DEV Community: Antoine Craske

Leveraging Test Automation Platforms for Continuous Testing Pipelines

Antoine Craske — Mon, 13 May 2024 09:33:48 +0000

Speed relies on robust foundations in software development, especially when aiming for continuous testing and deployment pipelines. A well-structured base is crucial for seamless testing that can support successful software releases.

Moving hastily without a solid foundation is like constructing on unstable ground, resulting in foreseeable problems and squandering resources. A more strategic approach involves analyzing the required production capabilities to succeed in the long run.

This article covers the continuous testing pipeline challenges and required capabilities clarifying where test automation platforms make the difference versus custom frameworks or siloed solutions, highlighting the importance of a steadfast foundation.

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The Challenge of Continuous Testing Pipelines

Continuous testing pipelines are the consequence of multiple activities that altogether form a resilient system supporting fast and reliable deployments. Yet, building such systems requires overcoming multiple challenges within software development.

The software production system can be seen as the sum of “people, processes, and technology” where these three layers form altogether the environment in which teams can build and deliver software with more or less ease.

Each of these layers has specific challenges for continuous testing pipelines identified here starting from the foundations:

Technology: Test Data availability and environment stability
Process: Seamless integration and process visibility
People: Optimizing resource utilization & skill sets.

Starting with technology, a lack of representative test data can compromise the efficacy of tests, leading to inaccurate results. In addition, Unstable environments may manifest in inconsistent outcomes, hindering the reliability of continuous testing processes. According to the Future of Quality Assurance Survey, QA teams spend 10.4% of their time on just setting up and maintaining test environments.

On the process side, a disjointed integration process may result in testing misalignment, causing delays and errors. On top, A lack of process visibility can impede the identification of bottlenecks, hindering overall workflow efficiency and team satisfaction.

Inefficient resource allocation may lead to underutilization, if people can only do narrowed activities, or burnout if they have to handle too many activities with a high manual workload at once — diminishing the overall testing effectiveness.

Each of these challenges has to be overcome for deploying sustainable continuous testing pipelines. Let’s see how test automation platforms can help accelerate the implementation of robust foundations that can enable the entire team.

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Ease Test Data and Environment Stability

Modern platforms have evolved to seamlessly address test data and environment stability challenges. Their added value is to provide standardized technology solutions to common problems and issues faced in managing test data and environments.

The major issues of test data and environment are to (i) make these available for testing in one place, (ii) ensure their stability, and (iiI) deploy them across all environments up to production still guaranteeing availability and stability for different contexts.

On one side, platforms ease test data management with:

Generation of anonymized test data, is not only comprehensive but can also be anonymized, adhering to privacy and regulatory requirements
Variable data for data-driven testing allows the incorporation of variable data through the same test structure, enhancing test diversity and thoroughness
Connectivity to data sources with the flexibility of real-world data scenarios when needed for comprehensive testing through API, databases, or file access.

Complementarily, they provide the environmental foundations:

Application Environment Mapping for a clear and intuitive mapping of application environments, ensuring that testing environments align deployment settings
On-Demand Environment Provisioning enables agility in testing with on-demand provisioning of environments, eliminating bottlenecks and delays of manual setup
Environment Sanity Checks and Monitoring ensure the health of testing environments and addressing anomalies that may arise during testing processes.

These test data and environment foundations can be in place rapidly through the use of a test automation platform. From that base, the next priority is to structure a repeatable and reliable process of continuous testing pipelines where platforms can help too.

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Provide Native Integration Points & Reporting

Test automation platforms understood that they must support the end-to-end development process to accelerate the delivery of valuable software. That’s where they leverage the power of integrations and data points to seamlessly support the flow of iteration.

Teams using siloed “best-of-breed” or custom solutions built in silos miss the capacity to integrate multiple solutions along the process and end-up copying data between systems, and trying to reconcile data sources in reporting solutions to get a fragmented visibility.

On the other side, platforms enable to quickly integrate end-to-end deployment solutions:

Test requirements aligned with the product development flow, ensuring iterative alignment with the team sprints and requirements evolution
CI/CD integrations within the deployment flow automatically triggering non-regression and functional tests before final exploratory testing takes place
Monitoring and operations flow integration providing real-time alerts, and seamlessly connecting with communication channels for efficient collaboration.

Once that interconnectivity is in place, teams can leverage test automation platforms to get an end-to-end visibility thanks to:

Single Source of Truth eliminating the need for manual report creation, distribution, and discussions for the entire team
Automated standard metrics computation such as coverage and stability ratio, and offering additional insights that extend beyond conventional metrics
More time for decision-making with analytics tools embedded within the platform providing valuable data over time for informed strategic decisions.

Teams equipped with environment foundations jointly with integration points and reportings have now more time for added-value activities. Yet, test automation platforms enable teams to go for an extra-mile optimizing the skill set requirements in continuous testing.

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Reduce Skill Set Requirements & Saturation

The demand for a skilled and adaptable workforce being unbalanced worldwide, testing platforms play a pivotal role in reducing skill set requirements and mitigating team saturation with their intuitive interface and process standardization.

The fast pace of innovation pushes people to rapidly evolve their skill sets to better support the team, but they don’t have time to learn everything. Profiles with proficient skills for testing web, mobile, API of different typologies are hard to find, and temporary.

Test automation platforms come to an help first by reducing skill set requirements with:

Intuitive user interface allowing team members to self-learn within a few hours, eliminating the need for extensive training
Standardized approach to use-cases enhancing extensibility and ensure that testing processes remain comprehensible and consistent across various scenarios
Library of e-learning training with self-paced training modules complete with certificates, motivating and empowering team members to enhance their skills.

At the same time, platforms optimize engagement and productivity reducing saturation through:

Accelerated learning curve lowering the time required for team members to learn and contribute effectively, maximizing the efficiency of the testing team.
Collaborative testing activities allowing to share testing activities, facilitating reviews and collaboration from development to business teams.
Minimized time on non-productive tasks with SaaS models eradicating the need to invest time in maintaining frameworks or infrastructure.

Platforms empower teams to focus on delivering high-quality results removing unnecessary bottlenecks. These overall foundations enable teams to focus on more added-value activities : implementing their testing strategies and fostering continuous improvement.

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Better & Faster Continuous Testing Pipelines

Continuous testing pipelines challenges are numerous, but can be overcomed with a proper planning of required capabilities and leverage of ready-to-use test automation platforms, already matured to standardize and accelerate continuous testing use-cases.

We saw that the tryptic of “people, process, technology” must be correctly implemented to structure robust foundations to avoid resource wastage and team demotivation. It is about recognizing that speed is a consequence of an efficient system and the first goal in itself.

Teams must embrace that paradigm deploying the minimum capabilities that enable them to test and tailor the end-to-end continuous testing pipelines with rapid iteration, something test automation platforms accelerate with ready-to-use features.

