NEWSFLASH: Solution Benefits Don’t Happen Overnight. Pierre Frigon is a seasoned expert with a number of companies in lab automation solutions empowered by methodologies including Lab as a Service (LaaS) and DevOps. In this M2M blog installment, Pierre shares his insights on an aspect of solution adoption all leaders must take into account well before a solution adoption: realistic time expectations of empowered productivity and ROI.
Everyone involved with product development in the age of digital disruption is familiar with the appeal of a LaaS adoption: the promise of accelerated time to market, empowered productivity, cost savings and enhanced resource management. Yet when an organization undergoes the profound complex changes required to deliver these benefits, it will invariably lose productivity before it can observe significant productivity—a process often referred to as the J-Curve effect. The frank reality is that benefits of a complex solution such as a LaaS implementation will not be realized until the organization has run a gantlet of implementation requirements involving the integration and orchestration of new technology, people, and process—the Valley of Despair. Only after this solution phase is conducted holistically and effectively can solid long-term benefits be reliably achieved.
The need to understand the devil in the details. Unfortunately, many managers fail to heed the warning communicated in the J-Curve analogy. They expect productivity to remain unimpeded as they go through the change. Going through a transformational change of this nature is a painful process. Facing similar circumstances, while undergoing a big change in the past, I’ve often asked myself “What was I thinking?” There are several key factors leaders must take into account to help them persevere. The inevitable question from the leadership is: “How long will we be in the Valley of Despair?” The short answer is: as long as it takes for the change to become the “new normal.” That’s the high-level answer and looking under the hood of what it takes to reach the new normal is helpful for planning and setting expectations for the entire organization to ensure a successful transition.
Solution success depends on a clear vision supported by committed perseverance for the lifecycle of the solution. In addition, navigation through the trough of the J-Curve effect can only succeed with proper planning that examines your goals and what you’re really trying to get out of the initiative. Then, look at the size of the investment you must make to get there. Having a clear understanding of the short- and long-term solution objectives helps break down the allocation of costs, technology infrastructure impact, resource allocation, and scoping of the overall effort of change required to achieve the desired new level of productivity. It’s also critical to understand that no plan ever survives first contact with reality. Leaders must be aware there are many unknowns when going through a significant change. These unknowns surface as you move the project forward and require constant adjustments to the plan based on what is continuously being learned.
Understanding the areas impacted by change during the planning process helps leaders anticipate the complexity of transition required for holistic and productive change. These areas break down into three categories:
Technology requirements in the lab environment. One of the most common elements of these types of projects involves power-related technology. Considerations include how you power the environment, along with how you control that power and monitor it. Analyzing the switching infrastructure required is also essential, since to automate a lab infrastructure, you need a sizeable switching infrastructure to support the scale and complexity of testing involved. This represents a large part of the environment, depending on what devices require switching in the lab. If the devices that allow you to conduct robust test campaigns fail, they stop your operation. One of the most crucial elements of the solution is the orchestration software that sits on top of the infrastructure and drives everything. This software coordinates and builds the test harnesses and systems you’re using in the lab. If that layer doesn't work, then you don't have a functional environment. Taken collectively, all these orchestrated elements represent a complex collection of independently critical factors which must be taken into account when scoping the potential impact of the J-Curve effect.
A wider perspective on technology considerations. An organization may also be involved in a consolidation of labs that extends across regions, national or international boundaries. Resources, some working remotely, may also be consolidated, all of which must be taken into account to gauge the effort required for a clear understanding of the J-Curve’s trough factors. In some cases, corporate reorganizations or acquisitions complicate the technology stack with disparate infrastructures that must be addressed during the consolidation phase. Some organizations will stage their solution goals in phases, first with consolidation, followed by lab automation incorporating DevOps and Agile principles. All of these elements are factors in gauging the realistic estimate of when optimal productivity will be achieved within an organization.
People. Teams are often siloed, either by function or geographical location. In a solution initiative of this complex nature, they will need to be assembled and integrated effectively. As a result, some of the disparate development teams will be brought into a closer working relationship. This doesn’t happen overnight. The teams facing implementation of an automation solution traditionally undergo a phased approach of acceptance and adoption. The process begins with early adopters who prove and validate a solution’s value in an organization before the critical mass of test teams jump in, representing the tipping point of the adoption acceptance, where the rest of the organization’s alignment to change will pretty much be automatic. Training cycles for test and development teams are always associated with a transition of this nature. These phases all take time and must be accounted for in a solution sponsor’s planning and incorporated into their vision.
Process. Recognizing that disparate teams must converge in a unified process is no simple proposition. Uniform best practices must be embraced and adopted across every group to assure all parties are working from the same criteria and requirements. A group familiar with Agile, DevOps and lean manufacturing principles is in a very different position of solution adoption maturity than one that must adopt these principles and ramp up with them. The path of acceptance on these principles requires training, as well as a trial-and-error cycle, to assure optimal efficiencies are in place.
The S-Curve pictured here also helps break down the constituent elements of a solution adoption, from beginning to end, providing an additional contextual perspective on the solution adoption process.
Final thoughts on the J-Curve effect. While the J-Curve highlights the struggles in the comparative short term, the big picture of the solutions adoptions shows that substantial benefits of ROI and maximized productivity will come. The due diligence required with the complex elements in a project of this nature—with technology, people and process—fortify an organization’s potential to face the challenges of digital disruption with the robust capability and flexibility needed to respond to the new opportunities of the emerging the digital economy.
The Months to Minutes blog series highlights how continuous testing, driven by test and lab automation, optimizes the validation of an organization’s networks and business offerings amidst the growing challenges of digital disruption. The result: taking testing processes which too often take months to perform, and deliver improvements where it can all be achieved in minutes – with increased efficiencies and capabilities.
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