Michigan has been hit extremely hard in this recession. Obviously, the U.S. auto manufacturers and parts suppliers have been hit the hardest. But some of the smaller manufacturers aren’t getting as much press. A triple-whammy has hit one furniture manufacturer right between the eyes. They sought practical advice in data governance (DG) to resolve, once and for all, data issues that are reducing productivity, sapping time and expense, and contributing to regional power struggles as the company evolves to manage in a truly global fashion. Starting with the assumption that data governance will be a permanent set of processes that will start small and adapt over time, this company acknowledged that they could not afford to tolerate the waste and frustration of data quality issues that are eroding their ability to anticipate changes in the marketplace and perform competitively in a permanently changed economy.

The Scenario

A decade worth of corporate downsizing among large global corporate purchasers had already limited production targets, before the global recession dried up potential sales even further. Layoffs to compensate for reduced profit margins represent 40% of the original workforce, with those approaching 30+ years of service being offered early retirement severance packages. Manufacturing plants have shut down, overhead positions have been consolidated, and fewer people are required to do more with less. Starting 17 years ago, the company undertook a common ERP platform standardization effort, and these efforts have been paying off; however, they are revealing significant regional and departmental gaps in data definitions as well as business usage. The move toward global operations, with shared services located in Asia/Pacific, Europe and the U.S. (including Mexico and Canada) has intensified the need for common business processes, shared data and well-understood definitions. The crowning piece of this trifecta is that as a significant part of their workforce reaches retirement age, these workers are not being replaced by younger employees who are willing to stay long enough to learn the ropes. Once the recession eases, how will this Michigan town, where housing values have fallen between 30-40%, where schools are closing and local revenues for other social services are drying up, attract and retain a younger, skilled workforce willing to make a career here?

You might assume that the staff would be demoralized, just waiting for the next punch in the gut. But that’s not the case. Midwesterners are a resilient bunch, and these folks are keenly committed to product diversification, global innovation, and adapting to a whole new business climate they feel will be with them for the foreseeable future. Managers and directors regularly fly 18+ hours to meet with regional offices in Malaysia, Europe and Mexico, showing up in the main office just hours off the flight. The Michigan office routinely entertains staff guests from divergent global locations. This Michigan headquarters is beginning to look like a mini-United Nations. And they are firmly committed to making data governance work.

We were asked to help them recover from a data governance effort gone awry. With all the justification from the best sources, and a well-planned effort to get governance underway, the project had fizzled almost instantaneously. While leaders had identified all the right reasons for data governance and had identified the team to work on high priority issues, the data challenges were too complex and the specific tasks and duties were too vague. Our challenge was to bring “just enough governance” to a “Lean” manufacturing culture, starting with the company’s most global resource: the Human Resources Department.

The immediate conundrum facing us was how to bring a set of “best practice” recommendations to an environment that clearly has little patience with heavy-handed consulting dogma. Regardless of the fact that on several occasions, we heard, “We hired you for your experience with other companies” and “We need to know best practices,” we also heard, “That will never work here – our culture is really different.” We needed to recommend a solution that “felt right” to this group, something that fit with a culture of innovation and that balanced formal processes with agile decision making and clearly measurable results.

The Solution – Part I

Well, they asked for best practices, and we gave it to them. We called it (jokingly) “The Data Governance Bible” because it was a thick, dense and meaty package. When they saw it, that deer-in-the-headlight look appeared in each of their faces. “But how do we implement this?” “This is great, but how can we right-size it so we know where to begin?” “But we don’t have enough people to do all this!”

