Slogan for Enhancing Overall Productivity in Software Development
(Regardless of methodology: Agile, Plan-driven, DevOps, etc.)
- See the Whole, Not Just the Parts
- Shift from Reactive to Predictive
- Leverage Tacit Knowledge and Collaborate with Humans and AI
- Transition from Long Overtime to True Intellectual Work
See the Whole, Not Just the Parts
Rather than optimizing individual components, we aim to optimize the entire system.
Professions such as programmers and system engineers tend to become highly specialized, often resulting in localized optimization.
In fact, for a specialist, maximizing their own performance might feel like the ideal state—even if it leads to partial optimization.
However, in software development, projects are usually team-based. It is more important to enhance overall team performance rather than focusing solely on individual contributions.
We are looking for software engineers who can utilize their individual expertise while lifting the performance of the entire project team.
Shift from Reactive to Predictive
In software development, both top-down, plan-driven approaches (like Waterfall using Work Breakdown Structures) and bottom-up, Agile approaches coexist.
While Agile development surged in popularity for a time, recently there has been a renewed appreciation for structured, plan-driven development based on detailed design documentation.
That said, neither approach is inherently superior. The most suitable method depends on the nature of the team, the company culture, and the required deliverables.
What can be said, however, is that software development is filled with unknowns. Therefore, instead of reacting to problems as they arise, anticipating and preparing for them is crucial.
In plan-driven development, this means detailed risk management. In Agile, this involves anticipating near-term issues using sprints, tickets, and iteration cycles.
While we cannot foresee the future, we can draw from a wealth of past experiences and knowledge to predict and proactively respond to challenges before they become critical.
Leverage Tacit Knowledge and Collaborate with Humans and AI
When knowledge management systems gained popularity, the focus was on documenting knowledge explicitly.
But in the rush to document everything, the original purpose—spreading and utilizing knowledge—was often lost.
It’s important to record knowledge in systems and documents, but that alone is not sufficient.
True value lies in human-to-human communication, where tacit knowledge—the kind of knowledge that is difficult to formalize—can be shared and leveraged effectively.
Using the SECI model (Socialization, Externalization, Combination, Internalization), we promote continuous knowledge sharing and learning.
More recently, AI technologies have also enabled new forms of knowledge collaboration. Working alongside AI is becoming a necessary part of modern development.
Transition from Long Overtime to Intellectual Work
Software development is fundamentally an intellectual activity. Working excessive overtime does not lead to higher productivity.
In fact, pushing for long hours doesn’t guarantee that the software will be completed.
In the real world, we often face constraints like limited budgets and tight schedules. We need to deliver working software within those boundaries.
Boosting productivity is important, but even more critical is ensuring we actually complete the product.
Let’s use our motivation, effort, and time efficiently toward that goal. The history of software engineering already offers proven methods for this:
- Ticket-Driven Development
- Test-Driven Development
- PSP (Personal Software Process)
- Peer Reviews
- 40-Hour Work Weeks
- Project Buffers
Let’s apply these practices to reach our goals through efficient, intelligent effort—not brute force.