Quality Maturity Model (QMM)

February 15, 2018

Due to the benefits of Shift Left and DevOps, Quality Assurance (QA) has become an integral part of the software developers toolkit. Many financial institutions are now faced with the challenge of maintaining quality standards across software development teams whilst simultaneously automating manual testing backlogs. This is key to realising the benefits of continuous integration and supports the concept of quality at speed – the idea that quality and speed are not mutually exclusive.

Brickendon was called upon by a major global financial organisation to assess their existing software development and QA capability and guide them through a quantifiable roadmap to successfully shift QA responsibilities whilst improving quality of deployed code.

The Challenges

  • Defects slipping into production, exposing the business to operational and reputational risk
  • Long test cycles limiting the organisation’s ability to deliver against strategic business goals
  • Lack of quantitative and qualitative performance measurements hindering progress towards measurable improvements
  • Inefficient software development life cycle (SDLC) processes and coordination within the delivery team (Dev, QA, BA and Production Support) leading to project delays and missed deliverables
  • Disparate test processes and tools increasing the complexity and the overall cost of testing

The Brickendon Solution

  • Baseline 26 KPIs and qualitative maturity levels across eight process areas
  • Identify pain points and root causes across three focus areas:  1) defect removal effectiveness; 2) test efficiencies; and 3) governance
  • Work with the client’s delivery team to outline an end-to-end remediation action plan for each of the pain points, focused on optimising processes throughout the SDLC, from requirements gathering, through development and testing, to deployment
  • Develop and implement project plans aligned with the remediation action plan, tracking progress towards the business goals
  • Advise on the formulation of an automation test strategy and roadmap to achieve 100% regression test coverage, ensuring testing tools are fit-for-use and streamlining automated test execution runs
  • Facilitate the realignment of the existing QA teams to achieve improved QA efficiency, including:
    • 1.Incorporating industry best practices for testing, including quality gates, test strategies, and SLA guidelines
    • 2.Standardising processes and documentation across teams
    • 3.Establishing automation and Continuous Improvement (CI) mechanisms
    • 4.Creating an Agile delivery environment
  • Establish levels of control and provide stakeholders with the insight needed to take corrective measures early in the project lifecycle, reducing risk, and delivering quality software on-budget and on-target
  • Institutionalise a KPI and SLA-driven governance model aligned with business goals, and enhance the data analytics tool to support the defined KPIs

Client Benefits

  • Increased use of automation from 10 to 60% per release, resulting in improved QA test efficiency, reduced testing times, early defect discovery, and reliable and repeatable results
  • Reduced organisational risk prevention with established Quality Gates, ensuring quality is embedded into each phase of the SDLC
  • Improved Quality Maturity levels across seven process areas of policies and governance; test deliverables; functional and automated testing; tools; reporting; environment management; and continuous improvement
  • Established qualitative KPI model that provides senior management visibility into quality throughout the entire SDLC, enabling better decision-making based on metrics
  • Embedded Shift Left practices across all teams supporting the reduction in time lags
  • Document walkthroughs and sign-offs, eliminating ambiguity and redundancy, leading to prompt identification of gaps in the documentation and test coverage, and early changes to test design
  • Automated acceptance testing framework within the development phase, improving the quality of releases into the QA phase
  • Automated test scenario and test case creation, optimising test coverage and generation while also reducing the end-to-end QA test cycle

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