Optimization: A Best Practice in Decision Analytics

Which projects do you invest in when you can’t invest in them all?

Organizations are challenged with choosing the right work at the right time within the constraints of limited resources. Choosing the right work is critical to maximizing return and minimizing risk, but traditional methods of prioritization, like cut-line ranking, cannot adequately capture the diverse value of each investment or the trade-offs of certain projects over others. Ranking investments by value and going down the list until money runs out may be easy to do, but it does not yield the best return.

Optimization delivers far better results by evaluating factors including start time, resource utilization, cost, financial benefit, alternatives, and more, all while respecting real-world constraints. Planners can explore and compare potential scenarios, like unexpected budget changes, and re-optimize the plan in light of real-world occurrences to be confident that the plan will always deliver the highest value.

Learn more about what makes optimization a best practice in decision analytics, how Copperleaf’s optimizer works, and how it can deliver superior results for your organization by downloading the white paper.