What do you do if your data governance framework needs to incorporate new technology?

In the complex world of data governance, introducing innovative technology presents challenges and opportunities. Technology should be integrated into an existing data governance framework, focusing on the need for collaboration and detailed planning. The process starts with a thorough impact assessment. This critical first step evaluates how the technology aligns with strategic goals, affects data quality, security, compliance, and alters the data architecture. It's like mapping out a journey in a digital landscape, preparing for any challenges and opportunities ahead.

In my view, everything goes back to the basics. How this new technology would impact to the current eco system. That determines the level of adoption and other associated steps have to the incorporated as part of adoption. It’s also dependent on current threat profile and appetite of the organization.

Integrating new technology seamlessly into your existing data governance processes and workflow may involve updating policies, procedures, and tools to accommodate the new technology. However, before doing so, it is essential to evaluate how the new technology will impact your current data governance framework to ensure that it aligns with your organization's data governance goals and objectives

To integrate new technology into your data governance framework follow these steps: 1. Ensure alignment with overarching business objectives to drive value and prioritize initiatives. 2. Start with incremental implementations to mitigate risks and accelerate value realization. 3. Measure and communicate the impact of new technology implementations to stakeholders. 4. Empower business leaders to lead data governance initiatives and ensure accountability. 5. Embrace an agile mindset to adapt to evolving technology landscapes and business needs. 6. Seamlessly integrate new technology with existing systems and processes. 7. Maintain data minimalism by focusing on capturing and leveraging essential data for strategic objectives.

One of the key technology aspects to consider is the impact on the DG Framework and the migration of the existing assets to the new technology. Quite often there is a lot of customisation which has been done with an existing technology and tool and one key technology consideration is what can be OOTB and configured as against getting into more complex customisation again. Customisation always comes with a lot of maintenance overheads. It is also very critical to back up all the metadata and assets and review them with the Data Stewards before decommissioning the older system.

Updating data governance policies is similar to renovating the core framework of an organization to accommodate next-gen technology. For a non-specific, yet insightful example, consider a healthcare provider overhauling its data management systems to integrate advanced analytics for patient data. This required a delicate balance of enhancing data accessibility for improved care, while strictly adhering to privacy laws. They redefined their data governance model, ensuring secure, compliant use of data analytics tools. This transformation didn't just align with regulatory standards; it revolutionized how patient care is informed by data, setting a new benchmark in data governance that is both forward-thinking and grounded in patient privacy.

In updating data governance policies and standards to reflect the new technology, it's imperative to ensure alignment with the organization's strategic objectives and industry standards. This involves not only addressing compliance with existing regulations but also anticipating future regulatory requirements that may emerge with the adoption of new technology. Moreover, considering the evolving nature of technology, it's essential to build flexibility into policies and standards to accommodate future advancements and changes. Additionally, fostering a culture of continuous improvement by soliciting feedback and regularly reviewing and updating policies can help ensure that the DG framework remains relevant and effective in the long term

I would suggest to train the stakeholders before the policies are updated. That could give us nuances to be included in the updates.

While assessing the impact of any new technology, pause and think about the different types of data being shared and the level of sensitivity. If mishandled, both personal and sensitive data may trigger legal implications due to unauthorized or unlawful use. Make sure that everything is strategically and ethically collected while being continuously reviewed and sense-checked by data governance specialists. Ensure that everything is compliant to both local and regional laws while establishing clear roles, accountability, and ownership throughout the organization. Upskilling your workforce in terms of both the new technology and the updated data governance policies and standards is the only way to prepare for any regulatory scrutiny

In my experience, update the data governance policies and standards to reflect the changes brought by the new technology, ensuring compliance with legal and regulatory requirements, and aligning with organizational data strategy and objectives.

By following these steps, we can smoothly add new technology to our data governance framework 1.Understand the New Tech: First, learn about the new technology to see how it fits with our data governance goals. 2. Find Integration Points: Figure out where and how the new tech will work with what we already have. 3. Update Policies: Make sure our data governance rules and procedures include the new tech. 4. Train Everyone: Teach the people involved in data governance how to use the new technology. 5. Keep an Eye on It: Set up ways to watch how well the new tech is doing in our data governance plan. 6. Keep Improving: Keep checking how the new tech is working, and make changes to make it better if needed.

