Choosing technology has never been harder. At all levels we’re inundated with choice, opportunity, and the noise of navigating politics and preferences in our teams. In both the boardroom and the scrum team, opinions are pitted against business needs as we struggle to make the best choices for our projects.
Finding balance across the many dimensions that influence decisions as seemingly as simple as “which programming language to use”, has surprising depth, and it is worth the breath it takes to weigh up these choices in the most pragmatic way possible.
Projects are now products and platforms, with much longer lifespans, which means that the stakes are also much higher. With each tech decision, we commit to a path which will impact not just the project in front of us, but the organisation too, and the people within it for years to come.
Make better long term technology investments, by being informed about the influences on technology selection. Surprisingly, functional requirements is only one of seven.
The context in every technology choice on projects of every type consists of 7 dimensions, spanning the full spectrum of influences on the organisation.
There is no obvious place to start, although in most businesses the “people” dimensions carry far more influence because that is where accountability and mandates stem from.
A lot of subjectivity is involved. No choice will ever have the same influences in each dimension, so instead the value is in practicing-decision making by reflecting on each of these areas, every time you choose technologies.
The point is not that there is a formulaic way to approach these decisions that will always be right. The point is to weigh everything up, and avoid ignorance of any of the dimensions. A decision made with full context will have substantially more value in the long term
Start anywhere, and think through these influences, prioritise and evaluate within the relative context of each decisions. Choosing a long-term product set or platform for the future of technology in a business obviously carries far larger consequences than picking a dashboarding library for your next analytics project. The dimensions of this choice, however, remain the same.
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