This series of question and answers were prepared for a meeting with a client’s Corporate Communications Specialist. The purpose of the Q&A was to assist her with determining the most appropriate messaging to share across the company. I delivered this series of questions focused on relating their need for an over-arching data strategy with the work that is presently being completed associated with standing up their formal data governance program. The results of that exercise are the content of this article that will be tailored to match the audiences at different levels of the organization.
The series of questions and answers will be customized for the client in the coming weeks and month, but the answers are suitable to share with any organization that is considering the alignment of a data strategy with their data governance program. I didn’t want the questions to be overly technical and I did want the answers to be relatable at all levels of the organization. For that reason, I attempted to keep my answers in layperson’s terms.
What is a Data Strategy?
A data strategy is a thorough plan and policy for moving an organization towards a more data-driven culture. A data strategy is often viewed as a technical exercise, but a modern and comprehensive data strategy addresses more than just the data; it is a roadmap that defines people, process, and technology. The exercise of creating a data strategy is one in which organization leaders take a deliberate look at what employees need so they are empowered to use the data. In addition, processes are examined to ensure that data is accessible and of high quality, and that technology is leveraged to enable storage, sharing and analysis of data.
Why is a Data Strategy needed?
A data strategy is needed because, without a centralized vision and foundation, different parts of the company will view data-related capabilities differently. This inevitably leads to duplication of both data and data systems across the organization and thus makes it quite difficult to determine the ‘truth’ from one’s data while driving up costs associated with operational efficiency and effectiveness. A data strategy provides the basis for enterprise planning efforts connected to data-related capabilities and is a tool that allows for unification of Business and IT expectations for all enterprise data-related capabilities. The more detailed and comprehensive the data strategy is, the better the chance that the business and technical parts of the organization will fully understand each other. There is no better place than a data strategy to define the metrics or service level expectations that should apply across the enterprise. The data strategy is the best place to explain thoroughly how management of enterprise data can be leveraged to support organizational mission objectives or processes. (Portions of this answer were drawn from dataconomy.com)
What are the Components of a Data Strategy?
Commonly, these are seven primary elements of a data strategy. The elements include:
- Business requirements and strategic goals for the organization when it comes to leveraging our data as a valuable corporate asset
- A good understanding of the questions the business is asking that can be answered with data
- Technology infrastructure requirements including the building of a flexible and scalable design of systems and data resources
- The ability to turn data into insights and visualization including the improvement of comprehension and intuitions directed at improved decision-making and story-telling and improvements in operational efficiency and effectiveness
- People and process including organizational structure, skillsets, required strengths and how these things will be supported
- Data governance or what ultimately focuses on employee behavior and allows enterprise level sharing of effective data
- The roadmap of the steps that will be taken to move from the current state to the future state. (portions of this answer were drawn from analytics8.com)
What is Data Governance?
I define data governance as the execution and enforcement of authority over the management of data and data-related assets. Data governance focuses on improving the value of data and information and pertains directly to the way people act when it comes to activities associated with data.
What is Data Stewardship?
I define data stewardship as the formalization of accountability over the management of data and data-related assets. In other words, a data steward is a person with a relationship to data (as a definer, producer and/or user) that is held formally responsible for how they define, produce and use data. For example, everybody that uses sensitive data is a steward of the data as they are expected to follow the rules associated with their handling of sensitive data.
What is Metadata?
I define metadata as information stored in IT tools that improves both the business and technical understanding of data and data-related assets. Metadata can otherwise be referred to as data context or documentation. It is one of the most effective resources used in implementing successful governance of data because it is the information about the data, including definitions, accepted values, location, who is responsible for the data as well as anything else that can be leveraged to improve usability, confidence, understanding, quality and accessibility.
What is the Difference Between Data, Metadata and Information?