Platforms are enablers of present endeavors but also architects of future innovations. Their inherent adaptability positions them as likely integrators of artificial intelligence, paving the way for sustained innovation, for those who, previously adopted them.

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5 Systemic Changes from Test Automation to Continuous Testing

Antoine Craske — Wed, 20 Dec 2023 07:12:01 +0000

5 Systemic Changes from Test Automation to Continuous Testing

In the dynamic landscape of software development, the journey from traditional test automation to continuous testing has become pivotal for organizations striving to achieve agility, quality, and sustainable delivery.

However, in today’s complex digital ecosystems, relying solely on automation for testing often falls short in meeting the ever-growing demands for quality, speed, and efficiency requiring to transition from test automation to continuous testing.

But continuous testing requires much more than the mastery of test automation by dedicated teams. It necessitates a shift in mindset, processes, and culture to develop a comprehensive understanding of the software production components.

This article shares 5 key changes to evolve from test automation to continuous testing leveraging a systemic approach enabling to align the software production system to the continuous testing ambitions.

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Set end-to-end ownership with objectives

System transformations require a clear ownership and accountability within organizations to initiate and sustain the changes. Else, the actors will return to their day-to-day activities With many external pressures,

Continuous testing being an embedded set of activities as part of the software production process, each phase must clarify the specific activities that contribute to the achievement of continuous practices for better and faster software delivery.

The most essential phase to develop from test automation are:

Design ensuring that requirements and tests are collected the earliest
Implementation having tests done close to development or fixes
**Operate **to reuse automated tests as part of deployment and operations.

Each of these phases require a clear responsibility model for software teams eager to develop continuous testing. Even if the “who” can differ, each step requires an owner to make the task happen and a reviewer that can accept or reject the work based on criteria.

These foundations of accountability are necessary for the actors to take ownership of their destiny of software delivery, clarifying that continuous testing is a means to help them achieve their objectives of better and faster release.

Provides self-service standardized solutions

Software teams have limited resources and attention to use wisely to meet the demand of multiple stakeholders and objectives. It means that the additional responsibilities for continuous testing must be eased to provide the necessary attention.

Technology comes to help to automate and provide self-service but must be composed correctly to let teams evolve from test automation to continuous testing focusing on the key use-cases that will make the difference.

Continuous testing requires to provide the following solutions:

**Requirements and tests referentials **automated link
**Self-service test definition and execution **across environments
**Native reporting and analytics **for fast decision-making.

Software teams used to test automation do get value from their automated tests but usually miss the end-to-end integration listed above that make them win numerous hours and cycle-time for each software release.

Robust self-service standardized test automation solutions are the necessary ground to let software teams use their resources to make sure that automated tests are defined early, implemented and iterated with developers, and used up to production.

Systematically defines requirements in design

Test automation led by quality and engineering teams will naturally tend to be optimized for their own objectives. One key risk if interactions are missing with customer and product areas is to develop huge unit and integration tests suites that miss the business link.

The systemic approach can be used to make sure that tests, whether manual or automated, are assessed as part of the initial design discussion as part of review mechanisms. That way, the team has a regular encounter to keep aligning the functional needs.

The main value of these reviews are to keep shifting-left the test automation effort to meet the users need and product goals. If the team is unable to present automated tests understood by the product team, they failed in their automation effort.

These early sharings are also good opportunities to align expectations before the coding work ever start, aligning for example the test effort needed based on the feature maturity, or adjust it based on concrete issues like team availability.

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Drive results and improve based on measures

Test automation efforts must enable the team to reach a particular destination. While an inspiring vision is required and helps to motivate, concrete objectives and deliverables will push the team to act and adapt based on their experimentation.

Measures can be challenging to choose as they can incentivize the wrong behavior, miss particular points, or make the team lose sight of the desired end-result. That’s why the objective must be kept clear like in OKRs, and supporting measures defined.

A practical model is to define up to 3 metrics of different types:

Outputs are basis metrics following the result of a productive activity (e.g. test executed)
Outcomes measures the contribution of the activity to a broader process like lead-time or change failed rate
Impacts represent the external results of activities usually linked to objective that can be business, customer, or product-driven

That framework measurement must be in place from the start to know the starting point, the desired target, and intermediary steps the teams must pursue in their iterations. From there, a regular assessment is required to adapt activities, and in some cases the metrics.

The tooling in place in your software delivery pipeline will usually provide metrics you can rely on. In all cases, a validation of the computation and standardized data collection must be performed so that metrics can be trusted and shared within the organization.

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Create an ecosystem of community learning

Last but not least, the software production having its actors at the center requires specific activities to let them develop the gap of skills from test automation to continuous testing, where more collaboration and adaptation is required.

Teams need executive support here to devote a small portion of their time for sharing and learning the new practices. Ideally, the emerging community of practices are best when supported by executives that can valorize improvements being led.

At first, the focus is to make sure that sharing is happening with clear leaders and an agenda to show first results. From there, the objective is to encourage collaboration, knowledge exchange, and peer-to-peer learning among teams.

On top of developing the skills gap from test automation to continuous testing, this ecosystem of learning will be the accelerator of best practices adoption in different teams making a cascading effect on the deployment of continuous practices.

When things are naturally done in the day-to-day because they make sense and bring value to the team with continuous improvements is the pivot from test automation to continuous testing you can reach with this systemic approach to software production.

Accelerate Test Velocity: Key Strategies for Faster Time-to-Market

Antoine Craske — Fri, 07 Jul 2023 06:16:36 +0000

In today’s fast-paced and competitive business landscape, slow time-to-market goes beyond just a delayed product release. When an organization takes longer to introduce its offerings to the market, it not only loses valuable opportunities but also exposes itself to the risk of being outshone by competitors who excel at swift delivery.

However, focusing on faster time-to-market alone is no longer sufficient to stay ahead of the competition. It is essential to recognize that the true challenge lies in outpacing competitors and delivering value to customers before others can seize the opportunity.

As a result, companies have turned their attention to accelerating test velocity as a means to expedite their delivery cycles. While many organizations have made strides in improving their testing processes by focusing on running more tests faster, they often reach a plateau where further enhancements are necessary to achieve true acceleration and stay ahead in the market

In this article, we will delve into the fundamentals of Quality Assurance, its key principles, methodologies, and its vital role in delivering excellence.

Quality Engineering transcends the notion of simply running more tests faster and delves into building a robust and productive software production system. It recognizes that speed is not an isolated objective but rather the outcome of a holistic approach that prioritizes quality throughout the entire development lifecycle.

Start by defining success on three perspectives

When striving to accelerate test velocity and improve time-to-market, it is common to focus solely on optimizing test execution and infrastructure. However, this approach can lead to time wastage if the desired goals and outcomes are not clearly defined from the beginning.

