How do you navigate conflicting priorities between a data owner's preferences and a data user's needs?

Owing the data is as important as consuming the data, but there is a gray area of shared responsibility that needs to be clearly defined. Data owners are always concerned about how the data will be used, and any possible violations in terms of policies and compliance, but also they need to be committed to provide the best quality of data possible for the consumers. Data consumers must me responsible for requesting the right data to fulfill their needs, the give-me-all approach should be re-thought, even though technically speaking the capabilities are present, but from the human standpoint, are they really able to understand it? This is were true definition roles and segregation of duties are key for success.

In a recent strategy meeting, we faced a challenge: the marketing team needed extensive access to customer data for an upcoming campaign, while our compliance department insisted on stringent access controls to protect privacy and security. To resolve this, we began by clarifying the roles. Compliance ensured data integrity and security, while marketing required data to drive engagement. We facilitated a dialogue where both sides outlined their critical needs. By implementing tiered access controls and anonymization techniques, we struck a balance, enabling marketing to perform their tasks without compromising data integrity and security.

It is very important to understand the priorities of both the parties and the origin of the conflict. It could be something as simple as the duration/timeline to have the data in a format that can be use or something as stringent as regulatory compliance thing. Reach at a mutually beneficial ground; negotiate timeline or used virtualized data representing the real world data without exposing the actual data etc. Ensure necessary checks and balances again data access and usage to ensure security and privacy. Bringing both the parties to the table to help understand each others perspectives helps knock down barriers and create a mutually beneficial way forward. A constant audit of data usage keeps the conflicts at bay.

When dealing with conflicting priorities between a data owner and a data user, I first listen to both sides to understand their needs and concerns. I look for common goals, like wanting accurate and useful data, and emphasize these to foster cooperation. Clear communication is crucial, so I keep everyone informed and explain the importance of each perspective. I then set priorities based on impact and feasibility, aiming for compromise or phased solutions. Following established data policies helps make fair decisions. Acting as a mediator, I ensure both parties understand each other and regularly check in for feedback to adjust as needed.

Both data owners and data users are key stakeholders, and each group needs to be incorporated into the data process. However, the feedback from data users plays a critical role in shaping how data should be collected. When analyzed data does not produce insights that guide the users' decisions, data owners must revisit users' demands and address how data should be collected and analyzed. Most data are like a black box when not analyzed. It is the users’ requirements that dictate how the data should be analyzed and consequently how the data should be structured.

Create a comprehensive data governance policy framework that addresses data ownership, access, usage, and security. Clearly define the roles and responsibilities of data owners and data users within the policy framework. Implement standardized processes for data access, including request and approval workflows. Develop guidelines for appropriate data usage, ensuring that data is used in a manner that aligns with governance policies and business objectives.

During a recent system overhaul, tensions arose between our finance team, who guarded data closely, and the analytics team, who needed broader access for reporting. We addressed this by drafting comprehensive data governance policies. These policies defined who could access what data, under what conditions, and the security measures required. We held workshops to ensure everyone understood the protocols and the rationale behind them. By including a process for requesting exceptions, we maintained flexibility. This approach fostered mutual understanding and reduced conflicts, ensuring smooth data operations.

I found very efficient to implement well-defined data governance policies that balance security requirements and operational needs. These policies should include guidelines for conflict management and decision-making protocols. They ensure actions taken are aligned with the organization’s strategic objectives.

Data governance involves coming with an approach on data usage. 1. The roles, responsibilities and usage of the data by user should be clearly defined. 2. Controls to be set for data provision, access and usage. 3. Consensus should be obtained from the data owner for data provision. 4. The data control matrix should be clearly defined and agreed upon between the data owner , user, data management division 5. A priority index should be set up in the data control matrix itself so that only needed data is shared based on priority. 6. A mechanism should be set up for purging and monitoring old and unused data sets.

For me it depends on the amount of data (and their sources!) and the size of the company. But overall I would value simplicity and keeping it lean, making it easy for everyone to understand, manage and access the data needed without creating (maybe) annoying hold-ups and waiting times. Clearly, valuing security and regulation is important - but over-regulation is the other extreme.

