With the growing number of data breaches in business, it is still a surprise that Coca-Cola have felt the backlash…Read more
With the growing number of data breaches in business, it is still a surprise that Coca-Cola have felt the backlash from an undetected data breach.
Back in September 2017, the data of 8,000 Coca-Cola employees was stolen without them even knowing. Although companies of such size have the capability to cover themselves for any foreseeable breaches, it is clear that Coca-Cola did not do so.
In fact, it was only after the FBI recovered the data that Coke were even aware that it was missing. With personal information being highly sensitive, it is yet another example of why any and all companies should protect their data. Although, it is different to the majority of breaches such as Yahoo or Facebook, as instead of the breach being the result of an external hacker, the source of this breach was an employee of a Coca-Cola brand who stole an external hard drive.
With clarity being a massive factor in the trust of personal information, it is not good that Coke disclosed the breach for over 8 months, and it is still unknown exactly what information was breached; although representatives said that this is down to an FBI investigation.
Coke have come under huge backlash from data management professionals for their complete what is being seen as a lack of care and respect for their data and employees; slating the beverage giant for only being aware of the breach when law enforcement came knocking, which suggests that they really did have no data management or security standards in place.
With Coca-Cola being a brand with a huge social responsibility, it is a surprise to see that they didn’t optimise their employees’ data; making consumers also question whether their data is at risk.
With the constantly growing standards of data protection for both internal and external breaches, there are more than enough options to optimise their data management and security following the breach, with such tools as user-specific role allocation and automated error-messages allowing them to have premium clarity over their data.