Scale is its own thing.
Bigger is not always better, but it's always different.
For that matter, so is smaller.
Look no farther than physics:
- Smaller: Sub-atomic quantum physics features particles with properties that are statistically uncertain, but those same properties would be deterministic but for the small (!) size.
- Bigger (or greater): For objects moving at near the speed of light the laws of physics don't change, but the math does (Einstein's theories). For example, you can’t just add velocities together the way Galileo or Newton did; you have to add them relativistically. You can’t just treat distances as fixed and absolute; you have to understand that they contract along the direction of motion(*).
At large scale, one observer (*) has said: "The quantitative becomes qualitative" meaning: when it gets big, the whole thing takes on a different character, apart from the numbers. Example: soloist vs a choir; a few people vs a crowd; the Grand Canyon vs a gorge, and so forth.
There's a lot going on in big projects; some stuff we all know about and have experience with:
- Communications degrade qualitatively and exponentially with the number of communicators. If two people are talking to each other, it's merely bi-lateral. But if 5 people talk among themselves, there's 5*4 ways that communications can flow: N*(N-1)
- Bureaucracy inevitably replaces personal trust and one-one relationships. You can't know and trust everyone is a large project with myriad subcontractors (1099s or entire companies), remote team locations, etc. So bureaucracy has rules, workflows, organization structure, and other institutional relationships to replace and substitute for personal relationships.
- Interfaces, whether institutional in the PMO or as part of systems of deliverables, become all so important. You may not have any visibility or understanding beyond the interface specification you must meet. (See: Systems, below)
But there are other influences that are prominent at scale:(***)
- Systems is the way you think about things. Anything really large has properties of systems, and so you have to think like a systems-savvy person: interactivity; interconnections; dependencies; sequencing; process and constraints; chaotic and impulsive behavior. If you don't know much about systems, start here.
- Phase or state changes: Increasing complexity arising from increasing parts is usually not linear; there may be abrupt changes of state or performance. Suddenly there are walls you can't get through; people you can't reach. Or, machines reach their absolute limit, beyond which their performance is unpredictable or unreliable
- Reduction vs construction: What you can disassemble you may not be able to reassemble or construct from the pieces. An unintended explosion may be an "unmanaged disassembly" in systems' speak. You can't put Humpty Dumpty back together.
- Symmetry, or not: If it's symmetrical, then it looks the same from all points of view. As things scale up, symmetry is often, if not usually, lost. There are just too many different points of view.
Scale effects on cost and schedule
Scale has two effects on cost:
- Scale increases friction with so many moving parts to the project. That is a cost increase, albeit with the benefit of having access to myriad capabilities and functionalities
- Scale is improves efficiency, making cottage industry efforts into industrial strength workflows, thereby reducing cost.
Scale requires "loose coupling" in schedules.
That is, white space or buffers are needed to accommodate a dizzying number of dependencies and interactions. And loose coupling protects the critical path, as we know from Critical Chain scheduling. All of this has a combined effect of stretching the schedule. But that's the "cost of doing business" at large scale.
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(*) Karl Marx
(**) Attribution: Ethen Siegel
(***) If you are into science, read this oft-cited paper: "More is different"
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