From information to results: how to transform indicators into actions that generate profit.

In recent years, companies have vastly expanded their capacity to capture data. Marketing tools, sales systems, financial platforms, and CRMs generate a massive volume of information every day. However, for most, this growth has not translated into better decisions.

According to Gartner, only 14% of organizations manage to transform metrics into consistent actions, while most continue to operate in "track for track's sake" mode, accumulating reports but without creating real impact. This is the great paradox of the current digital environment: data is not lacking, but qualified decisions remain scarce.

Why do so many companies track numbers but not act on them?

The central problem is not in data collection, but in the ability to interpret them. Many companies still work with fragmented analyses, where each area observes only a snapshot and loses the larger context of the operation. Furthermore, a large part of the metrics are tracked descriptively, without clarity about cause, effect, or priority. This weakens the analysis and transforms reports into repetitive routines without practical effect.

Meanwhile, more mature organizations use the same data to anticipate risks, detect bottlenecks before they become crises, and identify revenue opportunities in real time. The difference is not the volume of information, but the ability to read and act.

Transforming indicators into profit requires a cultural shift

Transforming indicators into results requires a cultural shift: moving from superficial monitoring to analytical interpretation. Companies that grow more consistently tend to translate metrics into hypotheses, connect indicators between marketing, sales, and finance, and make quick decisions, reducing the gap between insight and execution.

They understand that it's not enough to know that conversion has fallen; it's necessary to understand why it fell, its relationship to CAC, which campaign was impacted, and how much lost revenue this represents. This reasoning creates a work model where data ceases to be isolated numbers and becomes evidence for business decisions.

The acceleration of analysis with AI and predictive BI

Artificial intelligence is accelerating this transformation by eliminating the time spent on manual analysis. According to McKinsey, companies that use analytical automation reduce operational effort dedicated to analysis by up to 40% and increase decision-making speed by 15% to 25%. This happens because AI not only consolidates data but also automatically cross-references information, identifies behaviors that would otherwise go unnoticed, and generates contextualized alerts when something deviates from the norm.

Instead of consulting reports, teams begin to receive clear signals about what deserves immediate attention and why. This ability to monitor the business in real time redefines how companies operate, offering a competitive advantage previously reserved only for large organizations.

From insight to action: where companies really make money

When the analysis flow is complete, indicators cease to be observed and begin to guide concrete actions.

The most efficient companies unify dispersed data, identify relevant patterns, transform insights into operational priorities, and continuously monitor the impact of decisions made. It is this cycle that converts analytics into profit and allows the business to advance in a more predictable and intelligent way.

How Sherlock Transforms Data into Action, and Why It Matters

In this scenario, Sherlock emerges to fill an essential gap: offering not only data organization, but actionable intelligence that accelerates decisions. It was designed to seamlessly unify marketing, sales, and finance information, automatically interpret critical variations, and translate complex indicators into clear actions with real-time alerts.

It's not just about modern BI, but a strategic co-pilot capable of transforming each metric into a possible next step. And, above all, Sherlock is born with a clear premise: to democratize this analytical capability for companies of all sizes, allowing any organization to operate with the same level of intelligence and predictability as the market leaders.

Meet Sherlock!

Join the waiting list and be one of the first to test this new way of transforming data into action. The future belongs to companies that know how to execute, and this movement starts now.