As teams scale, the role of "Process" becomes a central topic, eliciting both strong support and vehement opposition. Processes can sometimes feel burdensome and ineffective, yet they're indispensable for seamless growth and concerted progress. The challenge lies in distinguishing between good and bad processes and finding the equilibrium between the need for consistency and the freedom to innovate. To unravel this, let's first examine the pitfalls that make processes cumbersome and prone to failure.
[Design - Can we get a timeline chart with the 9 headings - Identifiable Gaps -> Codification -> etc]
In the rapidly expanding business landscape, numerous new business cases arise daily, causing teams to traverse these 9 stages repeatedly. Put simply, what works for a small group might not suit a larger one.
Mismatched Processes vs. Amplifying Processes
All processes aren't created equal; there's no such thing as an inherently good or bad process. Processes either mismatch the specific business context or possess the potential to exponentially enhance efficiency, output, or cost-effectiveness by 10 times.
The Perception Quadrant of New Processes
Introducing a new process typically triggers skepticism or optimism among teams. This fresh process could either end up being a misfit or a 10X enhancer.
Initially, skepticism prevails when a new process is introduced, especially if imposed from a centralized decision-making point. Engineering managers might initially resist the new process's applicability to their unique business context, either accurately or erroneously. The possibility exists that the new process could indeed amplify their outcomes tenfold, but uncertainty clouds their judgment.
The fate of this advocacy depends on the organization's openness to change. If past processes were met with skepticism and proved misfits, subsequent decisions will be met with even more doubt. This breeds a damaging culture and suboptimal outcomes, a phenomenon all too common.
[Design - Can we get a 4x4 quartant. X Axis should be ( Skeptic, Optimistic) and Y Axis (Misfit, 10x) . Top should be 10x . Right should be Optimistic]
The solution lies in Continuous Adaptability Driven by Actionable Data.
Actionable Data: Every introduced process requires instrumented data to gauge whether it's a 10X boost or a misfit. Examples include:
Technical Debt Sprint Introduction: Improved defect rates, reduced support tickets, and heightened customer NPS scores due to enhanced communication.
Products like Harness Software Engineering Insights can provide actionable insights for testing process effectiveness.
Statements like "It's always been done like this" or "Other teams are doing it this way" reflect adaptability struggles. While standardization can be effective or not, continuous adaptability, data utilization, and questioning the "why" become potent tools to manage process edge cases. Leaders must recognize when existing processes falter for new contexts and iterate promptly.
The gravest error is halting process iteration, leading to institutionalization and forgetting the process's initial purpose.
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