In chemical process development, the term “success” often gets reduced to two metrics: yield and selectivity. And while those are important, they offer only a partial view of process performance.
But what about:
🔁 Reproducibility across batches and operators?
⚡ Energy consumption per mole of product?
👨🔬 Operator dependency and manual intervention time?
⏳ Throughput efficiency and downtime metrics?
What we fail to measure, we inevitably fail to optimize. And what we optimize defines not only the outcome, but also the cost, risk, and sustainability of that outcome.
In the era of data-driven chemistry, meaningful KPIs should reflect more than just what happens inside the flask. They must integrate upstream sourcing, downstream purification, equipment utilization, and even human factors.
🔍 We need multidimensional metrics that align innovation with scalability, robustness, and regulatory readiness.
Because real progress in process chemistry isn’t just about better numbers on a report.
It’s about building processes that hold up in the real world: across time, teams, and scales.
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