From Data to Decisions: Luis Velandia’s Perspective on Impactful Storytelling

Luis Velandia | Chief Data & Analytics Officer at Best Doctors Insurance
Luis Velandia | Chief Data & Analytics Officer at Best Doctors Insurance

Navigating the complex terrains of mining, oil and gas, banking, and health insurance with a passion for transforming data into business gold—Luis Velandia. He is a seasoned global executive with over two decades of experience. With a master’s degree in finance and economics and certifications in artificial intelligence and machine learning from MIT and AWS, Luis stands at the forefront of data and analytics leadership.

As the Chief Data & Analytics Officer at Best Doctors Insurance, Luis manages a diverse team of data experts to propel the company towards strategic success. In this role, Luis has masterfully implemented analytics and data science initiatives, leaving an indelible mark on customer retention, financial risk reduction and revenue growth.

But this isn’t just about data and numbers for Luis—it’s about fostering a culture. He collaborates with senior leaders and stakeholders that align data and analytics seamlessly with business goals. It’s a journey of turning raw data into meaningful insights that drive operational excellence and customer satisfaction.

Let’s explore the insights from a storyteller of data, shaping narratives that propel businesses forward and enrich the lives of those around him!

The Power of We

Luis reflects on a pivotal moment in his career that transformed his approach to operational analytics. Assigned as the D&A Manager for a major mining project, Luis found himself navigating unfamiliar terrain. “I had to learn about the industry, the mining cycle and even the intricacies of assets like 793F trucks in a very short period.”

The challenge was met through collaborative efforts. Luis spent hours in workshops with engineers from various departments, delving into processes, data flows and assumptions. “Sitting down with experts from operations, maintenance and mines allowed me to absorb valuable insights,” he recalls.

The significance of these collaborative sessions became evident during deep dives into productivity analyses. “These working groups, with people from different disciplines, were a game changer,” Luis emphasizes. The collaborative approach including breaking down silos and iterative teamwork proved crucial. Regardless of the role, contribution from everyone made a huge difference when delivering actionable insights to the Vice Presidents.

Luis’s experience underscores a key message—Working collaboratively makes a difference when wanting to rapidly bring business value. His journey with diverse teams highlights the power of collective knowledge emphasizing that collaboration isn’t just about sharing ideas but fostering an environment where diverse expertise converges for a common goal. In the world of D&A, this collaborative mindset, as exemplified by Luis results in accelerating success and delivering impactful insights.

Communication, Collaboration and Continuous Learning

Luis is an advocate for exceptional data scientists emphasizing the key qualities that make them stand out. “Problem-solving, critical thinking, technical skills, creativity, domain knowledge, and effective communication are essential,” he asserts. Luis places particular emphasis on communication citing negative experiences when a compelling data story isn’t conveyed to the audience.

Luis underscores the importance of humility in receiving feedback, even from fellow data scientists. “Some are unwilling to receive feedback,’ he observes. To foster these qualities, Luis implements a practical approach, ‘I conduct peer reviews for models with a checklist covering the minimum Machine Learning workflow.’ This mechanism has proven highly effective and well-received among the data science community he collaborates with.

Effective communication is a focal point in Luis’s strategy. ‘I provide training on Data Storytelling and organize competitions for presenting analytics use cases to stakeholders,’ he shares. These initiatives aim to enhance the ability to communicate complex findings in a comprehensible manner.

Encouraging active participation, Luis prompts data scientists to engage in brainstorming sessions with stakeholders. Understanding underlying problems and incorporating business input is crucial. Luis’s approach ensures that problem-solving, critical thinking and domain knowledge are not just individual skills but integral aspects of a collaborative process.

In Luis’s perspective, shaping exceptional data scientists goes beyond technical expertise—it’s about creating a well-rounded professional with the ability to communicate effectively, collaborate seamlessly and continuously learn and adapt.

Leveraging Data for Success

Luis highlights the transformative power of teamwork in creating business value. Collaboration to deliver data solutions is key, he emphasizes the effectiveness of diverse input to achieve common goals.

