Tech Insights: How Dirty Data Is Slowing Down Good HR Analytics

All the great new analytics tools work from the assumption that we have clean data.

Even when we just do a simple analysis, such as “employees by location,” we are presuming that all the data has been input, that it is accurate, and there are no duplicates.

As it turns out, much of HR’s data is pretty bad.

This is not really our fault. The data is dirty because it didn’t matter that much before and it takes effort to enter data correctly and keep it up to date.

Just look at your own address book; it probably works well if you are just looking up a contact, but how much information is incomplete, inaccurate or duplicated?

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Here’s what is interesting

  • How bad most HR data really is. It is a bigger problem than we anticipated.
  • How expensive it is to fix. BackOffice Associates says being reactive with respect to data quality costs 7 times as much being proactive.
  • The place to start is by looking at process, not at the data. Joe Essenfeld, CEO of Jibe, says that we if we understand the process (as it is really done, not just as it is supposed to be done) we will have a pretty good idea about where the data is going to be weak. To ensure quality data going forward, Essenfeld stresses that you need a good process and people have to buy into the process.

What is really valuable

  • HR needs to learn data quality processes. This is largely a new discipline for HR and one well worth mastering. Experience in managing data quality will become an attractive line on any HR professional’s CV.
  • Mastering data quality opens the door to effective analytics, and analytics will transform HR much as it has transformed marketing.

The world often operates on the principle of two steps forward and one step back. It is exciting what we can do with analytics, but now we discover that analytics only work with clean data and our data is dirty.

That’s OK, we’ll get there in the end; however, mastering the field of data quality has suddenly become a priority.

Data quality management is not as glamorous as other parts of HR, but it is a good career move.

David Creelman, CEO of Creelman Research, is a globally recognized thinker on people analytics and talent management. Some of his more interesting projects included:

  • Conducted workshops around the world on the practical aspects of people analytics
  • Took business leaders from Japan’s Recruit Co. on a tour of US tech companies (Recruit eventually bought for $1 billion)
  • Studied the relationship between Boards and HR (won Walker Award)
  • Spoke at the World Bank in Paris on HR reporting
  • Co-authored Lead the Work: Navigating a world beyond employment with John Boudreau and Ravin Jesuthasan. The book was endorsed by the CHROs of IBM, LinkedIn and Starbucks.
  • Worked with Dr. Wanda Wallace on “Leading when you are not the expert” which topped the “Most Popular List” on the Harvard Business Review’s blog.
  • Worked with Dr. Henry Mintzberg on peer coaching, David’s learning modules are among the most popular topics.

Currently David is helping organizations to get on-track with people analytics.

This work led to him being made a Fellow for the Centre of Evidence-based Management (Netherlands) for his contributions to the field.



1 Comment on “Tech Insights: How Dirty Data Is Slowing Down Good HR Analytics

  1. Funny, most HR don’t know people and individuals at all. It won’t be
    better, it only makes them more lazy and provides them an excuse when
    errors are made: the technology.

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