Littal Shemer Haim

People Analytics, HR Data Strategy, Organizational Research – Consultant, Mentor, Speaker, Influencer

HR Challenges in A Data-Driven World

A valuable part of my tailwind comes from my global community of experts who dedicate their careers to helping executives and managers, especially in the domain of HR, to become more data-driven. Here's an interview with one of my data heroes. Her opinions resonate with my own.
Photography by Littal Shemer Haim ©
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My personal endeavor to educate HR leaders by exposing them to data science fundamentals is continuing. Fortunately, a valuable part of my tailwind comes from my global community of experts who dedicate their career to help executives and managers, especially in the domain of HR, to become more data-driven. I was privileged to interview lately one of my data heroes, Tracey Smith, about her experiences and efforts. I was happy to find out that her opinions resonate with my own. So, without further ado, here’s her interview, which I’m sure offers validation to many of you, on your journey to data-driven HR.



LSH: Tell us about your background, Tracey, and about your main activities today, as an author and a consultant.

TS: In the early 1990s, I graduated with degrees in applied mathematics and engineering. I was hired by an automotive company to build predictive models for the performance of automotive components. This capability did not previously exist, and the creation of these models saved substantial time and cost related to product design iterations. The demand for the creation of these models increased rapidly. I was tasked with creating an entire team of simulation experts to serve the predictive needs of this company.

In the 2000s, I transferred the application of my mathematical skills to the area of the supply chain where analytics was rarely used. The benefits of analytics in this area come from cost savings and improved supplier performance. In the late 2000s, I was hired by the VP HR of a Fortune 500 company to teach them how to use metrics and analytics in HR and to implement global strategic HR programs.

In 2013, I left the corporate world to start my own consulting practice in analytics in order to help multiple companies use data-driven decision-making. My main activities consist of conducting hands-on analytics projects for clients, building the tools that clients need to understand their data, and creating on-site workshops and online classes to educate people on the benefits of using analytics. I serve most clients remotely and in multiple countries. Additionally, I am the author of multiple books on analytics and speak at multiple conferences and corporate events each year.


LSH: With such a broad background in applied mathematics and analytics in many fields, why did you choose to dedicate time and efforts in the domain of People Analytics?

TS: The area of human resources has been one that has lagged other areas in adopting the use of analytics. The skills taught as requirements for careers in HR have never included much in the way of numerical analysis. This means that the progression of HR toward being a more data-driven function required people from areas such as mathematics, engineering, economics, or finance to enter HR to demonstrate how to apply analytics to HR processes and to workforce insights. For this reason, I chose to focus my efforts in the domain of people analytics when I first launched my company, Numerical Insights, back in 2013. Today, I serve areas inside and outside of HR.


HR Challenges


LSH: Let’s talk more about the HR sector. What is, in your opinion, is the most prominent challenge that this sector has in a data-driven managerial environment?

TS: The most prominent challenge in HR in a data-driven managerial environment is leadership’s willingness to believe the results of an HR data analysis and to act on those results. The leadership I am referencing here are those inside and outside of HR. Results are more likely to be believed if they are presented by someone that comes from a numerical background. Information provided to HR from other business areas as input for analysis is more likely to be trusted by HR if it is evaluated by someone that has a background aligned to that area.

I will provide two real-world examples of this. I was hired by the VR HR at a client site to assess the workforce levels within their company. Their engineering area provided input on workload levels related to PPAP activities and other activities specific to launching products in manufacturing. PPAP stands for the Product Part Approval Process or the Pre-production Approval Process. It is the list of activities required to validate a part or change in the manufacturing of a part before that part is approved for release to customers. HR did not trust that engineering was telling the truth about the substantial workload level required to complete a PPAP. Engineering did not trust that HR could accurately make workforce decisions for their area. As a former engineer, I understood the PPAP process and the workload associated with it. As a former engineer, and after many questions about the methodology under which I would be conducting a workforce analysis, the engineering department was convinced that the analysis would be mathematically sound and they would believe the results.

