We are all aware of the need to define our Data Governance (DG) terminology, so let’s start there. What we mean by adoption does not fit the academic or literal dictionary definition, which is to agree, approve, or accept. Let’s consider the definition of adoption from the outcome we desire to drive. Effectively, the outcome of adoption means to have all the right people in the organization leveraging the right processes on the right data, at the right time using the right technology. We’ve all heard that mantra, right?
Through DG adoption, we are seeking a change in the behavior of our business and technical resources. Additionally, we desire commonality in the processes people use to create, manage, and increase the trust of data. We desire change in how people identify and access data, how they consume data, and the technical usage capabilities those resources use to support those DG processes.
The simple definition of adoption for most organizations is: to have another team of business and technical resources follow the governance processes established, using the supporting governance technologies that have been established. This allows us to look at adoption as an expansion of the governance program either as:
- Expanding the breadth of content by implementing a new domain of data using existing resources
- Expanding the depth of content by implementing additional capabilities for existing content such as capturing data quality rules and metrics or certifying authoritative data sources/reports
- Expanding the breadth of the governance program by implementing a new business use case and associated business resources into the governance program.
If only implementations were that simple. So why is adoption such a complex challenge to the majority of Data Governance teams? Often the answer is that we have not positioned the program for success at the outset.
I don’t mean to suggest that Data Governance adoption is just a “people problem.” It’s not. The challenges facing most organizations include:
- Adoption of data governance concepts and standards such as data principles (cultural change)
- Adoption of governance roles and responsibilities (change to individual activities)
- Adoption of the processes, standards, and best practices (change in how we interact with others)
- Adoption of the technology and standards (technology change)
- Adoption of data quality process to increase the trust in data (change in activities)
- Adoption of data usage practices and standards (change in how we interact with data)
Solutions to our adoption challenges start with the Data Governance Strategy, or publishing Data Principles and building a Data Governance organization that includes executives and leadership from all lines of business. Communicating to the organization about the Data Governance program early and often, can help to overcome many of the barriers inhibiting adoption. We have found that adoption is much easier for the organizations that actively communicate, educate, and promote the data governance program – something many data governance teams do not focus on at all.
Common Solutions to Increase Adoption
Many data governance programs start with very limited exposure in the organization. Many start as an IT skunkworks project. While this can have positive considerations, it can often lead to the root cause of our adoption challenges. It is recommended that we assess the barriers we have in our organization as a first step in determining solutions specific to the challenges we face.
It is common that we can classify the adoption solutions into three types as follows:
1. Organization and Communications
Lack of participation in or agreement of all business units in the governance program. Often the governance program starts with just a single business unit involved, which limits enterprise-wide involvement, communications, education and understanding for the value of data governance. An objective to fix just one business challenge – such as a new government regulation like GDPR – hinders our future ability to achieve program adoption. Obviously, each data governance implementation needs a focused scope. However, the stated objective of just a single implementation will make the adoption of a second implementation a difficult challenge. Adoption is always greater when communications and education is completed with all business use cases and data citizens in mind. Every day is an opportunity to communicate and educate everyone in the organization about the value and benefits of governance.
2. Education and Training
Lack of education and training of all data citizens (all those who use data in their jobs) will impede the ability for everyone to understand why change is needed and how it affects them. Most data governance programs have to address a change to the culture of the organization. To enable a “data driven” culture will require changes to the roles, responsibilities, processes, and technology. Changes in the data usage processes and how data provisioning will occur requires education – generally bottom up education. Improving the quality, accessibility, and trust in data will require not just education but training in the newer processes and technology. Adoption is easier when all data citizens understand all roles and responsibilities as well as the overall objectives and benefits of data governance. Why data governance is important to each individual (“me”) is an important consideration in your governance educational program.
3. Business Use Case and Value Understanding
The lack of a governance strategy that identifies the value and benefits of multiple business use cases can paint a governance program into a corner, stagnating adoption (at least until the paint dries). Again, if there is only one stated objective, adoption by a second business project will be more difficult. Do not let your data governance program be a one hit wonder. Now no question, it is critical to address the highest priority business challenge first. Over the last 3 years, the industry has seen multiple new government regulations fuel data governance programs and even the creation of the Chief Data Officer in many organizations. This momentum will likely continue into 2018 with the implementation of GDPR regulations. Yet, we have seen many governance programs stall once that single objective is met. Too many ask “now what do we do, what will be the next business unit to be included in the program, how do we communicate the value and benefits of data governance to them”? You do not want to be the program asking that question. Your governance strategy should be aligned with the business strategy so you remain relevant with the on-going business programs.
Consider those that are early in their maturity, say just starting out or just completed an internal POC for infrastructure implementation. Your adoption challenge is to get the first business team active in the governance program. For many organizations, the first governance activities will be around a regulatory reporting use case. The scope of the project activities and the associated resources will be limited. This scope and focus is important to reduce the risk of failure. However, if communications, education and promotion is not done for the governance program, even the successful implementation of the first project can lead to adoption challenges. We often see governance programs stall after the first project success due to a lack of business use cases on the roadmap, as well as the lack of communications, education, and promotion for the program across the enterprise.
Now let’s consider the governance programs that have had one or two wonderful successes. Your adoption challenge will be to increase the depth and/or breath of your business implementations. We see many adoption struggles with governance programs in this state of maturity. This may be the case where we have completed governance activities around one business unit, maybe Finance or Risk Operations or Actuarial. Solely focusing the data governance program on a single business unit, maybe even calling them the sponsor of the governance program, will lead to adoption challenges. Not having a cross-function of business unit executives on a sponsorship committee will limit the communications, education, and program awareness. Data Governance needs “champions” from outside of the governance team to promote the value and benefits of governance. Generally, our “champions” will be from other teams, either business or technical. Champions will be an effective weapon in the war on adoption.
Adoption solutions vary depending upon the governance maturity and culture of the organization, the business use cases behind the implementation efforts, and the desire for organizational cultural change. Finding great champions in the business or partner teams will provide significant benefits for adoption. Having someone outside of the data governance team discuss the value and benefits of governance will be your greatest ally against adoption challenges. Please recognize the importance of communications, education, and promotion of the data governance program. And as always, stay calm and allow your data governance program to prosper.
