Sometimes, although too rarely, people will bring up the idea of institutional memory in regard to planned merger and acquisition activity. Usually you’ll hear it once or twice up front from the management consultants, something like, “ … and we have to make sure to maintain institutional memory…”. And that will be it.
But institutional memory, the information held in employees' personal recollections and experiences that provides an understanding of the history and culture of an organization, especially the stories that explain the reasons behind certain decisions or procedures is critical. It’s critical in the sciences. It’s important in IT and data management (warning, you could lose hours in this Slashdot thread). And of course, the Business School types preach about it. Institutional memory can help you understand why a certain process has to be done a certain way. It can tell you the strategy behind a new application or IT project. And it can tell you, in the words of the IT team, “What the heck is in all these files?”.
Do these files need to be saved or can we just delete them?
These files seem to have names and dates. Is it PII? Are these real people? Is it test data? Do I have privacy risk here that I need to consider?
Will any of this data be useful to the analytics people? Is that why it was saved?
Without access to the people, to the institutional memory around this data, it’s very difficult to answer these questions. So, before you can do any of those big projects on your list – cloud migration, digital transformation, data classification schema – first, you need to know your data.
We recently produced a case study of a manufacturing company that had over 20 years of data coming from literally dozens of mergers and acquisitions. Each time they inherited a bunch of new data. And each time they put off organizing it, because they just never had the time.
And since the people who lost their jobs in the merger may not take kindly to a phone call from their ex-employer, maybe you should just call Aparavi. Aparavi can’t tell you that the Atlas project wasn’t actually named for the Greek god, but for the Project Manager’s GiantSchnauzer. But Aparavi can give you a quick demo to show you how to quickly spot trash data, or PII, or anything with the keyword “Atlas” (or “schnauzer” I suppose). And then we can get you started with a free pilot where you can start getting to know your data.
As the customer stated in our case study, “Everything is just easier when you know your data”.