise, to facilitate the appropriate use and interpretation of data.
We started with policy development because it’s necessary to encourage the desired organizational behavior with respect to information security and data classification, and things like data quality and life cycle management, thus they were foundational to this initiative. There’s not a lot of focus around change management, stakeholder engagement and communication, because this is such an enterprise wide initiative that we had to make sure we have appropriate change management around the activities. We also had to make certain that we’re engaging our stakeholders by showing them, and communicating with them, what they can expect particularly as it relates to the Microsoft BI stack and the capabilities within that platform the potential for self-service business intelligence.
When it comes to priorities:
- We focused on policies.
- We established the role of data stewards, to ensure that data was properly defined and used throughout the enterprise.
- We focused on developing of business glossary and data dictionary.
- We highlighted and isolated who the data owners and stewards by doing a survey.
- We also set in place some training for data stewards and staff from the BICC, to help guide them in their new roles.
- We’re in the process of defining a release master plan that puts the release strategy into six month intervals.
- We also developed a data quality management plan that the data stewards and personnel within the BICC could use to guide them in performing data quality assurance.
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Pertaining to the vision of responsibility, the data governance team is really focused around defining data governance strategy, policy and standards, whereby the BICC is more focused around delivering the operational capability and taking the guidance from data governance and actually applying that into the day to day operational issues.
What about the Business Intelligence Competency Center (BICC)?
The BICC is responsible for promoting the optimal use of business intelligence across the organization. It is the centralized organization at ProHealth that helps to drive and support the overall information delivery and BI strategy. It has representatives from both Business and IT, so again, good cross representation. And because it’s centralized, it also enables the organization to coordinate a lot of complex and competing efforts. Since it’s not distributed throughout the organization, it helps reduce some redundancy and therefore increase the effectiveness.
The BICC’s responsibilities include education, support, training and development. They also provide ad hoc end user support. They handle the intake and prioritization process for BI requests, and escalate those to data governance if appropriate. The BICC is involved in a lot of requirements, prototyping and application development, and collaborate with the data stewards around business metadata, quality assurance and governance initiatives.
Examples of the initial deliverables at ProHealth as it relates to operationalizing the BICC includes:
- Putting in place the right organizational structure and define the roles of the participants.
- Establishing a process for new requests, how we are going to prioritize those, to what extent the BICC could make the decision and act on a request, and what needed to be escalated to data governance or IT steering committee for their review.
- Building and maintaining the business offering as well as the technical metadata, and selecting the tools that we would need to manage metadata.
- Establishing the help desk and support functions for BI related issues.
- Forming the BI and data warehouse development team, so that they could actually execute on operational requests as well as deliver against Phase I requirements. We now moving into Phase II.
- Early stages of developing the release master plan.
- Developing a data quality management plan, which provides a guide to people in the BICC and data stewards in terms of how to perform quality assurance.
Source: How to Define and Run a Successful Business Intelligence Competency Center, Gartner, August 2007
So that concludes, on a high level, what we’re doing in terms of program data governance and the Business Intelligence Competency Center at ProHealth Care. If you want to learn more about how ProHealth Care is using Epic’s Cogito data warehouse to innovate in population health management, you can read the case study.