People Analytics as a Professional Career

What is People Analytics all about?

In this article, we explore HR Analytics as a career path - from Algorithms to Z-Score. This includes its roles, responsibilities, and privileges, and is mostly focused on large corporations. This is primarily for the benefit of new or inexperienced analytics professionals with other domain expertise who are considering a lateral shift to people analytics.

Who are we?

Raja Sengupta: Raja Sengupta has approximately 20 years of experience in Analytics consulting with almost 10 years spent in people analytics consulting for clients in Europe. He has worked with key people analytics consultants and HR tech startups as a consultant and in a direct senior management role for fortune 500 conglomerates in the Europe region. Since 2021, he has diversified in finance analytics and geospatial analytics along HR analytics, synergizing analytics learning from all three disciplines. He is currently the Sr. Associate of Strategic People Analytics at Korn Ferry.

Carolyn Peer: Carolyn Peer (CEO and Cofounder of Humaxa) is an award-winning Human Capital Management industry leader with an MA in Instructional Technology and a BA in Cognitive Neuroscience. Carolyn started her HR Technology career as the Lead Instructional Designer at an early-stage HR Tech startup called ProBusiness. Carolyn helped build the business and ADP acquired ProBusiness in 2003. After taking a leadership position at ADP (running one of ADP’s Learning & Performance organizations for National Accounts), she guided ADP to a top-20 placement in Training Magazine's Top 125 organizations and a top-5 placement in CLO Magazine's worldwide ranking in 2014. Carolyn left ADP in 2017 to join forces with two associates and to found Humaxa, offering a Machine Learning-powered Digital Assistant that predicts and prevents unwanted employee turnover.

Is HR Analytics fundamentally different from Marketing, Finance or Operations analytics?

Analytics as a discipline is not fundamentally different from HR, marketing, finance, logistics or analytics from any other business function. Applying data science and statistics to generate insights and drive efficiency, analysis takes place irrespective of the business domain.

Subtle differences pop up due to data types, business processes, metrics and insights relevant to compliance and data confidentiality issues.

There is also confusion around the representative term. Is it correct term HR Analytics or People analytics?

These terms tend to be used interchangeably and often confusingly, Its critical to note that the genesis of these terms is different

The genesis of HR Analytics lies in adhering to regulatory reporting compliance where certain metrics and statistical reports need to be available to businesses on a periodic basis. The primary purpose for HR Analytics is compliance, auditing, and HR business process improvement and maintenance of HR business performance.

On the other hand, the genesis of People Analytics lies in situations where the secondary purpose of HR analytics becomes the primary purpose. In other words, People Analytics’ primary goal is business process improvement. People Analytics leverages intuitive reporting, predictive and prescriptive insights to improve employees’ welfare, experience, and productivity.

People Analytics, as a holistic discipline, was designed to improve the overall brand and credibility of the organization as a top employer. People Analytics roles often align closely with senior leadership.

In the real world, businesses often have a broad spectrum of analytics roles, and the distinction gets blurred. To avoid any confusion, we will refer to People Analytics as the de facto term throughout this article.

What is the range of functions for People Analytics professionals?

For ease of understanding, let’s divide the function and skills required for People Analytics professionals into four distinct areas:

1.??????Producing different types of insight reports to different HR businesses - for example: Rewards, Talent Acquisition, Learning & Development (L&D), HRBP (Human Resource Business Partner) Operations, etc.

2.??????Managing the data, analytics tools, and technologies typically used by the People Analytics function. This also includes data accessibility and governance as well/???????

3.??????Synchronizing the HR digitization function with service delivery governance????????

4.??????Aligning objectives with those of senior leadership (HR and beyond) to showcase innovative work and collaborate regarding the overall direction of initiatives.

Let's go a little deeper into each of the four focus areas.

HR Insights and Reports could be further broken down into Compliance, Business Intelligence (BI), and Future-of-Work Reporting.

1.??????Basic Compliance Reporting includes charts, infographics, KPIs (Key Performance Indicators, and HR metrics for respective HR functions. ????

2.??????Business intelligence (BI) Reporting includes predictive analytics, attrition modelling, L&D course productivity modelling, talent acquisition efficiency modelling using vendor and mode data, etc.

