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Analytics for Digital Transformation

Digital transformation in the enterprise is an extensive, multi-year endeavor. Enterprise applications are heterogeneous and highly interdependent. Release pipelines are multi-faceted and encompass both Agile projects and legacy systems. Automation creates silos with limited visibility to the broader team. The data required to evaluate IT performance is fragmented at the release level, and essentially non-existent at the portfolio level. How can you improve if you can’t measure?
analytics

Enterprise System of Insight

Get metrics to evaluate the progress of your digital transformation.
Icon - Global Measurements

Establish global measurements of IT transformation

Plutora Analytics aggregates release, quality, and deployment data from all release activities across the portfolio to create a system of insight for global measurement of IT transformation.

Icon - Focus on outcomes

Focus on outcomes

Plutora Analytics creates comprehensive datasets and time-based KPIs. Report out on value delivered, articulate achievements in quality goals, and monitor improvements in deployment frequency.

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Achieve disciplined DevOps

Plutora Analytics provides a common repository to transform the way application delivery teams solve problems and measure results. Support localized decisions and unify diverse teams with system level insights that reflect business goals.

value streams

Visualize value streams

Plutora Analytics pulls data from the full value stream, from original business requirements to deployment production. Get a snapshot of the big picture to ensure that local optimization hasn't led to global degradation.

Solve problems, measure results

IT embraces business agility through collaboration across multi-disciplinary teams, faster feedback mechanisms, and continuous learning. Plutora Analytics provides the system of insight to transform the way application delivery teams solve problems and measure results.

  • Global measurements and KPIs of digital transformation
  • Universal access to contextual insights and outcomes
  • Statistical analysis and predictive modeling

Quantify, correlate, predict

Individual metrics tell part of the story, but correlation of portfolio-wide data can reveal deeper truths. Trending data facilitates directional understanding, and outliers often necessitate action.

  • Quantify productivity gains such as more stories per release or more releases per year
  • Correlate production incidents with pre-production activities or resources
  • Identify variables that predict release success or failure

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