Reflecting on an experience as a D&A Lead for a bank, Luis recounts the success of a collaborative approach to optimize branch network performance. “We set up a working group with SMEs from different teams to iteratively develop three data products.” The first was a dashboard displaying branch metrics, followed by profiles using clustering and an optimization model called ‘DEA: Data Envelopment Analysis.’

The collaboration yielded powerful insights and confidence in the developed solutions. “Testing and rolling out the pilot across the entire branch network became possible,” Luis states. The bank’s decision-makers were empowered with valuable information leading to efficiency improvements across the network. This underscores the tangible impact of collaborative efforts in leveraging data for strategic decision-making and business enhancement.

Cloud-Powered Transformation

In the world of insurance, Luis faced not just technical challenges but structural hurdles. Insurance companies often collect data transactionally, leading to an insight mine buried under a rigid structure. Luis found a solution by adopting cloud technologies allowing his teams to overcome processing and insight generation challenges. “We developed data marts focused on specific analytics hubs like customer analytics and sales.”

One notable challenge emerged during the first ML project. “Migrating data to the cloud was routine, but developing data marts posed a new dimension,” Luis reflects. Excitement surrounded the ML algorithm’s test results, yet it faced a hurdle—only half the required features were in the cloud. Luis and his team navigated this by building a mid-point data mart consolidating needed information and using UDTF to seamlessly feed the model.

In the end, the pilot stage yielded ‘mind-blowing results’ after four months. Luis’s strategic use of cloud technologies and innovative approaches not only overcame structural challenges but showcased the transformative power of analytics in the insurance industry. This journey exemplifies how adapting to evolving technologies can turn historical data into a valuable asset, unlocking insights that were once buried beneath a rigid structure.

Resonating with Data

Luis emphasizes the role of Data Storytelling as the bridge between insights and impact. It is the best solution for effective communication between technical and non-technical people. According to Luis, the crux of any data product lies in ensuring stakeholders not only understand but actively use the insights for decision-making. “If decision-makers don’t see the value or understand the actionable insights, realizing proposed business value becomes challenging.” To overcome this, Luis underscores the importance of connecting with stakeholders through ‘creating a compelling data story.’ In his view, the ability to resonate with stakeholders through storytelling is the key to unlocking the true potential of data insights fostering understanding and driving impactful decision-making.

From Ownership to Impact

Luis is a proponent of a thriving data-centric culture and he shares effective strategies for cultivating a dynamic and motivated team. “Investing in trainings is crucial for their development,” he asserts recognizing the value of continuous learning in the fast-paced data landscape.

Creating forums to emphasize the importance of self-education and adaptation is another key strategy. Luis believes in involving the team in decision-making processes, stating, “Asking for their input and showcasing results with a data-driven approach builds a sense of ownership.”

Collaboration takes center stage in Luis’s approach. “Emphasizing the business value of analyses and questioning why fosters a results-driven mindset.” Additionally, he advocates for Analytics Guild sessions where each team member presents results to the entire organization promoting knowledge sharing.

These strategies, according to Luis, contribute not only to team motivation but also have a significant impact on talent retention and overall business performance. In a rapidly changing world, these approaches form the foundation of a resilient and adaptive data culture.

Securing Trust

Luis is a staunch advocate for data privacy and ethics and he shares key considerations to uphold ethical standards in the realm of data-driven processes. Establishing a robust data ethics model is crucial highlighting the need for a framework that respects privacy ensures data security, transparency and prevents biases. To meet ethical standards, Luis recommends the following areas of focus:

  • Collect and Process Only Necessary Data: Reduce privacy risks by collecting and processing only the data necessary for the intended purpose.
  • Stay Updated on Data Protection Regulations: Keep abreast of regulations like GDPR and HIPAA to ensure legal compliance through internal policies.
  • Integrate Privacy Considerations Early: Embed privacy considerations from the initial stages of solution development.
  • Use Anonymization and Pseudonymization: Safeguard individual identities during data processing through anonymization and pseudonymization techniques.
  • Prioritize Explicit and Informed Consent: Obtain explicit and informed consent from customers before any data collection or processing.
  • Provide Ongoing Training: Offer continuous training to the team on ethical data practices and the significance of customer privacy.
  • Empower Customers: Give customers control over their data, allowing them to manage preferences and providing options for data deletion or correction.

