This blog is part one of a series of Top Data Trends for 2023.
SUMMARY
Most data governance strategies fall within a spectrum of data openness (sometimes called "democratization") on one side versus data defense on the other. Defending data from loss or theft is important but an overly restrictive approach negatively impacts flexibility, adaptability and decision making. An open or democratic approach offers greater freedoms but places greater burden on the user to ensure that: A) the data is accurate and B) they take measures to prevent the loss or exposure of this data.
Finding the right balance is one of the Chief Data Officer's most difficult tasks and it will likely require making significant structural changes to how data is governed. The payback for this effort is a more flexible and adaptable organization as the use of data drives decisions and decisions are what drives change.
With challenges on the horizon from both an internal perspective (such as growing data volume and complexity) and from an external perspective (such as increasing economic pressure), CDOs will find themselves in a losing battle if immediate steps are not taken to address the growing governance challenge.
Open or Democratized versus Defensive Data governance
What is Defensive Data Governance?
A defensive data governance approach is one that focuses on mitigating risk by maintaining a high degree of centralized control. This control not only attempts to protect data from theft, it also seeks to maintain a high degree of data integrity. CDOs who focus on the defense are better equipped to meet new regulatory requirements (GDPR, HIPPA, etc.) and are better equipped to make wholesale changes. Industries that face increasing regulatory pressure, such as healthcare or financial services, are more likely to take a defensive data governance approach.
Defensive data governance strategies include:
Preventing data breaches and cyber attacks
Mitigating operational risks
Meeting industry regulation requirements
Improving data quality
Minimizing ad-hoc IT purchases
Defensive data governance challenges:
Lower adoption / less data-driven decisions
Slow response rates
Greater bureaucracy
Increased dependence on specialized skills and tools
What is Offensive Data Governance?
An offensive data governance strategy seeks to maximize the return on investment from the data collected and procured by the organization. Offensive data strategy tends to be driven by executives that wish to capitalize on current market conditions. For data to reach its maximum value it must be wielded at the best possible time. For offense-minded CDOS, data is the tip of the spear that drives the business forward.
Offensive data strategies include:
Empowering business stakeholders with rapid access to information
Leveraging data to create new products and services
Using data to drive increased revenue or customer acquisition
Monetizing data assets
Taking advantage of real-time analytics
Offensive data governance challenges
A lack of consistency
A proliferation of spreadsheets (which represent risk to the organization)
Stovepipe or one-off solutions / less reuse
An increase in tooling - creating greater complexity
What is Unified Data Governance?
A unified data governance approach attempts to balance offense and defense by focusing on the structural changes that need to take place to offer both greater control and at the same time greater flexibility. A unified data governance approach is very realistic and can produce tremendous return on investment. If done right, the organization can expect greater collaboration and greater user adoption. As the unified approach gains traction it begins to provide even greater value over time.
What are the benefits of Unified Data Governance?
A Unified Data Governance approach provides several benefits to the organization:
A More Connected Architecture: One of the biggest challenges in defensive and offensive data governance is that it has to reckon with fragmented and disjointed data architecture. Most organizations see their data pass through many tools, roles, and systems to become actionable and valuable. Maintaining secure control over data flowing through a disconnected network is extremely difficult. Attempting to generate actionable real-time data is extremely difficult for the same reason. A unified data governance approach leverages a more connected data architecture from the beginning, allowing greater visibility and transparency into what is being managed, controlled, and distributed.
Reduced Data Sprawl: A unified data governance approach supported by a connected architecture helps to reduce data sprawl by providing centralized, defensively-governed environments that individuals can access to engage in more "offensive" data tasks, such as data analysis, dashboarding, and reporting. Such settings help to reduce spreadsheet proliferation and the number of data efforts completed in data isolation, allowing data to be more easily managed, improved, and distributed around business objectives.
Improved Data Democratization: When data architectures are connected and appropriately governed, it becomes easier to make environments where quality data is accessible to more users in two ways. First, by making capabilities like dashboards and visualizations, data warehousing, workflows and automation, and governance and administration available in one place, organizations can spin up specific data environments to help serve particular objectives. By creating many of these environments, organizations can help serve the needs of more data stakeholders at a ground level. Second, technological advancements also allow more users to work closely with data without requiring traditional skills or training. With platforms adopting no-code, drag-and-drop, auto-populating data capabilities, data becomes easier to work with for more people.
Transitioning to a Unified Data Governance Approach
A unified approach to data governance helps to effectively balance the needs of both sides without having to make trade-offs between the two. If you are struggling with managing your data due to a defense-heavy or offense-heavy approach, Process Tempo can help you explore a more unified solution through our purpose-built data applications. Our applications leverage common data models overlaid with critical data capabilities like data warehousing, data management, data engineering, and data analysis, all consolidated within a single, easy-to-use platform. In this way, we help provide tight-knit controls around data along with supporting flexible data environments that allow offensive data tasks to take place with ease. Contact us today to learn more about how we can help you make your data tightly controlled yet flexibly used and help you generate value from your data at scale. Talk to sales or schedule a product demonstration >