Annual Reviews has been publishing scholarly articles since 1932, and with that comes decades worth of data. See how using Ringgold data services helped Annual Reviews automate and connect data securely and accurately.
Annual Reviews has been publishing scholarly articles since 1932, and with that comes decades worth of data. With multiple departments using and inputting data about organizational customers, data coming from outside sources, and new accounts being created without a consistent naming or identification system in place, many duplicates were found in their business systems. For example, Customer Service would set up an institution using the full name in their primary system, while Sales would set up the same institution using an abbreviation in their primary system, making it difficult to merge the data to enable the systems to talk to each other properly.
In addition, because institutions were ordering through different individual departments, it was difficult for Annual Reviews to accurately identify parent-child relationships of the organizational customers and find the correct top level of an organization. To work around this, members of Annual Reviews’ Finance and Sales teams developed manual processes to maintain account names and relationships. This was especially challenging for customers with multiple accounts. Orders coming through multiple departments from an institution also made it more difficult to set up and manage online access to journals. In addition, Annual Reviews wanted to tie together author and subscriber data and given the lack of clarity in the relationship of departments to the top-level institution, manual workarounds were necessary to do so.
Everything is normalized. Everything is standardized. So, it allows us to institute those standardizations and normalizations into our systems, especially our customer master.