Treating data as a product is a great way forward. What are the motivations driving your data users? What kind of service are they using the data for? Have a meaningful business dialogue around these themes and the tech & governance sides will be easily sorted afterwards.

In a recent project, our research team needed detailed customer data to enhance our product offerings, but the data management team was wary of sharing sensitive information. We initiated regular meetings to foster open dialogue between the teams. During these discussions, the research team explained their needs, while the data management team highlighted their privacy concerns. Through collaborative effort, we agreed to anonymize the data, ensuring valuable insights without compromising privacy. This process underscored the importance of communication in balancing security with accessibility.

From a strategic leadership viewpoint, promoting dialogue aligns with building a data-driven culture within the organization. It underscores the importance of transparency, trust, and mutual respect among stakeholders. By institutionalizing regular communication channels, leaders can ensure that data governance is not only about compliance but also about leveraging data as a strategic asset. This practice can lead to innovative solutions, such as data anonymization, that balance the need for information sharing with privacy concerns, ultimately driving better decision-making and business outcomes.

I once heard the great saying: take the problem you are given and then shift it by 15 degrees and see if from another angle. My favourite approach is to iterate and learn along the way: share a draft, learn from the feedback and get better and closer to the truth with each attempt.

Conversation and communication is key... Doesn't matter what you do You have to make sure both parties talk in a cohesive and timely manner.

Data masking and anonymization techniques can be used to protect sensitive information while still allowing users to work with the data they need ensuring privacy and security without hindering data usability. Additionally, I'd employ secure data-sharing platforms that provide data users with the necessary access without compromising security or privacy One suitable secure data-sharing platform is Microsoft Azure Data Share.

I have implemented some of the best AI-driven data technology. The best comes out of the box easy to use by the data users. You don't need to recreate the front end. It should aid in driving consistency by providing suggestions for review and approval. However, even the best technology won't help if your colleagues are not bought into the change journey. Friction often occurs because the approach is unclear, and the goal has not been communicated at a level everyone understands. Suppose you are just provided with tech to use, without fully understanding the why, and the benefits to you and the business. it makes adoption difficult. Communicate, Communicate, Communicate!

When our sales team needed access to customer data for targeted campaigns, the IT department was concerned about security risks. We decided to implement advanced data governance technologies to address this. By utilizing data masking and granular access controls, we ensured that sensitive information was protected while providing the sales team with the data they needed. Automated enforcement of these policies reduced manual oversight and minimized potential conflicts. This tech-driven solution harmonized data security with user accessibility, streamlining our operations effectively.

One of the biggest mistakes we see organizations make is purchasing a tool and trying to mold their culture and framework to it. This almost always fails. Companies should set their policies, choose a framework and THEN find a tool that closest supports those.

Utilizando tecnologias avançadas de criptografia e anonimização para proteger os dados e garantir a conformidade com as regulamentações de privacidade, estas ações ajudam muito na implementação de sistemas permitindo que os proprietários de dados controlem como suas informações são usadas, enquanto soluções de monitoramento e auditoria asseguram que o uso dos dados pelos usuários seja rastreável e responsável. Além disso, tecnologias de acesso baseado em permissões ajudam a restringir o uso dos dados a apenas aqueles que realmente precisam, equilibrando eficazmente as necessidades dos usuários com as preferências dos proprietários.

Recently, our analytics team required broader access to data, raising concerns for our data compliance department. We addressed this by enhancing our compliance monitoring. Implementing continuous tracking systems, we kept a close watch on data usage patterns and user access. Regular audits provided insights into policy effectiveness, highlighting any overly restrictive or lenient areas. These reports enabled us to fine-tune our policies, ensuring they balanced security with accessibility. This proactive monitoring maintained alignment between data owners and users, fostering a compliant and efficient data environment.