To avoid this, it is essential to begin by defining what success looks like in the context of the project or initiative. To achieve success in accelerating test velocity and achieving faster time-to-market, it is crucial to start by defining success from three perspectives: outcomes, KPIs, and metrics:

Outcomes: These are the tangible business values generated by specific software outputs, such as the introduction of new features. It’s important to note that outcomes are not solely measured in numbers, but they encompass the overall value and impact on the business.
KPIs (Key Performance Indicators): KPIs are measurable numeric indicators that provide insights into the business value from various angles, including customer experience, financial performance, and operational efficiency. Examples of KPIs can be NPS (Net Promoter Score), churn rate, or contact per order.
Metrics: Metrics are supporting measures that help track the progress towards the desired direction. They serve as benchmarks for implementing new processes and ensuring that the ecosystem is moving forward. For instance, a metric could be the execution of test campaigns within five minutes after each code build or the lead time from defect identification to resolution.

Speed outcomes and KPIs: These metrics will measure the true acceleration of cycle time, delivery time, and overall stability to prevent rework and ensure a smooth development process.
Quality KPIs and metrics: These metrics assess the extent to which the focus on building quality is progressing and how it contributes to speed indicators simultaneously.

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That stage of success definition is the foundation to align your effort to accelerate test velocity and time-to-market. The next step is to identify the key issues that limit the speed and efficiency of software development in regards to our definition of success.

Identify more than software limiting factors

Software limiting factors enable us to gain insights into the specific areas that hinder performance and impact outcomes. They are fundamental to the concepts of value-stream and lean techniques to unlock the performance of a given system.

This stage is crucial to prevent scattered priorities and requires effective analysis, critical thinking, and problem-solving techniques. Employing methodologies like impact mapping can be valuable in achieving this objective, as they provide a structured approach to identifying and addressing the key factors that limit software performance.

Limiting factors help us filter and prioritize problems by identifying the specific factors that impact the overall performance of a system. By focusing our efforts on these key issues, we can effectively address the root causes of performance challenges, especially in complex software delivery processes where multiple factors may contribute to certain symptoms. This approach allows us to allocate resources efficiently and tackle the most significant issues that are hindering the system’s performance.

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Gaining a holistic understanding of the entire system is necessary to direct our efforts towards the most impactful areas. Focusing solely on the test process, such as the time taken for execution is not the priority if defining acceptance criteria takes twice as long, surpassing purely technical concerns.

Design not only the test, but the supporting system

A well-designed supporting system is essential for effective test automation, execution, and maintainability. Neglecting upfront design often leads to software that is overly complex, inflexible, and costly to maintain. Investing in test design is necessary for accelerating test velocity and time-to-market, but it goes beyond designing the tests themselves.

The true investment in test design following our philosophy of Quality Engineering is that the design is not limited to the test: we also need to address the supporting forces of the software production system.

The system can be seen in five domains to inject quality:

Methods focusing on the collaboration and processes
Architecture including technologies and infrastructures
Management to animate the team and drive forces
Organization to structure investments, teams and interactions
Skills to make sure the expertises is acquired.

One example is to systematize new methodologies like BDD as part of the definition of user stories, aligning the roles and organizational responsibilities between the product owner, developer, and quality roles for such tasks to stick in the long run.

Another one for test environments management is to consider technology to provide repeatability and automation, but combining it with Devops and FinOps methods to make them scale only when needed as part of the delivery pipeline, instead of keeping all non-production environments always on.

Automate what may stay, or is staying

The temptation to automate everything during iterations is strong, as it eliminates the need for future consideration and becomes a part of recurring executions. However, test automation comes with costs for development, execution, and maintenance, requiring careful consideration before implementation.

A practical approach to assess the need for automation is to assess the:

Value per automation usage.
Cost per automation usage.

The value per automation usage extends beyond cost reduction and includes benefits such as process reliability, enabling 24/7 execution, or stability even with team turnover. On the other hand, the cost per use helps determine the frequency at which a particular process will realistically occur, allowing for an initial assessment and continuous review of whether automation should be implemented or maintained, as some tests may be heavily utilized at a given time, their relevance may diminish as the product evolves.

If the need for automation is confirmed, automation should only be initiated only after the process has been executed manually or in a hybrid automated manner a few times. This approach enables rapid improvements based on the lessons learned from initial trials. As Bill Gates famously stated, “automating an inefficient process will only amplify its inefficiencies.”

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Streamline collaboration by minimizing hands-off

Minimizing hands-off is a crucial requirement for achieving speed, as it aligns with the principles of lean methodology. Each hands-off point in the value chain introduces disruptions such as information loss, changes in personnel, and potential errors, all of which hinder test velocity and time-to-market.

Tests often experience these disruptions, whether it’s between product owners, developers, and quality professionals in terms of acceptance criteria or defect management, or between operations and quality professionals regarding observability and monitoring.

Three key areas require focus:

Collaborative test management ensures comprehensive test definition.
Integrating a continuous testing infrastructure into the software delivery pipeline and processes enables efficient test execution.
Collaborative portals that combine requirements, execution, and defect management capabilities are essential for comprehensive test reporting.

Shared way of working and an enabling automation mindset for the definition of success are fundamental to that collaboration streamline.

Build system capabilities over project activities

Large projects pose challenges in terms of uncertainty, risk, and adaptability, which is why breaking them into incremental pieces of delivery is recommended. However, this approach can result in higher setup costs for each increment, hindering fast time-to-market.

To overcome this challenge, a shift in the mindset of Quality Engineering is essential. It requires investing in the software production system beyond individual projects and incremental deliveries, treating test design, environment setup, observability, and other test velocity requirements as system capabilities rather than project-specific activities.

Embracing the paradigm of platform engineering and quality architects enables teams to deliver and learn at a rapid pace, leveraging system capabilities for iterative and efficient development with a focus on quality and speed.

Implement tests at the lower execution cost

Failure to consider the costs of test execution from both a test and business perspective can lead to significant challenges. It is important to understand why, in relation to the test pyramid, prioritizing lower-level execution tests is preferred.

First, there is the notion of test frequency with 4 options:

No test executed
Unit test as part of the build
Other tests as part of CI/CD
Other tests on a continuous basis like monitoring.

Then the notion of costs which is not only what to pay to execute the tests but the overall costs to build, run, and maintain as an organization including technology costs. Think of your tests at the road toll that you can take to go faster in some cases, and sometimes only for comfort when you can even be slower. Your business doesn’t need that.

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Time-to-market and Test Velocity with Quality

Accelerating time-to-market and test velocity with quality requires to go beyond a narrow focus on tests alone. Organizations must actively build a software production system that enables fast iteration and embraces quality as a core principle.

By investing in test design, identifying software limiting factors, devising effective automation strategies, and minimizing hands-off points, companies can optimize their processes and achieve faster time-to-market. They should also consider the comprehensive concept of test execution costs, including direct expenses, organizational implications, and technological considerations, to make informed decisions about testing strategies.