Luis’s approach underscores the importance of a proactive and comprehensive strategy to ensure ethical data practices, safeguard privacy and maintain customer trust in the evolving landscape of data management.

Thriving Amid Change

Luis shares insights on driving teams to excel in a dynamic market. Encouraging teams to discover new and better ways is crucial for staying ahead, he emphasizes the importance of training in scalable technologies. For Luis, innovation isn’t just a buzzword—it’s about continuous improvement that provides a competitive advantage.

Luis illustrates this with the tangible impact of automation, a key mechanism for competitiveness. In organizations, automation, especially in reporting, is a game changer. Luis recounts how he facilitated stakeholders in automating reports liberating them from manual efforts and ensuring proper data governance.

The result? “A profound impact on performance, freeing up valuable time for nurturing strategies and making faster, better decisions.” In Luis’s view, embracing scalable technologies and automating processes are not just trends but essential strategies for organizations aiming to thrive in a rapidly changing market.

Learning, Teaching and Leading

Luis is a passionate learner and educator and he shares insights into his multifaceted approach to staying ahead in the dynamic world of data science. “I enjoy reading books, watching YouTube videos and delving into thought leadership articles,” he reveals. Luis is not just a consumer of knowledge but a fervent advocate for knowledge transfer. With a background as a professor, he finds joy in making presentations and training others.

Luis’s hands-on approach is evident in his use of tools like R and Python for building ML models and conducting statistical analyses. “Being hands-on allows me to stay connected to the evolving landscape,” he notes. His engagement extends beyond personal learning—Luis actively participates in events and panels as a speaker, generously sharing his knowledge with the community.

For Luis, continuous learning is a team effort. Clear competency definitions and regular communication are key. In the tech landscape, certifications and training are priorities to ensure consistent performance. Luis ensures that his team adapts to new technologies, especially modern data stacks.

Encouraging knowledge sharing within the team is a fundamental part of Luis’s philosophy. “If they can teach what they know, they will also learn and strengthen their own knowledge,” he believes. Luis embodies a holistic approach to learning—from personal growth to team development fostering a culture of continuous improvement in the fast-paced world of data science.

Investing in Tomorrow

Luis is a believer in the transformative power of Data & Analytics in the insurance industry and asserts that data is the lifeblood of any Insurance company. According to him, the future holds immense potential for business value through major transformations and emerging trends in the field.

While Luis sees Generative AI and LLM systems as pivotal, he emphasizes the ongoing significance of traditional machine learning and deep learning techniques in analytics use cases.

In Luis’s vision, there’s untapped potential in areas like “underwriting process automation, detecting insurance fraud, dynamic pricing, claims processing and management optimization along with product recommendation engines.” He anticipates these areas gaining even more relevance but acknowledges that realizing this potential requires substantial investment in technologies.

Luis highlights how such investments are not only crucial for keeping pace with industry evolution but also for increasing productivity and reducing costs in the ever-evolving landscape of the insurance sector.

Beyond Tools and Modeling

In the realm of data, Luis offers key recommendations for aspiring professionals drawing from his wealth of experience. “Firstly,” he emphasizes, “study problem solving, design thinking and stay ahead in the field.” Luis’s insight underscores the importance of continuous learning to navigate evolving challenges.

Moving to the core of data work, he advises, “Truly understand the underlying problem and frame it before jumping into tools or modeling.” Luis believes that this understanding of translating business challenges into data solutions not only saves time but also ensures positive stakeholder feedback.

Luis’s second recommendation centers on project management. “Understand agile methodologies, run projects using sprints, iterations and MVPs,” he suggests. Sitting down with stakeholders in workshops or brainstorming sessions becomes crucial to comprehend requirements and expectations.

The third piece of advice focuses on communication. “Learn how to use data stories to convey actionable insights effectively,” Luis urges. It’s not just about informing but ensuring that insights are communicated in a way that drives action.

Lastly, Luis stresses the importance of continuous improvement in domain knowledge. “Improving domain knowledge every day adds value to the data products they deliver.” Luis’s recommendations encompass a holistic approach combining technical prowess, effective communication and a commitment to ongoing learning for success in the dynamic field of data.