3.??????Future-of-Work Reporting which includes what- if scenario modelling, factorial Design of Experiments (DOE), game theory, Lean & Six Sigma dashboards. And analysis on big data, among others.

BI & Future-of-Work reporting are based on retrospective analyses of past decisions and provides insights to HR business leaders in terms of future decision making.

In practice is equal priority assigned to all four of these approaches to in HR insights and reports?

Basic compliance reporting remains the core function of people analytics teams. The function typically spends 80% of its time and resources on compliance reporting.

Many HR businesses have KPI reporting mandated as a part of global or regional compliance and governance. Reports may serve multiple HR functions, be periodic, or ad-hoc.

Leaders within HR functions may also use these reports to monitor and drive performance and highlight achievements.

Is Business Intelligence and Future-of-Work Reporting still a low priority in people analytics?

Typically, any time left over after basic compliance reporting is completed, the People Analytics team can focus on more strategic, future-of-work reports. This may depend upon business policies, priorities, and the resources available within the people analytics team.

Future-of-Work reporting can be classified as experimental approaches to HR process simulation, Design of Experiments (DOE), game probability etc. The essence of Future-of-Work Reporting is to provide decision support guidance in operational HR on a day-to-day basis.

For example, Future-of-Work Reporting could help HR answer questions like “Does it make sense to invest more money or less money in a talent acquisition campaign?” or “Should more hiring or layoffs take place, and for which roles?” “Does our promotion or rewards strategy need improvement?” “Where do your succession planning or employee development efforts need to focus?” “Are our programs motiving?”

Apart from reporting and analytics, what are other key functions of the People Analytics function?

One of the key responsibilities of people analytics executives is to familiarize themselves with the business processes of all HR functions.

It’s vital for the people analytics team to understand all the HR business details to generate meaningful insights. This will allow the team to effectively communicate with HR stakeholders.

An emerging trend is that businesses are experimenting with is to encourage HR analytics executives to work through job rotations in various HR operations roles.?This can be a part of an official policy.

This can help familiarize HR analytics executives with the core services of HR. Job rotations and assignments can give insights to ground operations and the criticality of those operations. For example, executives can gain visibility to the intricacies of day-to-day activities, their responsibilities, budgets, process protocols, how teams are structured.

Such rotations can also help People Analytics executives enhance connections and collaborations with HR functional leaders.

Why do People Analytics professionals need a specialist approach for every HR business function? Isn’t that simply just too much work?

There are substantial data dependency, confidentiality, and digital system differences between HR functions. These differences include the type of metrics being tracked and the Key Performance Indicators (KPIs.)

It is imperative to have an operational-level understanding of all functions that full under HR. Without that knowledge, one cannot be as effective of a people analytics professional.

Interestingly, specialist HR services sometimes operate with limited coordination between other HR specialists. Information is often shared only when required, creating further silos.

Large organizations are increasingly recognizing the need for dedicated HR analytics in each core HR function, including Rewards, Talent Acquisition, Learning & Development, etc.

Talent Acquisition Case Study

In Talent Acquisition, for example, we have shown that it’s helpful to have a detailed understanding of how open positions are filled from interview to onboarding, from compensation banding to negotiation, from notice period to how campus recruiting is conducted, from company policies to how demographic data plays a role, from the promotion and reward process to how biases are prevented and how escalations are handled.

What type of HR digital systems are people analytics specialists is expected to deal with?

Most HR process data (i.e., employee lifecycle records) will be in large, enterprise HRMS systems like Oracle HCM, SAP HR, SuccessFactors, ADP, Workday, etc.

There could be separate, dedicated systems for Rewards, Learning and Development, Talent Acquisition, or other systems where big data containing is stored. These systems could be centrally located and managed, or they could be located and managed across different regions.

It’s possible these systems could belong to the parent HRMS systems, or they could be stand-alone or add-on systems from third party vendors.

You may be wondering about the level of involvement from people analytics executives when it comes to these disparate systems. How can People Analytics deliver insights based on data from all of these systems?

