Improving organisational data quality is like house renovation

Photo by Webdexter Apeldoorn from Pexels

Imagine the scene, you are a newly appointed/ promoted Data Governance Manager or Data Manager with a remit of ‘sorting out the data mess‘. Colleagues are impatient for results and some are starting to blame you for the poor quality data. This does not feel right to you, but you are unsure how to keep motivated through these daunting challenges and the opinions of colleagues.

A number of our clients have been in similar positions – we have helped them in part by explaining that their role and challenges are similar to those of buying an old house to renovate.

Read on to understand why.

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Understanding data quality across organisations

Collection of shiny metal nuts and bolts

An organisation that works in isolation and does not share data with other organisations is probably rare. Most organisations will collaborate with other organisations to some degree and will be providing data as part of this collaboration. So, what factors need are relevant when considering data quality across organisations?

When building a machine or structure, you will usually be assembling components supplied by many manufacturers. For this to work, the interfaces between components and items should meet agreed requirements. For example, if one organisation decided to make bolts with a different type of thread, it would be difficult (or perhaps impossible) to join different components together.

In a recent post I considered what is needed to understand data quality from an organisational perspective, however, what are the data quality implications when we have to use data across organisations?

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