It’s hard to build a classification scheme that stands the test of time. Those that persist do so because they meet the collective needs of the organisation.
Businesses that develop fit-for-purpose standardised metadata can find the right information, in the right place, at the right time.
Most organisations fail to execute their digital transformation strategy because they don’t know where to start or how to clean up the current mess.
We autoclassified and appraised our legacy client records with help from our partner, Pingar. These were the results.
The starting point for data governance is to build a framework representing the business environment – we call this Enterprise DNA.
Managing metadata and developing taxonomies is easy! And so it is – when you are working within a confined context.
When major systems fail, poor governance is often cited as the reason. Dig in and you’ll find taxonomy and data/metadata quality is a factor.
With so many standards to choose from, it’s essential to understand the types of metadata standards and their purpose.
Without defined rules, descriptive metadata becomes subjective and results in ambiguous language.
Our challenge is harnessing language as a tool for describing information resources with consistency and precision.
It’s not surprising that users opt out of records management systems that don’t deliver functionality for adding, connecting and leveraging metadata.