People Analytics typically acquires data respective to each Agency of Record (AOR) and delivers insights based on combining data from all of these sources. The People Analytics function can then deliver valuable reports to each HR Business Unit.

Reports and metrics can be delivered in multiple ways including via dashboards, via ad hoc or tactical reports, in spreadsheets or as embedded HTML tables within an email.

Even the dashboards themselves can be built and delivered in different ways. These decisions primarily depend on company structure, data policies, existing HR systems, data compliance laws, the HR team’s analysis skills, and how frequently reports are needed.

How are HR analytics dashboards typically delivered by people analytics teams?

Typically, data visualizations and dashboards are delivered through:

1. Reporting modules that are built in the HRMS itself. Large, sophisticated HRMSs typically include reporting dashboards.

Because the data resides within the core HRMS system itself, this is ideal. It helps maintain standardization, confidentiality, and integrity. It also ensures timely delivery of insights. These systems are typically plug and play. A relatively low level of expertise is required to make use of data and run reports. On the downside, these systems often have a limited range of data visualization graphs and insights may be limited.

2. Dedicated data visualization and reporting platforms like Visio, Tableau, Power BI, Qlik Sense, etc.

Third-party business intelligence tools have pros and cons. They are best suited for an environment where organizational structures and requirements vary from region to region and change often. They also make sense when extensive customizations are required.

Third-party business intelligence tools are also best when protocols and data ownership have clear guidelines and there is good communication between HR and the people analytics function.

The ways of visualizing data in platforms like Tableau, Power BI, and Qlik Sense are comprehensive when compared with data visualization modules located within HRMS systems.

It’s also possible to extract predictive or prescriptive analytics from these third-party systems by using Python or R. This could be a distinct advantage of such systems.

What are the typical challenges surrounding the operational environment? What about data ownership?

The data integration between the HRMS and the functional HR systems can be a challenge. This is especially true when data confidentiality and ownership rules are not well defined. This is also true when there are multiple data dependency layers. This is typical in many large businesses.

The data quality and consistency can also be a challenge, especially during the intake of data from non-digitized systems. For example, regional reporting data may reside outside the core HRMS.

The quality of integrated data insights may come down to the skills and experience of the HR analytics team.

Dealing with data integrations and quality challenges

Application Programming Interface (API) connections between HRMSs and third-party systems can mitigate some data quality and integration challenges.

However, API connections may not possible due to data compliance and security issus.

In many production scenarios it’s essential to schedule data downloads or manually download data from disparate HRMS systems. This can be accomplished with flat files (such as a .csv file) which can be imported into separate reports and dedicated dashboards.

Depending on the scenario, substantial SQL-based data transformation may be needed. The kind of report you are generating will determine what – if any – data transformations are needed. The format of the imported data will also play a role in what data transformations are needed. These data transformations can be executed in local relational data base systems (RDBM) systems like MySQL, Microsoft Access, Microsoft Excel macros, or in component-based database systems like Alteryx, Rapidminer, and Knime.

What are future-of-work technologies in the HR analytics space and what are the benefits they offer?

Component-based workflow platforms are slowly becoming more common. (Examples of component-based workflow platforms include Altrix, Teradata, and Rapidminer.) This makes the whole ETL (Extract-Transform-Load) process easier to execute, document, and automate. Data quality can also be improved.

Component-based databases automate part of the workflow, ensure data integrity, and perform quality checks. With these types of systems, switches and forks can be developed. Python and R libraries can also be added for advanced analysis, enabling it to become an all-in-one HR data system.

Certain parts of the ETL or the SQL queries in the workflow can be reused repeatably. In other words, the same workflow can be used for different reports. Operationalizing reporting and data visualization will make the People Analytics team function with ease.

What other new technologies or though leadership is happening in HR Analytics?

New technologies like AI-based chat bots, generative conversational AI or AI-based reporting platforms are making their way into the HR Analytics market.

AI chatbots act as a virtual assistant, available to employees 24/7/365. While the primary benefit to employees may be getting immediate help, there’s loads of data that can be extracted from these systems.

Business Intelligence reports for operational HR can include employee sentiment analysis, workforce trends, unmet needs, learning gaps, and more. True AI-enabled bots improve over time.

