The Shift From More Data to Right Data in Business Strategy

For nearly two decades, the dominant business philosophy around analytics was simple: collect everything. More data meant better decisions, sharper predictions, and unmatched competitive advantage or at least that was the belief.

But as organizations scaled, this “more is better” mindset created a new problem. Overflowing dashboards, bulk data, and teams drowning in metrics that said everything and pointed to nothing.

In 2025, the conversation has shifted. Companies no longer celebrate the size of their datasets; they celebrate the clarity they have from them. This is the move from more data to right data shaped by some of the world’s most innovative companies.

Why “More Data” Stopped Working

At its peak, big-data culture produced an unhealthy obsession with quantity:

• Thousands of KPIs
• Complex multi-layer dashboards
• Massive data lakes with unclear ownership
• Repeated, redundant tracking across teams

Yet the outcomes didn’t keep pace. Leaders were frustrated that decision cycles were slowing down instead of speeding up. Teams were relying on instinct because the data was too scattered or too complex. Engineering costs kept rising. Success didn’t come from more data. It came from the right data, data with purpose.

How Global Leaders Made the Shift

1. Google: From Data Overload to Signal Quality

Google was one of the pioneers in collecting behavioral, and contextual signals at scale. But even Google reached a point where adding more data produced diminishing returns. Instead of tracking every possible micro-event, Google began prioritising high-intent signals that directly improved:

• Search relevance
• Ad performance
• User experience models
• Personalised recommendations

This move drastically reduced noise. Google realised that improving the quality of just a few critical signals often beat adding 100 new data points. Faster, more accurate models were built because of better data.

2. Nike: Precision Metrics for Performance Innovation

Nike’s ecosystem generates enormous data from wearables, retail behavior, supply chain operations, and digital communities. For years, the temptation was to track everything. But Nike recognised that high-performance innovation needed specific, high-impact metrics, not an endless list of indicators. Nike redesigned its data stack to focus on the metrics that matter most for:

• Athletic performance
• Retail purchasing patterns
• Product testing cycles

This allowed teams to make quicker decisions, run more efficient experiments, and personalise customer experiences without drowning in irrelevant data. Nike was able to better innovation cycles and stronger consumer insights through less but sharper data.

3. Samsung: Smart Data Over Big Data

Samsung’s device ecosystem from mobile to appliances, creates billions of data points daily. Initially, Samsung embraced a "collect it all" strategy to map user behaviour across devices. But complexity grew faster. Samsung identified and isolated behavioural patterns that actually predict purchase intent, usage behaviour, and retention.

Instead of building models from enormous, unfiltered datasets, Samsung now builds around targeted behavioural clusters. They shifted to better forecasting, stronger product-market alignment, and reduced infrastructure and analytics overhead.

Samsung realized that fewer, cleaner signals produced better predictions than massive, unfiltered streams.

The New Competitive Advantage: Knowing What to Ignore

Today’s most successful companies share a new philosophy. The organisations who win aren’t the ones with the largest databases, they're the ones with:

• Clear data ownership
• A defined metric hierarchy
• Clean, reliable pipelines
• Strong governance and deduplication
• High-quality outcome-focused signals

In other words, the winners are the companies who know what not to collect. This is the modern competitive advantage.

Where DataSense Fits Into This Shift

As modern organizations rethink their data strategy, many face the same challenge. This is exactly what DataSense fits in. DataSense helps companies transition from data overload to data intelligence by offering clean and reliable data pipelines, reducing low-impact data in a unified dashboard with which the whole can align.

It is a tool to identify which 5% of your data produces 95% of your outcomes. DataSense empowers businesses to refocus on clarity, and efficiency by producing actionable insights.

Conclusion

The era of collecting just more data is over, now clarity will define the future. The future belongs to businesses that collect purposeful data that empowers instead of overwhelms.

Google, Nike, and Samsung have already proved the value of this shift. Now it's time for every organization to become equally data-driven. DataSense is the partner that makes this shift possible.