Time-to-market and test velocity requires an active approach where organizations must shift their mindset to embrace Quality Engineering. The success is sustainable speed powered by Quality in the overall software production system.

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The Role of Continuous Testing in Reducing Technical Debt

Antoine Craske — Mon, 08 May 2023 06:26:27 +0000

Software development has become an increasingly competitive and rapidly-evolving industry, with businesses and organizations seeking to deliver high-quality software products that meet user needs and expectations before the competition.

However, with this rapid pace of development comes a common challenge: the accumulation of technical debt. Defects and issues piled up over time result not only in higher development costs but also impact competitiveness with a slowing rhythm of iteration.

Technical debt is a significant challenge for many organizations. Development teams with a medium to high levels of technical debt reported that they spend nearly 50% more time than low-tech debt teams on bug fixing and understanding existing code, and as a result, spend nearly 40% less of their time working on developing new features.

Development teams need more than Agile and DevOps practices to address technical debt. Continuous Testing, a software testing approach that emphasizes testing early and often throughout the development lifecycle is one game-changer for organizations.

This article explores the role of Continuous Testing in reducing technical debt and improving software quality and practical recommendations for getting started with this approach in your development process.

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Technical Debt, a Business Pain

Technical debt can have a variety of causes, including human factors, organizational issues, and pressure to deliver results quickly. A major problem accumulates over time if no action is taken, affecting both customer satisfaction and the organization’s bottom line.

As humans, we tend to avoid something when it is hard or painful. The same happens with software systems with technical debt: the team takes shortcuts and compromises to meet deadlines. But avoiding pain in the short-term leads to much bigger pains in the mid-term.

The business impacts of technical debt can be significant

Negative user experiences such as slow load times, crashes, or security vulnerabilities, can lead to lost revenue, decreased customer loyalty, and a damaged reputation.
The increasing cost of changes required to fix the technical debt can impede a company to deliver new features to improve its value proposition.
Slowing down delivery times as development teams struggle to work around code issues makes the organizations slower than the competition.
Accumulation of delivery risks, making it more difficult to meet project deadlines and causing other deployments, security, or reputation issues.
Lower team morale and motivation as developers struggle with the frustration and complexity of working with poor-quality code.

The impacts of technical debt make it a critical aspect to address proactively through strategies. To do so, they need effective detection mechanisms that enable them to identify technical debt early on in the development process and implement systems to minimize the accumulation of debt on a continuous basis.

Technical Debt and Continuous Testing

Addressing technical debt requires more than just tools and processes. It requires creating a fostering environment larger than the development team encouraging them to prioritize debt and take ownership of technical debt reduction and overall software quality.

Faced with technical debt, teams have 3 options:

Do nothing and accumulate debt
Start paying the interest to reduce debt
Erase the interest by replacing the system.

Hopefully, a decision is taken to first refactor the application.

Reducing technical debt needs a proactive, systematic approach that addresses issues before they become major problems, and makes it easy to change the code. It requires balancing methodologies, organizational, and technology matters.

The following steps enable an incremental approach to technical debt:

Initiate the technical debt backlog
Raise technical debt awareness
Prioritize the debt backlog
Reduce debt with confidence
Contain debt continuously.

While the steps outlined above provide the necessary steps to reduce technical debt in many contexts, the capability to perform them with quality and speed is only reserved for a minority of organizations that have implemented differentiating practices.

Reducing technical debt is harder than when building new features as it is usually not properly documented, people that worked on it may have left, and it is hard to know if we are breaking something. That’s where Continuous Testing makes the difference.

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Initiate the Technical Debt Backlog

One of the first steps in addressing technical debt is to identify and prioritize the issues. This involves creating a technical debt backlog that lists all the known debts and assigns them a priority based on their impact on the software product.

The team can start by listing technical debts based on its knowledge of the product and the recurring issues they are facing, organizing them into different categories. However, the value of the backlog can only remain if it corresponds to reality on a regular basis.

Technical debt Backlog

Continuous Testing is a valuable practice for initiating the technical debt backlog, as it can help identify technical debt early on in the development process, reducing the amount of time and effort required to identify technical debt.

Automated verifications can then serve as a continuous input to keep the technical debt backlog up-to-date. In addition, teams can identify and fix new debt items earlier in the process as being detected as part of the flow of work.

Raise Technical Debt Awareness

Now that the team has an identified technical debt backlog, it has a factual basis to convince stakeholders about addressing it. To succeed, the argumentation has to go beyond technical matters to link software debt with key business issues.

Stakeholders’ concerns to satisfy customers and business requirements are not firstly focused on technical debt. One must make the link between late features or customer experience issues caused by technical debt to put the topic on top of the priorities.

Continuous Testing increases technical debt awareness with:

Factual metrics among stakeholders
Regular refresh of supporting data
Link tech and business problems.

For example, Continuous Testing can provide data on the number of bugs and defects associated with technical debt, the time required to fix them, and the impact of technical debt on the overall quality and performance of the software product.

Developers with real-time feedback on the impact of technical debt encourage them to take proactive steps to address the issue, rather than waiting for it to become a significant problem with exponential costs of debt reduction.

Prioritize the debt backlog

Good and bad technical debt are two types of technical debt that software development organizations commonly face. The key difference is between how the debt is introduced and the future plans in addressing it or not.

Good technical debt is incurred deliberately to achieve short-term goals, such as new features or fixing bugs, with the intention of paying it back in the future. In contrast, bad technical debt is typically unintentional and accumulates over time.

Continuous Testing can, first of all, help in materializing an existing — and usually increasing amount of unintentional technical debt, whether through direct debt metrics or through team performance issues like slow delivery time and high rework rate.

In addition, Continuous Testing helps to identify patterns in technical debt issues with a set of historical metrics linked to the software development process, enabling organizations to develop targeted strategies for addressing the underlying causes of technical debt.

Reduce Debt with Confidence

Refactoring an application can be a daunting task, especially if it is a large and complex system. It often involves making significant changes to the codebase, which can introduce new bugs or regressions if not properly tested.

Without a reliable testing process in place, refactoring an application can be a risky and time-consuming endeavor the development team always pushes to the next day. The creation of a safe refactoring environment is therefore a necessity for debt reduction.

This is where Continuous Testing comes in.

Continuous Testing makes application refactoring much smoother and less risky with a reliable and efficient way to test software changes. Leveraging non-regression tests used for feature delivery, the team can address technical debt items with the same tests.

That capability of changing the internals of an application with verifications giving the team the confidence to move forward is a game-changer. Technical debt changes from a painful task to something part of an interesting continuous improvement dynamic, much more motivating.

Contain Debt Continuously

We covered the human cause of technical debt, where pain avoidance and hope of a better tomorrow makes people avoid the management of technical debt. That behavior is negatively incentivized when there is no regular reminder of debt piling up in the background.

