Numerical Insights
Turn Data into Improved Business Results

Analytics Articles for Business, Supply Chain and HR

Analytics Articles: Human Resources, Supply Chain, Diversity and Business Analysis

Numerical Insights publishes articles on a variety of topics including business analytics, data analysis, data visualizations tools, improving business results, supply chain analytics, HR Analytics, strategic workforce planning, and improving profitability. We aim to make our articles informative and educational.


Failure is not an Option: The Mindset for Success in Analytics


Being successful in analytics requires a thick skin, head-strong determination and a “failure is not an option” attitude. The challenges are many. They are often unexpected and constantly changing. In this article, I will demonstrate a few of the challenges from an HR analyst point of view, but the challenges apply to analysts in all functional areas.

Disparate Systems Producing Multiple Data Sets

HR has, and always will have disparate systems producing multiple data sets. The same holds true in areas like procurement and operations. While companies would love to have one system in HR, the fact remains that there will always be a combination of in-house, third party and manually-tracked data sets. While some vendors are trying to be your “one HR solution,” there are too many specific items that global companies need to track where there would never be a business case for an HR vendor to code it into their system. 

The challenge with multiple data sets from different systems comes when you need to merge this information to answer a specific business question. As an example, suppose you need to merge data from your recruitment system with information from your employee data system.

If the recruitment system records the employee number of the successful candidate, then it can be used to find the matching data from the employee system. If you are lucky enough to have one of the few HR systems that have combined the employee data with the recruitment module, then transferring recruiting data into employee data for successful candidates will take you less than a minute.

However, most recruitment systems remain separate from core HR employee systems at current time and they rely on manual input from the recruiter/HR business partner which doesn’t always occur. That leaves the option of trying to map multiple fields between the two systems to uniquely identify individuals which usually requires exact matches on several text fields. We all know the fun that Mike Jones in one system gives us when he’s Michael Jones in another.

Implementation of the GDPR

The GDPR, or General Data Protection Regulation, is an updated set of data regulations which companies had to have in effect by May, 2018. At current time, this regulation applies to the EU and the UK. Whether the UK remains in this agreement after Brexit or whether it opts to create its own data regulations remains to be seen.

For global companies and vendors serving global companies, this regulation presents extra challenges. It adds requirements for additional overhead such as needing a Data Protection Officer. It adds the challenge of where to house global data and, in some cases, may force the separation of global data into multiple regions or countries. This is unfortunate since most global companies have been working to merge their multi-country, multi-region data together over recent years. With separate regulations forming in many countries, global companies may revert back to having, as an example, a European instance of their data, an American instance, a Canadian instance, an Asian instance, an Australian instance… you get the idea.

Under the new regulation, analysts in the EU will feel a higher level of administrative pain in trying to move analytics projects forward than their North American counterparts.

Accessing Data Outside of HR

Even within your own country, you may experience challenges in accessing data outside of HR. After speaking with many analysts over the last 8-10 years, the most popular hurdle is Finance not wanting to send data to HR and HR not wanting to send people data to Finance. I’ve never had an issue gaining access to procurement or operations data, so the HR-Finance challenge seems to be an ongoing issue.

For the Finance-HR barrier, recognize that the challenge is in both directions. I have received calls from HR leaders telling me that Finance wants certain information from HR and the HR leader is nervous about passing the data along. If you take the time to understand why Finance wants certain data, often an average, range or scaled value of a certain “sensitive field” will be sufficient for Finance to complete their desired investigation.

As for HR accessing Finance data, I understand how large that challenge can be in some organizations. In one large company, I had access to Finance data but couldn’t release my analysis to the business areas without Finance reviewing my calculations. It was a “check mark” hurdle that took a long time since analytics coming out of HR was not a priority for the Finance team. In the end, by the time I received a “check mark” from Finance, the numbers were so outdated that they had no value. This activity was dropped after 3 attempts to speed up the process.

What I recommend in this situation is to buy your internal lawyers a good cup of coffee and develop a really good relationship with them. Often, a lack of access to data outside of your own functional area is a nervousness caused by the uncertainty of what you plan to do with the information and to whom you plan to distribute it. It’s easier for other functional areas to say no than to take the time to work with you to understand your intent.

Internal legal experts have a great way of cutting to the chase and understanding the value you can provide with HR analytics. A nod from the legal team has a way of speeding up data access nicely.

Over my 25 years in analytics, I have experienced many hurdles in data projects... most of which can be dealt with using some thought and creativity. Since HR works with people data, my experiences have shown me that the challenges to this group are higher than other functional areas. It is easier to act on what the data tells you when the subject is a manufacturing machine rather than people. For more details on that subject, see my recent article on People vs. machines: the ongoing ethical concerns of people analytics.

Adopt patience and a “failure is not an option” attitude and you will be successful.


Tracey Smith is an internationally recognized business author, speaker and analytics consultant. She is one of the most highly respected voices when it comes to business analytics and HR analytics. She is the author of multiple business books and hundreds of articles in a variety of publications. Tracey has worked with and advised organizations, both well-known and little-known, on how to use data analytics to impact the bottom line. If you would like to talk to Tracey about consulting work or speaking engagements, please use the Contact Us form.