So, what was in that DG bible? “Exactly what we asked for,” said one of our sponsors. So let me take you through the specifics, and then I’ll tell you how we made it work.
The Data Governance Reference Guide that we prepared is a comprehensive soup-to-nuts set of materials that detail each component of a successful data governance program. This includes:

• Data governance vision statement
• Principles and objectives
• Governance structure
• Roles & responsibilities
• Stewardship engagement model
• Procedures for effective decision making & documentation
• Support elements for:
• Designing performance measures
• Assigning responsibility for security and access rules
• Assigning responsibility for a communications plan
• Dealing with non-compliance
• Developing a metadata management strategy
• Addressing retention and archival issues
• Accepting third-party data
• Acknowledging external compliance and reporting requirements
• Designing a set of training modules and stewardship workshops
  

In addition, a detailed set of appendices provided hands-on examples of:

1. Each governance process and specific handoff points using swim-lane diagrams
2. Data governance glossary of terms
3. Suggested templates for committee agendas and meeting minutes
4. Suggested templates for a data governance project charter
5. Suggested templates for policy requests, policies and waiver requests
6. Survey for initial governance metrics to serve as benchmark over time
7. Sample data quality plan
8. Sample metadata management plan
9. Data governance maturity model
   

This set of documents is intended to be their set of resources as they move governance forward. It provides foundational materials with which to get started. These materials provide both a framework for the structure of governance specifically for the Global HR Department, and tools with which they can measure their progress and track specific decisions that have been made by the stewardship group. As data governance matures within Global HR and spreads to other departments in the company, those groups can use these resources and modify them as they want. As such, these documents are  “living documents” that will grow and change as necessary, with use.

The Solution – Part II

Once the team had a chance to digest the Data Governance Reference Guide materials, we administered a calming antidote in the form of a Data Governance Road Map.


This road map clearly identified 5 phases of implementation, starting with “standing up” the governance leadership team and the governance organization to identifying and training data stewards, and through developing long-term processes for building a data quality plan and a metadata management strategy. This is truly what crystallized our success on this project, especially due to the previous failed attempt at data governance. The road map gives clear expectations for what needs to be accomplished in the first 30, 60 and 90 days, and will serve as a template for the next groups once this team is ready to pass the baton forward. Used in conjunction with the reference guide, clear roles and responsibilities are detailed, and clear process expectations are presented. If there is slippage in the team’s progress, then specific accountability, as spelled out in the reference guide, can be identified.

Keys to Success

We are clearly not done working with this company yet. We will help them develop their training curriculum and attend the first stewardship workshop to provide subject matter expertise. But we are confident they will succeed this time, and here are some of the key reasons.

1. IT is coordinating the data governance effort, but only to expedite the process. Business will truly “own their own data,” especially because this is one of the driving reasons for data governance. IT has suffered enough staff cuts that they can’t afford to be a middleman between those using data and those collecting the data. While they can recommend tools and techniques, they need to get out of the role they have historically played as arbiters of data problems.
2. The person in charge of managing the whole effort will start with the HR Data Governance Council, which is the governance workgroup made up of all the data stewards, and will then transition coordination efforts to additional Data Governance Area Councils. There will be an Area Data Governance Coordinator identified for each department when they are ready to start identifying and prioritizing data issues for governance. This way, the Data Governance Manager will have the authority to ensure that governance meetings are happening, without the responsibility of being “down in the weeds” with each workgroup. 
3. Leadership is truly enthusiastic and on board. During our final presentation, we heard from the VP of Human Resources: “I’m ready to roll. If we don’t try, we won’t learn. We’re ready – let’s do it!” From the CIO we heard, “This feels right, this looks good.” They are willing to make the case to their managers and staff that establishing data ownership will truly empower everyone to make better fact-based decisions. The Critical Thinking Model is actively promoted as part of this culture.
4. The IT Oversight Group has already established a baseline set of metrics that can be enhanced as work begins. The manufacturing focus of this company emphasizes measurement of everything they do, and metrics will be central to monitoring progress and demonstrating success. They acknowledge they will need to have measurable proof of success before they will be able to get other groups on board.
   

While their work has just begun, at least they feel there is a solid set of foundational materials that they can use to get them started. Certainly there will be hurdles and resistance, but with honest Midwestern relentlessness, I’m convinced this time they will succeed.

SOURCE: Data Governance from the Ground Up: A Case Study