Technical debt has similarities with financial and other debts. If people would feel the future and continuous pain, many would consider avoiding taking credit in the first place, or at least, minimize the amount and shorten the payback period.

Continuous Testing acts as a continuous pain reminder about the existing technical debt. They see it through dashboards, and it links to daily issues requiring them to iterate with the quality and speed they strive for.

These Continuous Testing feedbacks are an essential part of streamlining processes with lean practices. People have to feel the pain regularly to start inverting the vicious cycle, addressing structuring issues caused by technical debt.

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Control Technical Debt with Continuous Testing

Technical debt can have serious consequences for organizations if left unaddressed. It can slow down delivery, increase risks, impact user experience, and accumulate costs over time until a breaking point can be reached in the worst cases.

Continuous Testing plays a vital role in reducing technical debt by allowing organizations to address issues on major layers of the software development process from code, infrastructure, and testing in itself.

Organizations that prioritize technical debt embracing Continuous Testing will be better positioned to deliver high-quality software through a lean pipeline, staying ahead of the competition in the rapidly evolving digital landscape.

How to Empower Your Team with Test Automation

Antoine Craske — Sun, 19 Mar 2023 20:14:15 +0000

Test automation is a critical capability that makes the difference in delivering software with quality and speed, letting the team adapt faster software changes to meet the quality requirements. But its implementation is hard.

Test automation has become an essential tool for organizations looking to stay competitive and deliver high-quality products on time and on budget in the rapid pace of technological change and increasing complexity of software systems.

The integration of test automation activities in the software delivery pipeline requires the transversal collaboration of multiple actors not necessarily familiarized with quality or testing activities — and that’s why a leader needs to empower the team to succeed.

Organizations, pressured by accelerated competition, have to lead fast transformations to capture opportunities before challengers do. This article shares how to make the difference when it comes to accelerating software delivery with test automation.

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Share the value of test automation

Your team has to understand that test automation is not just a tool for quality assurance or testing teams. It is a valuable capability to develop for the entire software development process and for the business.

The value of test automation lies in its ability to improve the quality and speed of software delivery, which in the end helps the company to develop better products and services for its customers more quickly and more efficiently.

Software teams that try to accelerate without test automation face accumulating technical debt that sooner or later translate into painful issues like recurring bugs, extra hours to fix problems, or performing recurring manual tests that are of low interest and too slow.

Your team has to understand the following benefits of test automation:

Faster and stable software delivery
**Confidence **to rework and change software
Save time for more valuable activities
Better understanding of expected software behavior
Production efficiency by detecting and fixing issues earlier
Maintain requirements up-to-date improving organization stability

The recommended way to share the value of test automation is to acculturate your team with external examples of successful usage of test automation for similar problems you are facing. That way, people can start to consider test automation as a realistic solution for what they want to improve, avoiding feeling forced to do so.

From that point, your responsibility as a leader is to envision the path to follow, share lights out of the tunnel, and help them to visualize the future with better outcomes than the current situation leveraging test automation.

Lead the way for the first steps

Having the team convinced about the value of test automation is the first step. Still, much ambiguity will remain about which actions to follow, whom to involve, and what to focus on as a priority.

The responsibility of a leader is to navigate that initial fog, deconstructing the complexity into clear outcomes the team can follow. The clarity of actions will enable the team to focus on the first actions to implement test automation.

As a leader, you have to clarify:

What are the desired outcomes
Which scope is the priority
What will change concretely
Who is involved and should do what
Which external resources are needed.

The definition of this initial perimeter enables you to set the stage for an early-win team and share more broadly in the organization about the change. The advantages of a small team are to test and adapt new processes more rapidly with minimum effort.

The team will encounter roadblocks and issues in the first steps of implementation. Your role as a leader is to help them in problem-solving to demonstrate that the subject is essential and how you expect things to be solved.

As test automation involves technology, the tooling question will be a structuring one to address early on to set your team on the right track.

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Invest in the right tools and technologies

Adopting the right technology makes test automation more efficient, effective, and accessible for your team to set up and maintain in the long run. Once again, your responsibility as a leader is to step back to improve the decision taken for your organization.

Many tools compete in the test automation space to help teams deliver better software. Your value is to set clear priorities of what will be a game-changer for your organization, and what should not be looked at all.

The important part is to clarify the structuring requirements specific to your context:

Which test techniques are more valuable first?
What integrations **are must-have for example with **CI/CD?
Does the tooling support better collaboration, sharing and reporting?
Are tests implemented with low-code and coding, which languages?
Can you combine multiple test techniques like Web & API?
How do functionalities ease setup and maintenance?

Answering these questions will clarify the most important functions and requirements your organizations need to capture value from test automation. The next step is to translate the requirements into possible technology solutions.

Test Management, Test Execution, and Test Reporting are the major vertical solutions needed to implement test automation. Specific narrowed tools exist for each vertical, but there are also unified test automation platforms like LambdaTest that bundle the offer.

The main capabilities to look at in your choice is the usability of the solution by different profiles to foster end-to-end collaboration in the organization. The availability of on-demand devices, native reportings, and intelligent features is also a strong factor of creating more value with test automation, and of the capability of the tool to be innovative.

Learn from results to replicate

Learning from the results of your automated tests enables you to replicate successes and avoid mistakes in the future, and develop a continuous improvement culture that is essential to increase the maturity of software quality practices.

One of the key benefits of test automation is to generate useful data that can be analyzed to identify patterns and trends. This data can be used to identify key areas of improvement and identify bottlenecks in processes to know where to focus your team’s efforts.

Based on the data, you can, for instance, identify which tests are taking the longest to run, are failing most frequently, and providing the most value. With more maturity, you can even prioritize test execution based on their value to get faster feedback loops.

But learning is not only about the tests and technology.

Performing retrospectives with your team enables you to discover other areas of improvements such as in processes, skills, and even organizational issues, providing you with the big picture necessary to solve structuring problems.

That learning process will support the expansion of test automation practices in your organization much more easily. Leverage also internal influencers and people ready to act as key users to diffuse more efficiently what works best in your context.

With the right tooling, you can accelerate the deployment of test automation by providing on-demand training, resources, and ready-to-use templates. You then have to continuously encourage collaboration and communication to keep improving in the long run.

You can also empower your team faster and save them valuable time by addressing key challenges of test automation right from the start.

Anticipate main challenges by design

Each organization is different, but common challenges will be faced when implementing test automation, whatever the context. One essential responsibility of a leader is to address them early on to set the team in the best conditions to make a difference.

Managing changes in organizations is about evolving in realistic transition stages that will bring enough value and manage the risks involved. Correctly size the challenges of each transition will sustain the team’s momentum and motivation.

