ROI pack
Illustrative public example inspired by a multi-site logistics case: a demand spike puts service under pressure and pushes three sites toward expensive emergency decisions.
Starting point
Three logistics sites have to absorb a five-day workload spike. Without a common frame, the team risks mixing poorly targeted overtime, late temp labor, and reallocation choices that only move the problem around.
Praedixa turns that context into an explicit trade-off: where to reinforce, where to reallocate, where to delay, and which site deserves service protection first.
Compared options
The example compares four options: local overtime, targeted temp labor, cross-site reallocation, and temporary service-level adjustment.
Each option is reviewed with the same assumptions: action cost, cost of inaction, service level protected, and spillover risk on the rest of the network.
Chosen decision and reviewed impact
The chosen recommendation combines cross-site reallocation and targeted temp labor instead of a blanket overtime reaction.
The before / recommended / actual review then helps separate what comes from context, from the decision taken, and from the observed impact. Econometric models are used here to make attribution more defensible, not to decorate the outcome.
What Praedixa adds
ERP, BI, planning tools, and spreadsheets already expose useful data, but the economic trade-off often stays split across teams and screens.
Praedixa adds the missing frame between those tools: compared options, documented decision, explicit assumptions, and impact review over time.