What are the most effective ways to negotiate access to data for your Business Architecture analysis?

For me, this is the key benefit of a data lake. You don't want to jump through all these loops every time anyone in the organisation has a valid business case to access data for this type of use case. The data should be added to the lake as part of an iterative process, with the various data sources being added on a "as-needed" basis. Each access request can then follow a standard approval workflow, with no new technical integration or development effort needed from the source "silo"/business function. In my experience, this approach removes all the biggest hurdles, both technical and political, then requesting access to data for business architecture related use cases in a complex heterogeneous corporate systems landscape.

1. Articulate Benefits: Clearly express how the data will benefit the analysis and the organization. 2. Establish Rapport: Build relationships with data owners and stakeholders to ease negotiations. 3. Adhere to Governance: Follow data governance policies to show commitment to compliance and security. 4. Data Request Document: Draft a formal request detailing data usage, benefits, and security protocols. 5. Executive Support: Gain backing from higher-ups to underline the analysis' importance. 6. Phase Approach: If full access is denied, negotiate for partial access and increase over time. 7. Mutual Benefits: Highlight shared gains, such as improved processes or decision-making.

Prior to seeking data access, it is essential to establish a well-defined and persuasive value proposition for your business architecture analysis. Consider the following key aspects: 1. Project Goals: Clearly outline the specific objectives and goals of your project. What do you aim to achieve through this analysis? 2. Benefits: Highlight the anticipated benefits of your analysis. How will it contribute to your organization's growth and development? 3. Outcomes: Describe the expected outcomes of your project. What tangible results can your stakeholders expect? 4. Alignment: Explain how your project aligns with your organization's strategic vision, objectives, and overall priorities.

I believe negotiating access to data for Business Architecture analysis demands a strategic blend of technical efficiency and organizational alignment. Now, utilizing a data lake for iterative integration and standardized approval workflows is undeniably practical; it's equally essential to cultivate a culture that values data transparency and collaboration. By marrying these elements, we overcome technical and political obstacles and foster an environment where insights flow seamlessly across departments, empowering our business architecture initiatives to thrive within the complex corporate landscape.

- Be a Partner: Convey that you're not a threat but a collaborative partner. Emphasize the mutual benefits of the data analysis. - Engage Early and Often: Involve your stakeholders from the beginning of your data analysis process. Regularly seek their input and feedback to make them feel valued. - Understand Perspectives: Take the time to comprehend the viewpoints, concerns, and motivations of your stakeholders. This understanding is crucial for a successful collaboration

- Data Types, Sources, and Formats: Clearly identify the types of data needed, where it will come from, and in what formats. Specify whether it's structured or unstructured data. - Quantity, Frequency, and Duration: Determine the volume of data required, how often you need updates, and the duration for which data access is essential.

Identify Potential Barriers and Obstacles: - Recognize any legal, contractual, or regulatory barriers that may restrict data access. - Identify potential conflicts of interest within your organization or with data providers. Anticipate Data Quality Issues: - Acknowledge possible errors, gaps, or inconsistencies in the data you're requesting. - Be aware of data source limitations that may affect the quality and reliability of the data.

Data Agreement Negotiation: - Define the terms and conditions of data access in a formal data agreement. - Specify data requirements, scope, roles, responsibilities, and deliverables clearly. - Set realistic timelines and establish performance metrics.

Some data can be aggravated and anonymised. Then it becomes easier to analyse it and identify gaps. Performance analysis can then identify gaps and bottleneck through the customer journey. Privacy-preserving statistics can help.