Here’s common test automation challenges to address early on:

Produce valuable outcomes by focusing on concrete problems where test automation can makes the difference and show its value to the organization
Reduce initial cost and effort of implementation limiting scope, tools and processes to the essential, and using SaaS to limit capital expenditures
Availability of skilled and experienced profiles you can manage with internal mobility, external expertise, and complement with on-the-job training
Limit maintenance and updates efforts requiring to limit automation at first to increase its stability and ability to update them with software changes
Clarity of leadership and coalition leading first, and progressively defining a responsibility model to spread test automation responsibilities across teams

Leaders have to balance the competing demands of different stakeholders and priorities to address these challenges. It requires proactivity and adaptability to effectively adapt the value proposition of test automation to each stakeholders interests.

Anticipating issues is the hard part of leading transversal changes in organizations like test automation. but will contribute to the most important goal of supporting the organization in remaining competitive today’s digital competition landscape.

Empowering for Better and Faster Software

Test automation creates a differentiating advantage for organizations searching to continuously deliver Quality at Speed software. More than technology, test automation favors an end-to-end collaboration on the delivery of better and faster software.

Your responsibility as a leader is to develop a test automation capability by empowering your team to overcome the first obstacles and set the right foundations that will generate valuable outcomes for the organization, to then be deployed more broadly with other teams.

There’s no valuable transformation without challenges — that’s where a leader able to empower the team can unlock the potential of each team member to solve whatever problems emerged to progress towards the delivery of better and faster software.

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Conclusion

Empowering your team with test automation is a journey leaders must be able to lead at different parts of the organization to succeed. It is not about one-shot efforts, but about leveraging test automation as the accelerator of business transformation.

Shift-Left or Shift-Right: A Question of Quality At Speed

Antoine Craske — Fri, 11 Nov 2022 11:00:22 +0000

The formulation of a question determines how much we understand a problem, and influences how we might answer it. This makes us wonder if asking “Shift-left vs. shift-right?” as an opposition to these two practices is the right way to formulate the question of improving software delivery for quality and speed.

The software lifecycle is an end-to-end flow of value starting from the business ideas to its actual value delivery in production to a growing base of users. Shift-left, shift-right, and even practices in the middle of the flow all contribute to the success or failure of software changes, requiring us to look at the big picture before deciding what to do.

The first thing is to understand what each practice can bring to improve software delivery, to then perform an assessment that will support the definition of an optimized action plan. This article provides you exactly with that structure to let you answer the question of “Shift-left versus Shift-right?” maximizing quality and speed across your software lifecycle.

Shift-right gives the customer and operations priorities

Shift-right consists in performing quality activities towards the customer experience in production following the deployment and release stages. Its objectives are to measure and improve quality by confronting ourselves with the value delivered in production environments where the live customer experience is happening.

“Shift-right lets teams access the joy and pains of the customer experience.”
— Antoine Craske

One significant benefit of shift-right is to provide the most accurate data from a customer point of view as directly performed in the production. Staging environments can be used to some extent but hardly reflect the reality of the traffic, and some events only happen in the target environments like infrastructure instabilities, and network latencies, among others.

Another significant benefit of shift-right is to focus different profiles on the same and factual objectives above their local priorities. Product owners, software engineers, and testers can all collaborate on customer journey performance supported with factual metrics, building up an internal culture of continuous improvement of business and technology.

Customer journey monitoring is an example of business-focus methodologies measuring the paths taken by users on the digital experience channels. Its value is to provide visibility about the performance of major paths and their areas of improvement, but also on recurring issues, users can face like error pages resulting from bugs or unmanaged exceptions.

Site Reliability Engineering (SRE) best represents the technology focus of shift-right with techniques such as Progressive Delivery or Chaos Engineering where improvements are continuously measured with the golden signals of availability, response time, error rate, and latency of services in production, all giving inputs for upstream improvements.

Testing in production with shift-right for the right reasons can therefore bring major quality improvements for what makes sense to be measured there. For other cases, it is best to implement quality improvements right from the beginning with shift-left.

Shift-left improves quality and speed by design

Shift-left emphasizes quality practices earlier in the software lifecycle, up to the initial planning and design stages where things are only on paper and can be easily changed. Its effective implementation is not easy, requiring the collaboration of multiple actors with different priorities, not necessarily familiar with the requirements and design phases.

Organizations that can shift left benefit from increased quality and speed with minimal rework in later stages. The key is to implement systematic practices of reviews and testing that provide rapid feedback on key assumptions and quality requirements. Defects detected at the stage can be quickly corrected at a much lower cost.

Shift-left methodologies also have the two prisms of business and technology.

Shifting left on the business relies on assessing customer and functional requirements as early as possible, wherever in the planning phases improving the priorities to maximize the potential value delivery, or in the design phases, making sure that key customer requirements will be answered in the software implementation that will follow.

The technology side of shifting-left is about non-functional requirements such as security, performance, and reliability. These can be addressed with checklists to identify the most important ones, to then define deliverables that will answer these requirements once the product will be built in implementation stages.

While Shift-left and Shift-right are important, the core of the work is to build valuable software that relies on good code in the first place, at the middle of the software lifecycle.

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Continuous delivery brings faster iterations

Software implementation is largely influenced by the paradigm of Continuous Delivery and Software Craftsmanship respectively pushing for faster cycles of delivery through automation and well-crafted software from the start. The key objectives are to support faster business iteration, maximize the business value delivery, and contain technical debt.

The focus of code implementation are the software engineers that emerging platform teams consider as their customers. They must be able to leverage self-service, automation and insights for frictionless iterations code implementation of code delivery with reliability and confidence leveraging automation and testing.

Organizations that embrace such paradigms leverage continuous testing and continuous monitoring practices to accelerate their cycles of iterations and value delivery. But their main problem is the increasing complexity and size of the codebase that over time, becomes harder to maintain and slower to release.

Shift-left and shift-right helps with proper software design or customer journey monitoring but do not solve all issues. Specific solutions are appearing on the market to keep the rhythm of software delivery even with a growing codebase, providing ways to build, deploy and test the minimum of code impacted by a proposed changes

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Practices of software craftsmanship combine software production and testing to improve the core of the software lifecycle like hexagonal architecture, test-driven development (TDD), or more generally the Agile Testing framework to adapt the testing techniques — whether manual or automated — depending on the context of the product.

Now that we understand that the question is not “Shift-left or shift-right” as each stage of the software lifecycle must and can be improved for quality at speed, one question remains: where to start?

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Shift-left or shift-right depending on the limiting factors

We can be tempted to improve all parts of the software lifecycle, launching many improvements in shift-left and shift-right, hoping to drastically improve quality and speed across the software lifecycle. But most of the time, it is a waste of resources where people are busy instead of being productive and can become a bad habit.

The performance of any system is limited by its weakest point, making it the only priority to tackle; actions done outside of the bottleneck will not affect the system until the weakest point is improved. This behavior is an opportunity to help us prioritize our initiatives focusing on removing bottlenecks of quality and speed across the software lifecycle.

