Ideally they should use a formal RDBMS, but that cranks up the cost of the study. A data QA team also helps. The question is whether these measures are "worth i

Ideally they should use a formal RDBMS, but that cranks up the cost of the study. A data QA team also helps. The question is whether these measures are "worth it". Are the Excel errors significant enough? Are 10 studies with a conclusion flaw rate of 30% better or worse than 5 studies for the same cost with say a 10% conclusion flaw rate? A cost/benefit analysis on this can get tricky. In almost any endeavor there is a quantity-versus-quality trade-off per given unit of resources. In the IT field, we often say: A: cost, B: speed of delivery, C: quality. You can only pick 2 of the 3, which are they? It's kind of the same principle, but with delivery time more explicit.