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Data governance campaigns should be fluid and pragmatic. In this blog, learn how to make the process frictionless and easy to understand.
Highlights
- Data governance campaigns should be fluid and pragmatic to make the process frictionless and easy to understand.
- Successful governance projects begin at the start of the project and work in the background to ensure high quality and secure data throughout the entire organizational analytics lifecycle.
- The three keys to success are collaboration and communication, executive sponsorship, and a shared understanding and motivation to succeed.
Governance of any form or fashion has long been the word that saps the life out of most projects.
Largely because governance considerations were far too onerous. They slowed work and were brought to the table too late in a project, which ended up putting the brakes on delivery momentum.
Like it or not, people are likely working with data in an ungoverned manner. Whether this is due to a subpar governance system or lack thereof, people will find workarounds to obtrusive processes. Fluid beats rigid.
Companies need to invite these people to apply governance principles to their work without the risk of progress being stymied. Usually, this works out in one of two ways:
- Working iteratively with them to implement unobtrusively and show them how pragmatic governance can accelerate their work in the medium to long term.
- Leave it be and they go back to their usual way of doing things.
If the latter happens, then the organization is no further ahead and will likely fall further behind if they do not commit to coming up with a framework that balances implementing governance iteratively with work that is happening.
If organizations implement by infusing pragmatic data governance into analytics processes, then the guidance can be an enabler of speed and agility. If not, fluid beats rigid, and companies are left holding a stack of policies and procedures that are destined for the bin.
This article will cover the many facets of governance. We will start by defining the process, then covering some of the challenges with implementing a pragmatic governance strategy and how to get started in your organization.
Sections
- What is data governance?
- Why do we do governance in the first place?
- Challenges of data governance
- What does pragmatic governance look like?
- Governance Program Management
- Start, Iterate, Adapt, and Grow
What is Data Governance?
Data governance is a set of organizationally agreed-upon principles and practices that are used to ensure high quality and secure data usage across the entire organizational analytics lifecycle. This is so that organizations maintain accuracy, consistency, and control over their data.
There are many different industry definitions of what governance is and what it is trying to accomplish. Some of them can get quite wordy and academic, but let’s examine two top ones here:
DAMA International defines data governance as “the exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets.”
The Data Governance Institute defines it as “a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.”
Put simply, data governance aims to produce high-quality data that is used securely by the right people.
An effective governance strategy works throughout the entire data lifecycle, from its initial generation to its distribution and reuse, or eventual deletion. It is working to ensure data is:
- High quality: There are two main criteria for quality. The information must be fit for its purpose and it must accurately represent the real-world construct for which it was collected. High-quality is accurate, consistent, and timely.
- Secure: Sensitive data must be secure to prevent it from falling into the wrong hands. Data security is achieved by maintaining privacy, confidentiality, and regulation.
- Readily available: Data shouldn’t exist in a vacuum. The right people must be able to easily access it to make informed decisions based on the latest information.
Why govern in the first place?
Many organizational problems can be traced back to poor quality data. Whether that means a lack of access, inaccurate, or insecure data, poor quality can cause confusion, mistakes, and, ultimately, waste time.
A McKinsey study found that an estimated 30% of employee time is wasted on non-value-added tasks due to poor data quality and availability.
Data governance extends throughout the entire organization and externally as well. The main objectives can be broken into internal and external goals:
- Internal: Governance should clarify processes and principles for managing data. This should prevent confusion and misunderstanding. Creating unified terms, definitions, and business rules enable teams across the organization to easily work together using a shared understanding of data principles. Additionally, data access should be controlled so that only those who need to use the information can access it and those who don’t cannot.
- External: If sensitive information gets into the wrong hands, there can be severe consequences. Governance prevents sharing data with people who shouldn’t see it. For example, no business would want marketing analytics to get into the hands of external competitors.
Challenges of Data Governance
Governance projects can be challenging when teams try to do too much and expect to have all the answers before anyone starts. Eventually, frustration leads to participation drop off, and people are back in their silos. In other words, a project that is too big and fast (or some may argue slow) is a recipe for failure. The business needs to move forward, and governance cannot be seen as slowing progress.
Another big challenge organizations face is getting the senior-most level of leadership in an organization — CEO, CIO, and COO — to prioritize and provide funding for governance. Without such support, governance remains an IT project with little business value, as it will likely compete with other projects for priorities within IT’s limited budget.
Additional challenges that governance projects may face include:
- Putting off governance until the end of a project: Instead, governance should be baked into the project from the beginning to keep everything running smoothly.
- Lack of access and documentation: The right people must be able to access key information without going through countless approvals or overcoming needless barriers.
- Working under rigid standards: The project must be able to adapt, iterate, and grow to meet changing needs.
What does pragmatic governance look like?
“Water is fluid, soft, and yielding. But water will wear away rock, which is rigid and cannot yield. As a rule, whatever is fluid, soft, and yielding will overcome whatever is rigid and hard.” ― Lao Tzu
At Iteration Insights, we often use this Lao Tzu quote to emphasize the importance of pragmatic governance campaigns. While data management and security are a top business concern, there are plenty of other processes in place that keep the business as a whole running. To prevent further amplifying confusion and misunderstanding, a data governance campaign should be fluid rather than rigid.
Rather than creating a bunch of rules that can become obtrusive (and people always figure out a way around the rules), a fluid governance campaign can adapt and grow to keep things governed and secure.
Governance Program Management
Here is the shortlist of what, exactly, should be governed:
- Decision Rights
- The Data Itself
- Access to data
- Who can use it?
- How they can use it?
- Corporate library
Start, Iterate, Adapt, and Grow
Where is a logical place to start? Start simple and prove the value first. Be prepared to make mistakes and change. We recommend baking pragmatic governance early and often to make the process frictionless and easy to understand.
Here are a few guiding principles to ditch the bureaucracy and start any governance campaign off in a low-fi manner:
- Corporate library: Start by establishing terms and definitions so that everyone in the organization is on the same page.
- Document the process: Create a spreadsheet, SharePoint list, or any document that can be found, is searchable, and has accurate data.
- Establish value: Do not move to a more formal management system until you understand the process and people see the value first.
- Track features and functions: Once you start a governance project, keep track of features and functions that you would like to see in a more formal tool (i.e., Iterate your way to a complete requirement set).
- Establish a team: Ultimately, everyone in the organization needs to participate for pragmatic governance to work. Business analysts in charge of governance campaigns should be good documenters, good questioners, and not afraid of controversy.
- Iterate, adapt, and grow: Add more breadth of attributes as needed. Add more depth of information as subject areas are onboarded to the Center of Excellence.
It can sometimes be a long road to measure progress. The best thing to do is to develop a starting point to get the discussion going. All of our governance projects are guided by the following keys to success.
Three keys to success
- Collaboration and communication
- Executive sponsorship
- Shared understanding and motivation to succeed
Conclusion
Data governance is a long game. The most successful projects undergo a very slow, subtle change with many iterations along the way. The benefits will not necessarily be felt for a few months (if not longer), but once the culture of data governance is felt throughout your organization, people will start to see the value.
