The Leadership Discipline Behind Analytics Success

Alexis Alvarez is Head of Advanced Analytics and Data Governance at Antamina, where he helps teams turn data into practical decisions that improve everyday operations. Over more than 15 years in technology, analytics and data leadership, his career has evolved alongside the growing complexity of large organizations, shaping his belief that value comes not just from models, but from people adopting new ways of working. Known for bridging technical insight with clear communication, Alexis focuses on building trust in data, encouraging better questions and embedding analytics into how work actually gets done.

Balancing Structure and Agility: Governance That Accelerates Innovation

Data Governance and innovation are two sides of the same coin, where governance serves as the rails, while innovation is referred to as the speed. You need both. The trick is to keep the rails clear and simple: who owns the data, who gets it, how we go about protecting it and how we know if its quality is good enough.

With those fundamentals in place, teams can move fast without creating chaos or risk. Good governance makes it easier for the flow of innovation because you have everybody comfortable around what is numbers, so people debate less about what is right or not.

Setting Realistic Expectations: What Analytics Can and Can’t Do

Start with a well-articulated business question and the decision it will support. Establish a KPI and a shared baseline so that everyone measures the same thing. Avoid making the wrong conclusions by always conducting disciplined analysis (validate assumptions, test outliers, results across time and segments, etc). Lastly, turn insights into action: put them in workflows / processes, assign an owner, measure impact over time otherwise it would remain interesting analysis or PoC not business value.

The biggest challenge is the change management. With most organizations making decisions not on data but based on experience and urgency, it is up to leaders to help these teams establish new habits. Time is another challenge: operational teams are stretched and always busy so data and dashboards should be part of the day’s work rather than extra work. But data can also raise uncomfortable questions, which might be as simple as gaps in a process or lack of clear accountability, about how things are done and leaders need to deal with that in a constructive manner. Finally, leaders need to moderate expectations: Analytics doesn’t eliminate uncertainty, but it helps teams make better decisions and get better over time.

Automating the Essentials: Reducing Friction in Governance

The most effective governance frameworks remain when it keeps a little bit simple and concentrates on what really matters. We don’t need the rules to be designed at same level for all the data. For instance, executing reporting data should have slightly more closer checks than the ones we do for quick exploration. It also doesn’t hurt if there are some key controls that are automated, such as data quality checks and a standardized process to request access.

Governance can be far more distributed as the organization matures. Every business area owns more of its data day-to-day and the central data governance team are providing standards, tools and direction. It’s a way of keeping control but making decisions faster and more practical.

From Insight to Adoption: Helping Teams Change Habits

They need to be about value, not just focus on analysis. What’s key is change management, because people will need new habits, not just new tools. They should be familiar with data platforms at a higher level (and not an expert in all technology stack). And they need to be able to explain in plain language, why it matters, what value there is and what’s missing to show less rejection going forward and management support more quickly.