AI-based reporting platforms offer HR professionals interactive sessions with data based on voice commands or AI-based suggestions. The purpose of AI-based reporting systems isn’t to create more reports, but rather to make self-service reporting easier.

For a People Analytics professional, what type of project would require the highest level of technical aptitude?

If talking on an extremely technical project is a personal goal, it’s possible that an HR Analytics Specialist could be called upon to develop a tailored product or app from scratch. It could be possible to apply for a patent. It could be necessary to build a specific type of report or simulation tool for interactive data visualization. An advanced analytics product like a chatbot or NLU (Natural Language Understanding) tool might also be needed.

What are the non-technical positions for HR analytics professionals? How does HR Digitization contribute to non-technical HR Analytics roles?

While people analytics' primary focus is on providing reports, metrics and insights to different HR functions, HR Digitization is the custodian of data generated for these reports.

Strong lines of communication between People Analytics and HR Digitalization is critical. People Analytics professionals can also obtain expertise in the licensing, administration, configuration, authentication, and in global HR digital systems.

Growth and long-term prospects of People Analytics professionals

There are a wide variety of career paths within People Analytics. It’s possible to specialize in HR data science and even change verticals. For example, it’s possible to focus on Finance, Logistics or even Space Utilization. Many opportunities will depend on availability of projects that are presented or that one chooses to go after.

If you are interested in a full-time corporate HR or People Analytics career and are willing to learn, the time is now. A 20+ year career working with senior leaders in HR and Technology can be rewarding, both intellectually and monetarily.

If data science and analytics – even outside of HR- is of interest to you, it may be a good idea to focus on data science processes and routines in a variety of domains. This can open many doors and help you find a fulfilling role in a large corporation or in an analytics-focused HR technology startup.

Top Ten HR Analytics Guidelines (according to ChatGPT):

1. Continuously educate yourself and stay up to date on the latest developments in People Analytics, as the field is constantly evolving.

3. Collaborate with other data-driven professionals such as data scientists, data engineers, and business analysts to gain insights and approaches to problems.

4. Be a proactive thought-leader in people analytics and advocate for the value that People Analytics can bring to organizations. Help others understand the potential of data-driven insights to drive better outcomes for both employees and the business.

5. Be ethical and responsible when working with sensitive employee data. Ensure that all data is handled in accordance with relevant laws and regulations, such as data privacy laws.

6. Take an interdisciplinary approach when solving problems. Use a combination of business, technical, and people skills to drive impactful outcomes.

7. Develop strong communication skills to effectively articulate insights, recommendations, and results to non-technical HR stakeholders.

8. Build relationships and seek feedback from HR leaders, HRBPs, and employees to gain a better understanding of the challenges and opportunities in the HR domain.

9. Embrace a culture of continuous improvement and be open to learning from experiments. This will help you grow as a people analytics practitioner and drive better insights for the HR business.

10. Seek opportunities for professional development and take advantage of networking via HR conferences, seminars to improve career prospects in people analytics.

Finally, Nine Golden Rules for People Analytics professionals (written by us, the human beings):

1. Most HR operational leaders are not from a STEM (science, technology, engineering, and math) background. You will need to gauge their understanding of data science and proceed at an appropriate pace.

2. Many HR organizations - especially those in large corporations - have a transactional mindset. Its purpose may be to ensure protocol and etiquette.

3. If you plan to initiate a breakthrough or disruptive data project, make sure you have support from key individuals within senior HR leadership and clearly defined business goals.

4. Operational HR leaders usually have great people management and leadership skills. Don’t pass up an opportunity to learn from them.

5. When proposing a solution to a problem HR leadership is aware of, it’s often a good idea to explain the problem and solution in reverse. Explain what would happen in the next quarter or year if no solution is implemented. Back your solution up with data.

6. When presenting HR dashboards, do NOT over-complicate them. Keep it simple and focus on user-friendliness. Display only the metrics that really matter.

7. Always validate your results thoroughly before presenting a solution to senior HR leaders.

8. Consider what your analytics or HR dashboard inadvertently highlight at the business unit level, especially when access to data is not tightly controlled.

9. There is great power in people and workforce data. Enjoy the journey and good luck!