When more data makes insight worse

When confidence in insight is challenged, the most common response is to add more data, more platforms, more sources, more volume. But in highly optimised social media platforms, scale can distort as much as it reveals.

As online content becomes increasingly shaped by incentives, repetition, and amplification can create a false sense of robustness, patterns can seem stronger than they are, and marginal trends can gain disproportionate weight, all leading to biased “insights”.

This session explores why “more data” is no longer the answer in good social intelligence work. We’ll examine how volume, duplication, and amplification can erode insight quality, and why reduction, scoping, and deliberate exclusion are becoming essential analytical skills.

The focus is not on doing less work, but on doing more defensible work, and on how social intelligence teams can justify better, more focused analysis in organisations that still equate scale with rigour. You’ll learn:

• Why volume can create false confidence in optimised environments
• How repetition and amplification can distort signal strength and data quality
• What false robustness looks like in practice
• When narrowing scope increases credibility