Computer Systems Assurance – Methodologies and Technologies to Consider
In our previous blog, we discussed the steps to develop a plan to move to Computer System Assurance (CSA). In this blog we consider the key methodologies and technologies, along with other important considerations to transition to CSA.
There are several important factors to consider to ensure a successful transition to CSA. They are focused on those areas that can provide a major impact to your CSA implementation.
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Leveraging Agile Methodologies
- Leverage Scrum – Scrum is an approach that relies on teams working together in short phases, enabling rapid feedback, continual improvement, and fast adaptation to change to accomplish an objective. By incorporating this agile approach with the CSA implementation the organization will be able to bring in efficiencies and optimization into their processes supporting CSA.
- Test-driven development (TDD) – TDD is a software development methodology that focuses on establishing unit test cases before writing actual code. It’s a method that combines programming, unit testing, and refactoring in an iterative. TDD will enable organizations and teams to reduce the amount of documented testing that would need to be performed as part of the system release.
- Follow Behavioral-driven development- BDD is an agile software development process in which an application is documented and designed around the behavior that a user expects to see when interacting with it. BDD will help reduce the rigor and the complexities of developing test cases from the requirements alone – incorporating the learnings from the BDD sessions into the testing phase will greatly reduce the time for the testing phase as well as bring in efficiencies.
- Introduce early testing techniques – By incorporating configuration and experimentation in lower environments to find defects early, organizations can improve process efficiencies across the SDLC as well get to release faster.
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Leveraging automation and digital technology
- Continuous Integration – The method of automating the integration of code changes from various contributors into a single software project is known as continuous integration (CI). It’s a key DevOps best practice that allows developers to merge code changes into a common repository, from which builds and tests can be executed. Using this approach, organizations can test more holistically and focus more on the integration testing rather than the functional testing.
- Continuous Delivery (CI/CD) – This refers to the ability to securely and swiftly deploy updates of any kind, such as new features, configuration changes, bug fixes, and experimentation, into production or into the hands of users. By adopting CI/CD into the deployment / release processes, quality is incorporated and hence tested at various phases of the process, thus reducing the final testing that needs to be done prior to the release of the product. This further results in a reduction of the workload for the Quality team.
- Employ Automated Controls and Quality Management System (QMS) tools – By leveraging automated controls throughout the organization the quality function can receive feedback quickly from systems that are able to collect that data and provide it in a consolidated fashion. A QMS or Enterprise Quality Management System (EQMS) is an important component to any digital quality framework. The objective of EQMS is to manage content and business processes for quality and compliance across the value chain. This EQMS platform integrates with the IT architecture and data model and facilitates cross-functional communication and collaboration.
It is essential that the EQMS is not siloed. Quality information should be collected as data and leveraged across the organization to make informed decisions.
The EQMS has to also have an interface to other systems whether it is ERP, PLM, supplier quality, vendor management, or other enterprise systems integral to the organization. Those interfaces are critical because that is where data resides, and access to that data is vital for decision making.
EQMS also needs to be mobile. It can’t be at one particular location or region or within one area. The EQMS has to provide the ability to look at data wherever, whenever, and however needed. Having this visibility to the pertinent data allows teams to make decisions faster as well as implement controls that prevent issues and non-conformances further in the processes.
Conclusion
As we’ve outlined, there are multiple methodologies and technologies to consider when the organization is looking to transition to CSA. By leveraging the right mix of tools and methodologies, the organization’s move to CSA will result in lower risks during the transition.
Additionally, it is equally important to have the right skill sets (internal and external) to assist with implementing these approaches and tools. Knowing the various methods and technology and being able to apply them are effectively two distinct requirements.
Why it Matters to You
Organizations making the transition from Computer System Validation (CSV) to Computer Systems Assurance (CSA) will benefit from this information in the following ways. It will:
- Assist in identifying and implementing efficiencies and optimization of the processes supporting CSA.
- Enable organizations and teams to reduce the amount of documented testing that would need to be performed as part of the system release.
- Provide a way to greatly reduce the time for the testing phase as well as provide for efficiencies.
- Enable tests to be done more holistically and to focus on the integration testing rather than the functional testing.
- Reduce the final testing that needs to be done prior to the release of the product.
About Astrix
For over 25 years, Astrix has been a market-leader in dedicated digital transformation & dedicated staffing services for science-based businesses. Through our proven laboratory informatics, digital quality & compliance, and scientific staffing services we deliver the highly specialized people, processes, and technology to fundamentally transform how science-based businesses operate. Astrix was founded by scientists to solve the unique challenges which science-based businesses face in the laboratory and beyond. We’re dedicated to helping our clients speed & improve scientific outcomes to help people everywhere.
