How to transform simple questions into strategic decisions with AI.

For a long time, making strategic decisions was a slow, expensive process restricted to a few people within companies. It required extracting data from different systems, cross-referencing spreadsheets, interpreting complex dashboards, and only then attempting to reach a conclusion. Along the way, many decisions ended up being made more by intuition than by evidence. Artificial intelligence changes this game by placing a new mindset at the center of management: asking better questions to act faster.

Today, companies that grow above average are not those that accumulate the most data, but those that manage to transform it into clear answers to objective questions. Simple questions, such as "which channel generates the most profit?", "where are we losing revenue?", or "what needs attention now?", begin to guide decisions with a direct impact on the business.

The problem is not the lack of data, but the difficulty in obtaining answers.

According to IDC studies, more than 70% of the data generated by companies is never used for decision-making. This happens because the information is fragmented between marketing, sales, finance, CRM, spreadsheets, and legacy systems. The result is a common scenario: data exists, but it doesn't communicate with itself; reports exist, but they don't generate action.

In this context, managers spend time trying to interpret numbers instead of making decisions. Each new question becomes a project, a dashboard, or a request for the technical team. By the time the answer arrives, the context has often already changed. AI applied to data analysis emerges precisely to eliminate this bottleneck between question and decision.

From "looking at reports" to "ask and act"

The big leap in productivity happens when the company abandons the passive logic of monitoring metrics and adopts an active stance, guided by strategic questions. Instead of navigating through dozens of reports, the manager begins to interact directly with the data, questioning the business in real time.

AI-powered platforms can interpret these questions, cross-reference information from multiple sources, and return contextualized answers with actionable insights and recommendations. It's not just about showing numbers, but about indicating what they mean and what actions make the most sense at that moment. This is the point where data ceases to be operational and becomes strategic. Artificial Intelligence as a Co-pilot in Decision Making

AI doesn't replace managers. It acts as a strategic co-pilot, reducing analytical effort and enhancing the quality of decisions. By automating analyses, identifying patterns, anticipating risks, and signaling opportunities, the technology frees leaders to focus on what really matters: prioritizing, deciding, and executing.

According to McKinsey, companies that consistently use AI in decision-making increase their response speed by up to 5 times and significantly improve indicators such as margin, operational efficiency, and revenue growth. The key difference lies in the ability to transform simple questions into quick decisions based on reliable data.

Where Sherlock connects to this new mindset

This is exactly where Sherlock positions itself. The platform was created to eliminate the distance between data and decisions, connecting information from different areas and allowing any manager to ask direct questions and receive clear answers, without depending on code, manual reports, or technical teams.

Sherlock organizes data, but goes further: it generates insights, sends intelligent alerts, and helps prioritize actions. Instead of more dashboards, it delivers clarity. Instead of lengthy analyses, it provides answers in seconds. This model democratizes access to advanced analytics and puts data intelligence into the routine of those who need to decide, not just those who know how to operate complex tools.

Making good decisions means deciding with better questions.

At the end of the day, strategic decisions don't begin with reports, they begin with questions. Companies that understand this build a more mature, agile, and results-oriented data-driven culture. Artificial intelligence makes this process simpler, more accessible, and scalable.

Transforming simple questions into strategic decisions is no longer a distant competitive advantage. It's a necessity for those who want to grow consistently in an increasingly dynamic market. And that's exactly the transformation Sherlock aims to enable: less complexity, more clarity, and better decisions at the right time.