There are two common approaches to harnessing optimization into a decision making process in a modern organization: Black Box and Human in the Loop.

By  Black Box, we mean that the optimization model will be directly responsible for making a choice that was formerly performed by either a person or a prior model.

The complexities of this approach include:

• Getting definitive rule and cost data out of subject matter experts’ heads and into the optimization model
• Employing automated data cleaning, automated parameter tuning, and other advanced techniques that eliminate the need for human quality assurance on each transaction
• Gaining the confidence of the sponsoring organization that there are sufficient safeguards installed; that the machine-driven approach has a lower error rate than the one it is replacing

Examples of Black Box Optimization are:

• High speed buying and selling for the high frequency hedge fund – providing the jump on other market participants
• Offering web customers capacity and rates for the freight railroad without an internal salesperson – providing fast booking confirmations for customers while reducing commission costs
• Automatically scheduling follow up lab tests for the pharmaceutical company on the same blood sample; providing faster diagnostics at low costs without requiring additional visits to the lab by the patient.
• For the 2020 U.S. Census, in the evening preceding each day, assignments are made in over 700 different regions, which are geographically diverse, ranging from cities to rural areas.