Despite the proven value of collecting raw software project data and analyzing it to create actionable, easily digested key performance indicators (KPIs), many firms still struggle to extract, analyze, and organize this data into reports—let alone dashboards or scorecards. If this sounds like your organization, don’t be surprised. In my experience, only a handful of firms have been able to implement truly effective, streamlined reporting systems—and many teams and their leaders don’t even recognize what they are missing.
As user expectations escalate and development and testing costs continue to increase, organizations are seeking additional mechanisms for gaining more insight, earlier, to improve product quality. One contributor to this effort is data analytics and visualization.
In software engineering, if metrics and KPIs are being confused or used interchangeably, it generally means that stakeholders are not defining and building out KPIs, and software teams are not using them effectively. At the end of the day, these incorrect assumptions diminish the quality and amount of actionable information that can help reduce defects and promote a better outcome.