At most large enterprises, the IT environment has evolved over decades into an “accidental architecture” with everything from mainframes, PCs, and LANs to the Internet, cloud, and mobile devices, all connected by a poorly tied together patchwork that limits speed, flexibility, and innovation. IAM offers a new model for managing users and devices within the organization, where routine provisioning processes are automated and a System of Record (SOR) feeds the IT infrastructure and drives the user experience. In this blog series, we will explore the topic of data quality, its importance in IAM, and offer some recommendations to address this important issue.
It’s been said that IT systems are a lot like the Old Testament, lots of rules and no mercy! IAM solutions are no different, because they process data according to defined rules to grant and revoke user access to the network and key applications. If we have bad data, then users cannot get the access they need to be productive. Let’s walk through a brief example: We hire a new user and enter their name and other personal information into our HR system, but their manager is incorrect. The HR system sends the employee data over to the IAM solution to create the new employee user on our network. Because the manager field is wrong, all the user’s requests are routed to the wrong person – access requests, expense reports, time sheets will all be sent to the wrong manager for approval – delaying access, creating additional work for the IT operations team, and reducing productivity. The key takeaway is that with good data, your IAM system will make your IT operations efficient and your users productive. With bad data quality, you simply get bad results faster. Bad data quality offers no mercy! Check out Part II – The 5 Dimensions of Data Quality to learn more about how to evaluate your data.
