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Data-Driven Decision Making - Software Delivery Performance Indicators at Different Granularities
Optimizing a software delivery organization is not a straightforward process standardized in the software industry. Getting the organization to analyze the data and act on it is a difficult undertaking. This article presents insights into how a socio-technical framework for optimizing a software delivery organization has been set up and brought to the point of regular use.
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Data-Driven Decision Making – Optimizing the Product Delivery Organization
The Data-Driven Decision Making Series provides an overview of how the three main activities in the software delivery - Product Management, Development and Operations - can be supported by data-driven decision making. Applying Hypotheses, CD Indicators and SRE’s SLIs / SLOs enables a software delivery organization to optimize for effectiveness, efficiency and service reliability.
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Data-Driven Decision Making – Product Operations with Site Reliability Engineering
The Data-Driven Decision Making Series provides an overview of how the three main activities in the software delivery - Product Management, Development and Operations - can be supported by data-driven decision making. In Operations, SRE’s SLIs and SLOs can be used to steer the reliability of services in production.
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Data-Driven Decision Making – Product Development with Continuous Delivery Indicators
The Data-Driven Decision Making Series provides an overview of how the three main activities in the software delivery - Product Management, Development and Operations - can be supported by data-driven decision making. In Development, Continuous Delivery Indicators can be used to steer the efficiency of the development process.
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Data-Driven Decision Making – Product Management with Hypotheses
The Data-Driven Decision Making Series provides an overview of how the three main activities in the software delivery - Product Management, Development and Operations - can be supported by data-driven decision making. In Product Management, hypotheses can be used to steer the effectiveness of product decisions about feature prioritization.