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White Paper

Assurance Transformations — Performance Prediction Model


Organizations are continuously evaluating Quality Assurance (QA) maturity levels, transforming their QA functions, incorporating industry standard models for operations with test Center of Excellence (CoE) setups and test factories to remain competitive. This implies a complete transformation of their QA operations making performance prediction for assurance programs critical.

Organizational Change Management (OCM) is a major challenge for most consultants engaged in providing enterprise assurance transformation solutions.

Some of these challenges include the following:

  • The reluctance of teams to adopt industry best practices
  • The failure to identify the wastages and redundancies in existing processes
  • The inability to align with the strategic QA objectives of the organization

In this white paper, we present a model that predicts the response of an organization to the proposed assurance transformation such as the establishment of a Testing CoE or the definition and rollout of industry standard test process such as the Test Maturity Model integrated (TMMi).

They help predict the organization’s transition curve and effectively manage transformation estimates, challenges and outcomes. As these factors take into account the characteristics of the organization in question, they can be applied to any transformation initiative. The whitepaper includes the following sections:

Case study: A large retail customer – Assurance Transformation
This case study recounts the experience of managing a transformation initiative. A large retailer in the US wanted to establish a TCoE to achieve level-three maturity on the TMMi.

The Phases of the Kübler-Ross curve
A widely used industry model, the Kübler-Ross curve helps explain the various stages of assurance transformations and the corresponding effect on performance.

The model takes into consideration the Kübler-Ross change curve and its stages spanning denial, anger, bargaining, depression, acceptance as well as other key contributing factors. It also describes how a QA organization’s performance can be measured by assigning a weightage to these factors.

The factors identified and defined to enhance and build on the Kubler Ross model here are intended for use by change management consultants, Quality Assurance (QA)consultants, enterprise leadership teams, and stakeholders.

The ideal performance: Change curve
The change curve for a QA organization’s performance during a transformation shows the organization’s performance levels plotted on a scale of ten. The performance scale has been derived from the sample of various QA-related enterprise transformations we have executed across various domains and geographies.

The managed change curve
Ideally, if the transition is managed well, the various challenges associated with each stage can be controlled, productivity levels will not drop and the desired state will be reached with a linear increase in productivity. When measures are put in place to ensure all impacts of change are managed correctly, the QA organization’s performance will not drop. Such a curve – the managed curve – will be linear, a result of managing the change perfectly.

The factors for change stages
We examine the various stages and identify the key factors for each stage to predict performance in the transformation journey spanning:

  • Denial
  • Enthusiasm
  • Anger
  • Bargaining
    • Complexity of business process
    • Complexity of technology
    • Strategic engagements and special interest groups
    • Leadership focus

In the various engagements across domains, where the prediction model has been put to practice, stakeholders have realized the following benefits:

  • Cost: Optimized estimates based on an organization’s characteristics
  • Time-to-market: Improved time-to-market, and expectation management
  • Decision making: Enabled decision creation and prioritization to implement change with deeper insight into the organization’s strengths and challenges.
  • Smooth execution: Marked increase in participation of all stakeholders for a smooth transition

Managing enterprise assurance transformation always presents numerous challenges. The proposed model helps consultants predict the performance change curve for an organization and effectively manage estimations, challenges, and outcomes.

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