Data-Rich, Action-Poor: Why marketing mix models fail to drive decisions

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TL;DR

Companies invest heavily in marketing analytics, yet most fail to act on the insights—leaving value unrealised.

Article
Despite widespread adoption of marketing mix modelling (MMM), many companies struggle to convert insights into meaningful action. A recent Harvard Business Review analysis highlights a persistent gap: firms collect vast amounts of data but rarely use it to reshape strategy.

MMM, long valued for measuring the impact of marketing spend across channels, has regained prominence as privacy regulations limit user-level tracking. Yet its outputs often remain confined to dashboards rather than boardrooms. The issue is not data quality but organisational inertia.

Several factors contribute to this disconnect. First, MMM outputs are often too complex or slow for real-time decision-making. By the time insights are delivered, market conditions may have shifted. Second, internal silos hinder execution. Marketing, finance, and analytics teams frequently operate with misaligned incentives, reducing the likelihood of coordinated action.

There is also a cultural barrier. Senior leaders may endorse data-driven decision-making in principle but default to intuition under pressure. Without clear accountability, insights risk becoming advisory rather than directive.

Some firms are beginning to close the gap by integrating MMM into planning cycles, simplifying outputs for executive use, and tying performance metrics directly to model-driven recommendations. Automation and faster modelling techniques are also helping shorten decision timelines.

The broader lesson is straightforward: data alone does not drive outcomes. Organisations must build processes—and mindsets—that prioritise action. As measurement capabilities evolve, competitive advantage will increasingly depend not on who has the best data, but on who uses it decisively.