Stakeholder empowerment is essential for successfully integrating new technologies into organizations, much like equipping explorers for a journey. This involves providing detailed knowledge and tools for understanding the technology's functions, benefits, and limitations. A key example is the introduction of an Electronic Health Record (EHR) system in healthcare organizations, where extensive training programs, including workshops and simulations, are conducted for all staff levels. Such preparation ensures the workforce is familiar with the system's capabilities, highlights how it can improve patient care, and addresses operational issues.

Clarify Technology Usage: Explain the technology's purpose, benefits, and limitations relevant to their roles. Learning Objectives: Define clear learning goals for understanding and applying the technology. Training Materials: Develop diverse materials like guides, videos, and interactive tutorials. Training Methods: Use varied methods like workshops, online courses, and hands-on sessions. Delivery Channels: Choose accessible channels for training, such as webinars or in-person sessions. Assessment and Feedback: Include assessments to gauge understanding and gather feedback for improvement. Ongoing Support: Provide continuous resources and support for deeper learning and application.

Provide training and education to relevant stakeholders on how to use the new technology within the data governance framework. This includes understanding its capabilities, best practices, and compliance requirements.

Introducing new tech in the real world, especially something as big as cloud computing in a finance company, is like navigating a ship through unknown waters. From what I've seen, it's all about testing every part of our data governance framework to find and fix any weak spots. Imagine setting up real-life scenarios that reflect our day-to-day business operations, using the latest tools to dig deep and detect issues, and putting together a solid system to keep an eye on everything. Taking this all-around approach made a huge difference. It helped make sure our clients framework was bulletproof, giving us the green light to move forward with our tech upgrade with full confidence.

From my perspective, whenever integrating new technology into the data governance framework, it's essential to assess its impact on existing policies, processes, and controls. Start by conducting a thorough analysis to understand the technology's functionalities, potential risks, and alignment with data governance objectives. Collaborate with stakeholders across departments to ensure consensus and alignment with organizational goals. Develop clear guidelines and procedures for the technology's implementation, usage, and monitoring, incorporating best practices for data protection and compliance. Review and update the governance framework to adapt to evolving technologies. Aware people about the day-to-day changes to adapt effectively.

Predictive Analytics for Data Governance: Use predictive analytics to identify potential future governance risks and opportunities, allowing for proactive rather than reactive management. Feedback Loops: Incorporate technologies that enable continuous feedback from data users to governance teams, facilitating ongoing improvement of governance practices.

To Implement a new technology , first of all understand readiness of people across different business units and all levels. 1) Assess Soft Benefits ( productivity, Timeliness, Security, Risks and dependencies, Compliance Readiness etc.) as well as Hard Benefits ( Time , Resources, Cost Benefits, Operational Resources Benefits etc.). 2) Consider Alignment with Data Strategy, Data Quality Initiatives, Data Security and Compliance Frameworks, and Enterprise Architecture measures for the new data governance Tool. 3) Understand Executive leadership Alignment and Adoption Strategy in advance for upcoming 3 years to build a robust plan with right resources for implementation and evangelization in organization.

Often times, the advent of new technology in an org becomes the focal point of a data-driven program. However, data governance is really about trust. Does your company already have a culture of transparency and good communication? Technology is great, but without a well informed and accountable set of data stewards, e.g., to ensure that access by engineering teams aligns with the stated data privacy risk...a new lawyer of complexity might only lead to more liability for the organzation. Data governance is one area where you need humans and a well-thought out communication program to ensure that the technology is appropriately applied and your risk aligns with business drivers in a healthy ecosystem built around trust and transparency.

I think it's essential to start with why the adoption of new technology and how it impacts the business (Architecture) or vice-versa! Look at the below aspects to understand the impact 1. Data Steward, Ownership changes if any 2. Any changes to the way Data Security will be addressed? Newer Methods? 3. In relation to the above point, what is the impact on maintaining Data Compliance 4. Data collection, processing, transfer, backup, archival and retention policy changes 5. Data quality- how can one ensure this via the adoption of new technology! Cloud adoption brings in another tangent altogether! So think through!

Start with why the new technology is being introduced and how it will be utilised in service of the stakeholder vision. The answer to this question underpins nearly every other decision throughout implementation and change.

Establish mechanisms for monitoring and oversight to ensure that the new technology is being used effectively and in accordance with data governance policies. This may involve implementing automated monitoring tools, conducting regular audits, and assigning responsibility for oversight. Continuously evaluate the effectiveness of the new technology within the data governance framework. Solicit feedback from users and stakeholders, and make adjustments as necessary to optimize performance and address any emerging issues.