Our work focuses on the quality information aspect of the inventory management domain of the supply chain in the organization. Within the scope of quality information we have concentrated upon the discrepancies known as inventory errors, which are the result of events that can be classified as one of the following three types: Shrinkage, Misplacement and Wrong Scanning [1]. These events lead to differences between inventory reflected in the IT system records and available inventory for sale. These discrepancies and/or their associated negative effects can be minimized should additional information be available. Our work explores four different models that operationally take the discrepancies into consideration in four different scenarios: (1) No Information Scenario, (2) Static Informed Scenario, (3) Informed Scenario, and (4) Full Information Scenario. The objective of our work is to explore and quantify the value of the additional information in Scenarios 2 - 4 compared to the No Information Scenario. We implemented an analytical model for each scenario, where the objective in all four scenarios is to minimize the average expected cost per period. Our findings indicate that additional information greatly influences optimal policies and, if exploited wisely, can save a great deal of money