Techniques coming from the manufacturing world make a lot of sense in the software world that in the end is a flow of work that must be optimized for value delivery. Many frameworks have common points to start by understanding how things work and what are the problems before planning, implementing, and measuring improvements.

The same logic can be used in the software. Methodologies must be adapted to the software specifics like the software lifecycle stages and leverage the access to advanced automation and scaling capabilities. The main challenge in software is to visualize the distributed flow of work making it complex to get an end-to-end vision of the multiple integrated pieces.

The following steps enable to improve quality and speed through iterations:

Value-stream mapping to understand the flow and its performance
Limiting factors identification with root-cause analysis, issues-tree
Task-prioritization mechanisms to implement identified improvements
Measurement & retrospectives to learn and adapt from experience.

Each of these activities must be performed as a continuous process after each increment to define the most important priorities depending on the identified limiting factors. In some cases, shift-left would be the main part to address to improve quality upstream, while automation would be required in the middle to streamline activities that remain manual.

The discussion between shift-left or shift-right moves from a debate of opinions to factual improvements of the software value chain based on facts. The customers, business, and users are the center of attention where efforts must be translated into valuable outcomes concretely improving quality and speed across the software lifecycle.

The goal is to reach and maintain a state of continuous value delivery in a rapidly evolving ecosystem to sustain the business.

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Continuously improve value delivery, shifting where necessary

Quality at Speed software is a journey rather than a destination where only the actors are able to master the software flow can reinvent themselves to remain valuable, successfully equilibrating shift-left and shift-right practices depending on their maturity.

It’s about creating a mature system where the practices shared by value-stream mapping, limiting factors removals, and continuous improvements focused on quality at speed becomes an organizational habit enabling to support the business growth.

Shift-left or shift-right is therefore not the question to be answered. Instead, we must continuously ask which practices would have the most impact to deliver quality and speed across the end-to-end software lifecycle.

This question requires more than software engineering — it’s Quality Engineering.

How Test Automation Can Accelerate Business Transformation

Antoine Craske — Thu, 10 Nov 2022 09:07:08 +0000

Digital business transformation is a race against time. A company’s survival directly depends on its transformation speed with continuous pressure to reinvent itself in short cycles. In such a competitive ecosystem, only first movers can gain a competitive advantage.

And transforming a business with digital requires continuously improving the company’s value proposition through software. The challenge is to accelerate the delivery of valuable software while guaranteeing the stability of business operations.

Testing is one of the activities companies rely on to improve their confidence when changing software components. Organizations usually start with a manual testing approach that can help at the start, but that quickly reaches limitations in terms of scalability.

Test automation is pivotal to provide reliable and fast feedback loops to software teams, enabling them to accelerate. And that increased speed enables business transformation of companies.

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Test automation supports core business functions continuity

Transforming a business is like renovating a house you are living in — part of the rooms is changed while still using the other ones as usual. It is the same for digital transformation, incremental changes are required as a big-bang approach is not possible.

And like with a house, it is equally a question of foundations. Trying to change parts of a complex software system without knowing first its actual behavior is a risky approach. Even small changes can result in cascading issues directly impacting the business.

Teams need a way to rapidly verify if the existing functionalities are still working. Automated tests of non-regression are one area of test automation that can provide such feedback loops in a timely manner, in a repeatable and scalable way.

Organizations successfully implementing non-regression tests gain the confidence to maintain the existing business behavior and operations. As a result, they can accelerate with test automation to speed up recurring validation cycles that were previously ineffective.

And they can accelerate even more testing earlier.

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Early test automation accelerates incremental changes

Delivering software at speed requires minimizing defects in the first place and reducing the costs of fixing them. Shift-left is a paradigm pushing for acting upstream in the lifecycle to improve quality, including smaller changes with test automation.

Teams able to split business ideas into smaller software increments can deliver software with more velocity. The remaining challenge is to quickly validate changes to avoid the accumulation of pending changes blocking the flow of business value delivery.

Test automation can be leveraged to accelerate the cycles of validation with tests performed upstream. And by being faster to validate, the entire team can benefit from a continuous flow of changes with minimal rework and risks.

Organizations leveraging test automation early in their software lifecycle recurrently gain time that lets the team concentrate on what matters: incrementally improving the business through experimentation with confidence.

Test automation enables continuous value measurement

Delivering a successful user experience through software requires to perform successful experiments that improve the companys’ value proposition. But organizations are limited by the speed at which they can assess the value delivered to scale experimentation.

Testing value hypotheses requires measuring the effective delivery of value from a customer point of view, when directly using the product. A traditional approach with manual testing can work but leads to delayed improvements compared to faster competitors.

Test automation can be leveraged to systematically measure the value delivered based on customer journeys, freeing the team from performing costly and slow tests. As a result, the organization can accelerate its cycle-time of value-hypothesis testing.

And companies can capitalize on automated tests focused on value to monitor the value delivered in production, for example by performing customer journey monitoring based on the key value metrics such as customer creation or order entry.

Continuous test automation supports business monitoring

Changing a business that depends on software requires mastering the end-to-end lifecycle to deliver changes without impacting the business. The continuous feedback provided by test automation helps businesses achieve frictionless business changes.

Changing a system involves the risks of failing to deliver what is expected or disrupt other parts of the system. An effective way to minimize risks is to perform regular health checks to adapt the software more rapidly based on testing results on the entire software chain.

Organizations able to implement feedback along the software lifecycle with continuous test automation benefits from systematic and automated feedback on their system. The improved visibility let teams perform more business changes with limited disruption.

Change in the results of many changes making the difference over time. The cumulative gains of delivering successful business changes with quality and speed result in an accelerated business transformation that always needs to go faster.

Intelligent test automation speeds up improvement cycles

The speed of business transformation speed is limited by the processing capability of humans and systems across the lifecycle. When organizations already leveraged improvements with automation, their next step is accessing intelligent automation.

Intelligent automation is about automating complex decision matrices normally taken by human brains. The concept is applicable to many areas such as software, and also to the domain of test automation.

Teams accelerating software delivery have to rapidly implement, maintain and execute tests to answer “Can we deliver that change now?”. The issue is that with more components and tests to perform, the feedback loops are usually delayed, limited by the system capabilities.

The use of intelligent test automation can help reduce limiting factors across the software lifecycle such as reducing the number of tests to execute depending on the change, parallelize tests that do not have dependencies, or give a prediction about false positive results.

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Test automation is an accelerator of business transformation

Transforming a business through software is not the result of one-shot efforts or random luck; it’s the results of a systematic and rapid experimentation where software becomes an integral part of the customer experience and business operations.

Test automation enables the delivery of valuable software with more confidence, faster feedback, and reduced risks. The capability to accelerate both value-hypothesis testing and software delivery is what enables to accelerate the business transformation.

