Analytics projects do not usually fail dramatically. They degrade slowly. The reports that were accurate on launch start to drift. The metrics that were trusted start to be questioned. The dashboards used daily start to be checked weekly, then monthly, then not at all.
This whitepaper diagnoses the root causes of analytics project decay - from missing ownership and semantic drift to the absence of maintenance practices that keep a data asset reliable over time - and prescribes the specific practices that prevent it.
Analytics decay is the default. Prevention requires intention.
The root causes of analytics rot
The causes are predictable: a report with no named owner, metrics that have drifted from their original definitions, source data changes never propagated downstream, and a team that moved on to the next project before the current one was properly handed over. Each is preventable.
The practices that stop the decay
The whitepaper is not a manifesto for additional governance overhead. The practices that prevent analytics rot are specific, lightweight, and can be built into how a project is delivered rather than added as a management layer afterwards.
What the whitepaper covers
- The specific root causes of analytics project decay - from missing ownership to semantic drift
- Why most analytics investments degrade over time - and why it is predictable rather than inevitable
- The lightweight practices that prevent decay without adding governance overhead
- How to build maintenance and ownership into a project from the outset
- How to diagnose an existing analytics estate and prioritise remediation
Who this is for
Data leaders, analytics heads, and BI managers who have seen previously successful analytics projects lose trust over time and want to understand why - and what to build into new projects to prevent the same outcome.