HR must take ownership of HR master data – part 2

In my previous post I argued that the quality of Master Data is the very foundation of quality HR analytics. I also argued, that HR must take proactive ownership of their organizations’ Master Data.

In this post I will be a bit more nerdy (sorry) and explain what HR Master Data really is. If HR need to reclaim its Master Data we must be sure that we are talking about the same thing;

Master Data can be classified in three layers;

First Level Master Data: 

  • Person Recognition Data (The data that defines a person across all systems/processes):
  • Name (First name and last name)
  • Name of your boss (First name and last name)

Second Level Master Data:

Personal data connected to a person.

  • Name, social security number, date of birth, address, mail, phone number, next of kin, etc.

 Third Level Master Data:

Data in connection to the person

  • Data in relation to different processes
  • Interview Master Data
  • KPI Master Data
  • Competence Master Data
  • Salary Master Data
  • Etc.

To have quality Master Data all three levels must be included but to build it from scratch, start with The First Level and build from there but at the same time at the architecture-design-phase think ahead as to how you would like to have all your three levels to work together.

Most are interested in the Third Level because it is the source of all interesting Workforce Analytics. But in reality, you have to start at the bottom – the first level.

This gets me to the concept of Big Data, which is gaining influence. Essentially, Big Data just means that we are dealing with data so large – often from many different data-sets – that to storing, analyzing and processing them is difficult. But the interesting thing about Big Data is that it promises to deliver insights which are very valuable. The trend for companies is to collect so much data about their employees, products and customers that the Analytics output will give them insights which in turn will lead to higher sales, higher profits and more engaged employees etc.

The problem with Big Data is, that it only works with quality Small Data – another name for Master Data. At a very basic level; you can only build, process and analyze Big Data if the Small data is right – how many employee do you have, where are they located and to whom do they report etc. While being basic, many organizations simply don’t have Small Data which is good enough. And if your Small Data is not good enough you cannot build Big Data.

So again, take ownership of your Master Data and make sure the quality is exceptional. Only then can you build true Analytics.


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