The clients you have on day one are often very different from the ones you’ll have a few years in. Even if they’re the same organisations, their business, expectations, and tolerance for complexity likely have changed. And the volume of historical data can also be a factor.
A pattern I’ve seen repeatedly in practice: 1. A new system that addresses an urgent need feels refreshing, especially if it’s simple. 2. Over time (1, 3, 10 years? depending on industry), edge cases and gaps start appearing. Workarounds begin to pile up for scenarios the original system wasn’t built to handle. 3. Existing customers start expecting these workarounds to be replaced with proper solutions. Meanwhile, new customers (no longer the early adopter type) have less patience for rough edges.
The result is increasing complexity. If that complexity is handled well, the business scales and can support growing product demands.
If not… I'm sure many around here have experiences where that leads (to borrow Tolstoy: “All happy families are alike; each unhappy family is unhappy in its own way.”).
At the same time a market niche may open for a competitor that uses a simpler approach; goto step 1.
The flip side, and this is key: capturing all nuances on day 1 will cause complexity issues that most businesses at this stage are not equipped to handle yet. And this is why I believe it is mostly a business problem.