Discuss three ways in which errors can arise in developing and executing linear optimization models in business situations, and indicate some of the business consequences of such errors. Explain how analytics professionals can help to prevent such errors.

The mistake is something you did, that could not be incorrect. It may consider errors when creating and implementing simulation models in business situations because of some procedure problems. It is not because of bemusement and a few of the other error types were also acceptable even though the correction is affordable.

Type 1 error: This type of error arises due to limited accuracy issues, in this the gadgets or devices used for the simulation study, quantitative measurements. These errors Often simplified in expectations. It is a concept for analysis, in which experts firstly understand this kind of mistake.
Type 2 error: These errors may occur due to inaccuracy. If another analytic method behaves differently for two analysts. It tends to cause errors, that are unrecognized by no pre-defined methods for fixing those errors.
Type 3 error: These issues can be reduced by the improper selection of software, and in the implementation period, it can consider this sort of error due to the failure of system integration tools.