Testing after software changes or trying to follow software teams is not sufficient. Testing must be performed in just-in-time, alongside business changes and operations to maximize its value to the entire organization.

More than an act, test automation makes the difference by becoming a habit that is part of the business and the software value-chain. It’s about embedding quality and testing at each level of the software lifecycle with Quality Engineering to accelerate business transformation.

How enterprises can shift left?

Antoine Craske — Thu, 10 Nov 2022 08:47:09 +0000

Organizations are facing an increasing competition from digital actors with a capability of continuous adaptation through software. Their competitive advantage is to master the entire steps of the software lifecycle to continuously deliver Quality at Speed software.

But traditional approaches to quality slow down software delivery for most organizations; and focusing solely on speed in the short-term results in an ever-increasing technical debt thereby slowing down the rhythm of innovation, putting the organization’s viability in question.

That pressure makes companies look for solutions to improve the way they deliver software. An instinctive approach is to try improving the coding stage. But once companies understand that quality issues have underlying causes upstream in the software lifecycle, they look to act earlier.

Companies can leverage the paradigm of *Shift-left *to effectively balance quality and speed. The concept emerged in the software industry in Agile, DevOps, and Testing — but it’s the entire enterprise that needs to shift-left to succeed in the digital transformation.

First things first, understand Shift-left

The philosophy of shift-left is to improve the outputs of the software production process by performing upstream activities that help to detect issues earlier, reducing the cost of fixing them by a factor of 10 to 100. In reality, there is even more value in shift-left than cost reductions.

“Shift-left is about accelerating the delivery of valuable software.”
— Antoine Craske

The early involvement of actors contributing along the software lifecycle enables them to include by design requirements that avoid costly reworks once software has already been produced. That’s where shift-left is more than testing upstream: upstream quality contributes to more speed.

Companies capture additional value with shift-left by improving the collaboration of the teams with shared methodologies, constraints, and reviews. The upstream involvement fosters an environment where software is improved even when ideas are still on paper, supporting faster cycles.

Shifting-left is, therefore, a must-have for companies searching to accelerate their digital transformation. It enables faster iterations of software delivery that are improved earlier, tested faster, and delivered with a continuous velocity, contributing to organizational agility.

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Start with Why, defining the outcomes

The initiation of a shift-left dynamic usually leaves the team full of energy to implement practices they have heard about, such as Behavior Driven Development (BDD), starting to measure how many scenarios they cover. It must start the other way by defining the expected outcomes.

Enterprises aiming to embrace a shift-left dynamic must be able to articulate its contribution to the company strategy and business objectives. Even if shift-left activities can actually be measured locally, their bottom-line impact is to contribute to the business outcomes.

But there are difficulties for organizations to measure the outcomes of a shift-left initiative. Delayed feedback loops create a time gap between the implementation of practices and the measurement of results; thereby complicating the correlation between shift-left outputs with business outcomes.

That’s why organizations must measure shift-left performance in three main categories:

Key business outcomes (i.e. KPIs) like customer satisfaction or new revenue streams
Software lifecycle performance on quality and speed (e.g. Accelerate)
Shift-left practices concrete actions through metrics.

These outcomes will drive the formulation of the enterprise shift-left vision.

Share the vision to align the organization

Organizational alignment is critical for creating a shared understanding about the need for change, what are the expectations, and what is likely to change for the teams. The burning questions to answer for everyone are “What’s in it for me” and “What’s next?”.

That stage is about creating content about the shared vision that can be presented in town-hall, team meeting and other instances. The key motivations defined in the previous must be present and easily remembered, easing the adoption and recall among teams.

One must-have message is about creating a quality engineering culture, where all actors collaborate along the lifecycle with the quality and speed imperatives in mind. Like in Toyota factories, anyone not satisfied with the outputs at one stage must be able to block the flow to improve it directly.

The start of the initiative is then about managing a series of incremental organizational transitions, starting small while keeping the entire enterprise up-to-date. The first transition requires leveraging your guiding coalition and identifying your “early wins shift-left team”.

Prioritize Shift-left activities and measurement

The first team to start with shift-left practices must be composed with a high probability of succeeding, picking your best assets with the necessary skills, open to new ideas and enable to drive the implementation of shift-left practices in short cycles.

The objectives and context must be first assessed to define the most valuable priorities that will contribute to key outcomes of quality and speed. The practices to implement must either contribute to improve the products upstream or reduce the risks of introducing defects along the software lifecycle.

The team has to analyze its software lifecycle performance according to the outcomes defined in the first step. For example, if the objective is to increase customer activation by 5%, deliver daily instead of every week, the team needs to define which shift-left practices make more sense.

Identifying the shift-left activities that could provide more value can be done with questioning:

What actions that, if improved or added, would contribute to the outcomes?
Where are the limiting factors in our current software lifecycle?
At which stage non-functional requirements are best tackled?
Which activities are generating the most rework? Why?
Which steps are most likely to introduce defects?

The team can then identify which practices and measurements are more useful. If teams have too many reworks from the testing stage, they can invest in BDD in their user stories to perform them earlier with test automation. If there are security concerns, architecture reviews can be set up.

It is essential to systematically drill-down into the root causes of the identified symptoms to prioritize the correct shift-left actions. Teams can introduce defects due to a missing stable test environment, and not because of the quality of the specifications. That’s why measurement is needed.

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Expand linking shift-left outputs to the outcomes

Shift-left for Enterprises should deliver successful incremental transitions to unlock its full potential across the organizations. Measurement is useful to follow the implementation progress but also to define when the switch to a new transition is required.

Once the first team has delivered valuable changes with shift left practices, it is then time to expand them among teams. It is critical at that stage to ensure the scalability of your foundations in terms of methodology, architecture, organization, management and skills.

Start by ensuring a properly-defined set of shift-left guidelines and practices that can be replicated by other teams using ambassadors from the early wins team. Similarly, ease the adoption with reusable templates, technology assets, and training materials.

The continuous measurement across your three categories will help you link shift-left outputs to the outcomes, ensuring that the expansion of the practices is effectively contributing to your enterprise objectives. That’s indeed why you started the initiative in the first place.

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Shift-left for Enterprises, a necessary transformation

We saw that shift-left starts by clarifying the Why in the expected business contribution. That focus is what enables the implementation of the most valuable shift-left practices along their software lifecycle, depending on their context and priorities.

Enterprises able to shift-left can accelerate the delivery of quality (at speed) software, enabling them to sustain the necessary rhythm of the digital transformation. That velocity sustains the capability of the organization to remain valuable in our challenging ecosystem.

Shifting-left is a business imperative supported by, and not driven by technology. Only organizations that formulate a compelling shift-left vision can drive the necessary transitions to deliver sustainable changes for quality at speed software.

And, it all starts with the right leadership and vision