Consider the equation that Data + Metadata = Information. Data is the content of a specific field – for example “15217.” This number could be a quantity, an instrument setting, a zip-code or a measurement. The Metadata about that Data tells us that “15217” in this field of data is “Headquarters-Zip-Code” (the name of the data field), that the data is 5 positions in length, and that the values follow the standard postal codes used by the United States Postal Service (USPS). The information is that this specific zip-code is the physical location of the company headquarters in Pittsburgh, Pennsylvania, where employees are located, and that is used for tax purposes. When you take the pure data and add the metadata (context or data documentation), the result is that the data is now information that can be utilized for business purposes.
What is the Difference Between Data Governance and Data Management?
Data governance focuses on people’s behavior associated with the data while data management focuses on the activities of delivering data and metadata to individuals across the company through a variety of disciplines including Metadata Management, Master Data Management, Data Science and Analytics (to name a few). Data governance concentrates on formalizing people’s conduct for how data is defined, produced and used while data management focuses on the disciplines associated with providing effective data to your organization’s staff on time and within budget.
Why is it Important for Your Organization to Have a Data Strategy and a Formal Data Governance Program?
Because it is better to have an overall plan for how to approach significant organizational change than it is to attempt to make these changes independently and without structure and resources. Data strategy includes the components mentioned in the earlier answer (in the list) and pertain to the data, systems & applications, building out the necessary expertise, knowledge and skills, and the delivery policy and process required to move from the current state to the future state.
Why is Data Governance an Integral Part of a Data Strategy?
Data governance is an integral part of data strategy because it focuses on the people and behavioral aspects of the strategy, the formalization of accountability for the management of data, improvements in organizational data literacy (enabling people to recognize and treat data as a valuable asset), the reduction of data-related risks, and assuring that data rules, both internal and external, are followed.
Why Should You Care About Your Organization Having a Data Strategy and a Data Governance Program?
The data of the organization is a valuable tool to enable improvements in product development, customer interaction and satisfaction, quality improvement and impacts the organization’s bottom line in terms of decision-making, and improvements in quality, efficiency and effectiveness. Everybody, at all levels, must recognize that your organization’s data governance program will enable you to strategically manage data as an asset to achieve accurate, trusted, and secure data that delivers business intelligence focused on leveraging and building a competitive advantage.
What Will the Impact be on the Organization and on You and Your Role Specifically?
The impact on the data of the organization will be significant. Employees and partners will benefit from everything stated as the purpose of the data governance program (in the previous answer). The impact on individuals roles will depend on people’s present relationship to the data, however, the intent at your organization is to take a less pervasive approach that aims to minimize disruption to normal business activities. Individuals that define data will become educated on the aspects of data definition that drive improvements to the organization’s confidence in the data they use. Individuals that produce data will become educated in quality data production including timeliness, accuracy, completeness and relevance. Individuals that use data will become educated in how to determine how the data is defined, produced and intended for use. Data users will also become educated in the business and external rules associated with handling sensitive data. The impact on your role specifically will be based on how closely you follow existing standards for data definition, production and usage in comparison to what will be expected moving forward. It is worth restating here that the intent of your organization’s data governance program, if you follow the Non-Invasive data governance™ approach, is to be less threatening and easier to adopt than traditional methods of governing data.
Where Will You See Improvements Related to a Higher Level of Confidence in the Data?
Confidence will be improved in several ways. One way is through improved understanding of the data as the definition, including description, values, ownership, and business rules about the data, becomes more consistent and easier to access. Another way confidence is improved is through knowledge of what data exists, where the data resides, how to gain access to the data and who is responsible for (or the owner of) the data. A third way that confidence will be improved is through the knowledge of, and access to, the policies that are associated with the data including privacy laws, compliance laws, and ethics and fair use rules. The last way to be shared here is through the knowledge that your organization has formalized its approach to managing our data and that you are paying close attention to how the data is being governed to improve your competitive advantage and efficiency and effectiveness.
So … how did I do? Does this set of questions with answers begin to address the alignment of the data strategy with the need for data governance? Or did I miss the mark? Please consider leaving comments as to how you were able to relate the subjects and also share which of your messages translated into effective communications for the different audiences across your organization. We can all learn from each other.