In my experience, monitoring for compliance needs to be seen as a benefit rather than the data police. we are here to enable operations to continue while protecting the data assets and the company from the potential risks of inappropriate use of data. When explaining compliance monitoring. Help people understand it to safeguard them and the company rather than catch people out. You will need to demonstrate this too, as words are not enough. A good analogy is the Rugby referee. They are there to protect the player's safety and ensure the rules are complied with. Not stop or prevent the game from being played. This is the same for data. Help people feel comfortable with compliance monitoring.

Monitoring compliance is essential to ensure that all projects adhere to consistent policies and rules. This practice promotes a unified understanding of data regulations and restrictions across the organization, making it easier for everyone to comprehend and follow the established guidelines.

Our company recently faced a situation where the product development team needed greater data access to innovate, but our initial policies were too restrictive. We responded by scheduling quarterly reviews of our data governance policies. During these sessions, stakeholders discussed evolving needs and emerging technologies. We adjusted access controls and security measures accordingly, ensuring policies remained relevant and effective. This ongoing adjustment process allowed us to maintain a balance between the data owners' security concerns and the users' need for accessibility, fostering both innovation and compliance.

The world we live and work in changes constantly. You only need to look back at the last few years for example, with the pandemic and Gen Ai. What's next is only around the corner. Therefore, check in around every 6-12 months using your data governance committee to ensure your approach, compliance measures and reporting, etc. are still appropriate for the current and expected future needs. Follow organisations like Garter and McKinsey for insights on future developments that might affect you along with the world economic forum on global risks that would impact your organisation.

Governance should align with how your organization operates. As processes evolve, governance must be adjusted accordingly, as applying the same rules to fundamentally different processes is ineffective. However, any changes to governance should be carefully evaluated and discussed. Scheduling quarterly or semi-annual governance committee meetings can help ensure that governance practices remain relevant and meet the organization's current needs.

A governança de dados não é um processo de definir e esquecer; requer ajustes contínuos para se alinhar às necessidades de negócios em constante mudança e aos avanços tecnológicos. Esteja preparado para revisar as políticas e os resultados do diálogo para garantir que permaneçam relevantes e eficazes. Essa abordagem dinâmica permite uma estratégia de governança responsiva que pode se adaptar a novas circunstâncias, mantendo o equilíbrio entre proprietários de dados e usuários.

Kann man so unterschreiben , wenn man sich nur gesetzliche neue Bestimmungen anschaut der letzten Jahre. Die UST-ID und SteuerID die plötzlich im Prozess geprüft werden mussten oder der Datenabgleich gegen Terrorlisten uvw. Dynamik im System ist wichtiger denn je

How do you navigate the priorities of participants in the city traffic? (make everybody play by the same rules; acknowledge that despite the best efforts accidents can sometimes happen - have remedies available)

Effective data governance isn’t about preferences of data owners; it’s dictated by facts, overarching business needs and impact. Open communication, clear governance policies, and prioritizing decisions based on business impact are key. By fostering a culture that values data sharing and collaboration, organizations can ensure that data usage aligns with business objectives, enhancing efficiency and profitability.

I understand the topic maybe looking at the day-to-day operational aspects of Data Governance. Hence, one important thing that should have been a bigger topic here but missed is the business importance and prioritization of the data initiatives. Always the biggest bang for the buck or how much operational improvement a data owner's preference or a data user need would bring to the business metrics or cater to operational improvements would help prioritize vs. completely eliminating. The idea here is not that we have to forego one thing over the other. If both the conflicting priorities prove to be important to the enterprise, but on equal footing, then you would record them as part of your product backlog and enable one after the other.

Use Smart Data Protocol to productize your data assets and tightly configure the attached contract to control precisely what the data user can do and to monitor the data product’s usage and lifecycle to ensure a highly tailored user experience that meets the requirements of the data owner. Without Smart Data’s ability to monitor, control, and audit who, where, when, and how the data asset is used - this problem will continue!

Working with data is always about balancing: having data in the right quality, but that is secure. Being able to access it in an instant, without being reckless with access. Acknowledge that it is an iterative process: mistakes happen, take them in stride and keep learning.