(US & Canada) VIDEO | Know Your Audience Well for Communicating Data Value — Best Doctors Insurance CDAO

Luis Velandia, Chief Data and Analytics Officer at Best Doctors Insurance, speaks with Carlos Cruz, National Lead of Data Strategy and Governance at Centric Consulting, in a video interview about strategies to communicate with diverse audiences, implementing data governance, and the role of data governance in AI.

Speaking about the challenges faced while communicating technical insights to non-tech leaders, Velandia states that data stories are a way to address the challenge. He believes in sharing complex technical concepts in simple language involving analogies and metaphors.

Adding on, Velandia says that using visual elements such as infographics elevates the visual appeal and facilitates a better understanding of data among non-tech people. He further notes that using business examples to address specific concerns for non-tech audiences allows organizations to foster a collaborative and informed decision-making process.

Digging deeper, Velandia states that the goal is to enhance decision-making and it is critical to know who the audience is and engage well with them. He stresses that data storytelling is the right mechanism leading to informed decisions.

When presenting data to a non-technical audience, Velandia starts with a high-level review, straightforward language, and visuals.

For a technical audience, he incorporates a detailed analysis of a model, uses business examples, and encourages interactions through questions. Engaging technical audiences brings in technical perspectives and generates good insights.

Emphasizing data governance, Velandia states that it is crucial to understand that data governance is not an isolated concept, but a response to specific needs. He continues that many companies implement data governance when addressing data security issues and exploitation.

Commenting further, Velandia recommends implementing governance as a data governance program through a flagship strategic project linked to data that would facilitate decision-making. Also, he suggests integrating governance into the strategic decision-making process from the outset.

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Next, Velandia suggests adopting an incremental approach considering the unique conditions of each company because data governance is involved in every organizational process. Then, he discusses the importance of culture stating that it is the key component of organizational transformation that helps to avoid resistance and promote sustainable implementation.

Highlighting the role of data governance in AI, Velandia opines that having robust data governance is essential to ensure ethical, responsible, and reliable AI applications. To identify and address AI biases and avoid unintended consequences, it is imperative to implement governance measures.

Furthermore, Velandia adds that data quality is a key driver for data governance programs. Taking the case of sensitive data used in AI applications like LLMs, he focuses on the need for data privacy. He also believes that data governance policies should focus on data anonymization, encryption, and compliance with privacy regulations to safeguard customer information.

Governance fosters transparency and reliability in data ensuring comprehensibility of decisions, says Velandia. He maintains that designated data stewards are necessary to maintain those governance practices.

On a similar note, Velandia says that a continual collaboration among data scientists, ethicists, and experts is needed to refine governance frameworks in the evolving landscape of generative AI and LLMs. This should be done to ensure a balance between innovation and ethical considerations in the development and deployment of AI.

Furthermore, Velandia states that technology solutions and machine learning models can be developed, but understanding the complex AI lifecycle while addressing regulations is important.

In conclusion, he mentions the European Union AI Act, as it incorporates technical policy and procedural controls to achieve responsible AI objectives and risk assessments — while maintaining sustained performance and ethical AI practices.

CDO Magazine appreciates Luis Velandia for sharing his insights with our global community.

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