When an organization has bad data, the outcome will be flawed $($Almeida$,2023).$ The inaccurate data can lead to incorrect assumptions, biased conclusions, and unreliable patterns $($Almeida$,2023).$ This would cause an organization to go down a path that is flawed and missed opportunities $($Almedia$,2023).$ Misguided strategic decisions could also come from discrepancies but also the lost of creditability due to it$.$ Something that happened that affected multiple branches but also lost creditability in locations was that certain employees and managers were making their sales numbers look better by discounting the cost of the rental but charging for the extra protection for the car. At Enterprise, the way someone is promoted is through their individual sales, so someone that is changing rates of the cars and selling more of the extra protection, management is most likely going to promote them. This lead to Enterprise putting these employees in manager roles, who then taught their employees to make their number better in an unethical way. There were multiple managers that got to where they were from this method, which ended up having very bad PR for the branches, causing their fleet to diminish, customer service rating to plummet and branches close. For the ones that stayed open, they had to rebuild their customer base but also their fleet so they could make more money as managers since everything is per car for Enterprise's financial statements.$$