As a second example, while working for a Fortune 100 company, I had many discussions with business leaders around the globe. What I noticed when I spoke with leaders from operations and finance, is that they did not take the conversation seriously until I announced that I came from a math and engineering background, not HR. After communicating my background, I was treated with a much higher level of respect, and the conversations were more cooperative and collaborative. When meeting with HR, these areas are historically expecting a “touchy-feely” discussion, not a numerical one.


LSH: I’d like to hear more of your perspective, as a multi-domain expert in analytics, about People Analytics. What are the main differences between studying people at work and other research domains, e.g., in operations, finance, and marketing?

TS: The biggest difference between studying people at work vs. studies conducted in operations, finance, and marketing is that it is much easier to act on the results of a study outside of HR. For example, in manufacturing, I can conduct a study on what settings are required for a piece of machinery in order to optimize the creation of a part. I can communicate these settings to the manufacturing team, and they can change the settings on the machine. They would then validate the improvement of the part and if necessary, conduct a PPAP to approve the part for mainstream production.

When it comes to studying people, you cannot simply turn the dials on people and change the behavior of your workforce. Additionally, there are data privacy regulations and ethical considerations that limit the actions you can take and the studies you can conduct. There are also unintended consequences that need to be considered before conducting certain studies to ensure that the end result doesn’t damage the employer-employee relationship.


HR New Roles


LSH: A lot is changing these days in data, technology, law, and ethics. What do you think about the role of HR departments? Are they a player in these fields? What influence do they have, if at all?

TS: It will be difficult for HR to stay current with the changes in data privacy laws and regulations. Additionally, since technology always exists before regulations are created for those technologies, HR must play a part in maintaining high ethical standards prior to regulation creation.

HR will not be able to play this part alone. It will need to maintain strong relationships with the company’s legal experts, data access and privacy experts, and data analysis experts. In some companies, the data analysis and privacy responsibilities may be transferred to a centralized data analysis team under a Chief Data Officer or under the legal function. Sometimes this makes controlling data access and the scope of analytical studies easier to accomplish.


LSH: What would you advise to HR professionals who what to re-skill or up-skill themselves to be more data-driven? What are the barriers they have and how to overcome them?

TS: The reality today is that the world changes quickly and HR departments will never have enough resources to assist all employees with their career development. It is, therefore, the responsibility of each individual to determine which skills they need for the future and to seek out resources for their own up-skilling. Becoming familiar with the application of analytics to HR is a step in the right direction to ensure that the roles of HR professionals do not become redundant.

There are several barriers to overcome if HR professionals want to up-skill themselves. First, is the willingness to dedicate time to self-improvement. It seems that most professionals consume all of their time with the day-to-day activities of their current jobs. They may need to make a conscious decision to spend some of their personal time on self-development. Additionally, HR professionals who come from non-numerical backgrounds will have to let go of the assumption that only highly mathematical people can do analytics. There are many HR analytics projects of value which can be conducted without going beyond arithmetic. A basic, introductory course can be taken without having to understand specific mathematical techniques.

Even if an HR professional never conducts an analytical analysis as part of their regular job, understanding what is possible with analytics will greatly improve their ability to recognize when they can help a business area by connecting their analytics professionals with a business problem from that area.

LSH: Thank you, Tracey! There’s a lot of food for thoughts in the experiences you shared, and I hope to see more HR leaders gain the value you offer in your books and training opportunities. 

Littal Shemer Haim

Littal Shemer Haim

Littal Shemer Haim brings Data Science into HR activities, to guide organizations to base decision-making about people on data. Her vast experience in applied research, keen usage of statistical modeling, constant exposure to new technologies, and genuine interest in people’s lives, all led her to focus nowadays on HR Data Strategy, People Analytics, and Organizational Research.

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