3D Results Blog

People Analytics: State of the Industry

“What is the current state of the People Analytics industry?” 

The answer to this question is more complicated than you might imagine. Let’s structure the answer around three general topics: Strategy, Metrics, and Technology. But first, before we dive in, we need to understand “Analytical Maturity.” 

Analytical maturity, or the People Analytics Maturity Curve, is a theoretical model which identifies the various levels of maturity, experience, and complexity of HR reporting teams. Understanding your current level of maturity will determine your reporting needs and capabilities. This current state analysis will drive your metric selection, strategy discussions, and technology requirements. When we understand your current state, we can accurately forecast your future needs, ensuring you are ready with the appropriate metrics, changes in reporting strategy, and updates to technology. 

Maturity Model2.pngFirst and foremost, the vast majority of organizations currently reside in the “Foundation” and “Intermediate” levels of maturity. Companies in the “Foundation” level of maturity often have disparate HCM systems, and rarely contain an aggregated data model—which would unite the data from these unique systems. Reports are very often produced on an ad-hoc basis without a structured distribution schedule or mechanism. As companies increase their level of sophistication to the “Intermediate” level, they take an enormous first step in advancing their reporting capabilities. First, they have invested in a data warehousing/aggregation solution; second, they have standardized and prioritized all of their metrics; and finally, they’ll have invested in a reporting-specific technology solution.

The “Advanced” level of maturity begins to move away from reporting, and towards true, research-based analytics. In this stage organizations are beginning to examine causal relationships into problematic areas. Hypothesis testing, research design, and statistical analysis are crucial at this level. The “Strategic” level begins to measure the impact of research derived interventions implemented during the advanced stage. For example, “how does simplifying the recruiting pipeline impact our quality of hire?” Finally, the “Predictive” level focuses on forecasting the impact of interventions, as well as diving into the proverbial deep-end of data analytics.

It is important to understand that as organizations move along the maturity curve they retain the competencies acquired from lower levels in the model. Mature organizations have acquired the right knowledge, skills, and technology to streamline and automate lower-level reporting needs.

Now, let’s review the current industry best practices and organizational needs we see in the market today. Most importantly, let’s return to the three general topics of Strategy, Metrics, and Technology. Clients typically ask about strategy: What are other company’s reporting on?  How do we get started with true people analytics? What are the skills we should be recruiting for?

The explosion in interest and investment in this area is forcing organizational analytical teams to think strategically about their reporting teams’ skills, responsibilities, and capabilities. As your leaders demand data driven insights, you might be realizing those manually produced excel dashboards lack the actionable real-time data insights required today. Organizations want outside expertise to help roadmap their progression through the maturity curve. Companies want expertise on not only metric standards but also selecting the what are the appropriate metrics which align with business strategy in order to build story-based dashboards. The ultimate goal is to combine informative metrics (e.g. Headcount, Turnover Rate, etc.) with insights: How and why has headcount changed overtime? What are the turnover rates for voluntary, involuntary, regretful, constructive turnover?

Diving deeper into the metric discussion, we find that standard metrics/dashboards are a great beginning and an effective quick-win for your people analytics teams. Companies with relatively young analytical needs and capabilities welcome the structured nature standard reports and metrics deliver. Providing real-time dashboards with industry standard metrics and allowing for insightful discovery will solve two reporting issues the majority of organizations face today.  First, they provide real-time access to data and metrics your leaders have been asking for on a regular basis:  What is our hiring rate? How many requisitions do we have open? What is my average Time-to-Fill?. No longer does an analyst need to gather the data and construct a dashboard, leadership can simply log on and access the information they need in real-time.

Second, as your need and desire for advanced analytics matures you have unknowingly entered a feedback loop of “Answers-Questions-Insights.” For example, a standard recruiting dashboard might provide a metric such as “# Open Reqs” which provides an answer to a simplistic question. That answer ultimately leads to other questions (e.g. “What is workload of my recruiters? What is the average age of my open reqs?). These questions require increasingly complex analytics driving their analytical maturity. Here are common recruiting metrics we recommend on a regular basis. 

  • # of YTD Hires (KPI)
  • Trending Hires (Charts comparing current year vs. previous year)
  • Trending Hires by Month (Chart)
  • # of Current Week/Month Hires (KPI) 
  • Internal/External Hires Ratio (KPI)
  • # of Hires by Recruiter (Chart) 
  • # of Hires by Source (Chart)
  • Quality of Hire (Chart - Performance Rating for first year hires of turnover of first year hires)
    • Quality of Hire by Recruiter or Source
  • Diversity of Hires % (KPI)
  • Offer Acceptance Ratio (KPI) 
  • Offer Acceptance Ratios by Recruiter (Chart) 
  • % Referral Hires (KPI)
  • % Referral Applications (KPI)
  • # of Pending Regs (KPI)
  • # of Open Regs (KPI) 
  • Trending Opened Regs (Chart comparing current vs. previous year) 
  • # of Open Regs by Recruiter (Chart) 
  • # of YTD Filled Regs (KPI) 
  • # of YTD Filled Positions (KPI)
  • # of Filled Regs by Recruiter (Chart) 
  • Avg Age of Open Regs (KPI)
  • Ave Age of Open Regs by Recruiter (Chart) 
  • Avg Time to Fill (KPI) 
  • Avg Time to Hire (KPI)
  • Avg Time to Offer Accepted
  • Avg Time to Fill by Recruiter (Chart) 
  • Application Funnel (Current) - How many application is each active pipeline stage
    • Avg time application in current stage
  • Application Funnel (Historic) - Historical application flow ratios between pipeline stages
    • Avg time application in each stage
  • Source Effectiveness (# of Applications and/or Hires by Source)

Let’s turn our attention to the role of technology in the people analytics space. As aforementioned, your business leaders are placing increasingly more pressure on your HR reporting teams to produce insightful analytics. As you find yourself on the first or second level of the maturity curve your business requests are not only pushing the limits of your analytical knowledge and skills, but also your technology. The days of the “Excel Olympics” are quickly becoming obsolete as true data driven insights require advanced technology. Companies are beginning to partner with 3rd party vendors who supply the analytical platforms capable to consume, analyze, and distribute insights in real-time. Currently, we are seeing three distinct technology models emerging: self-service, custom, and hybrid. These models are a result of the varying analytical, technological knowledge, and skill discrepancies between clients. Some organizations are requesting full self-service platform capabilities which allow the client to construct their own reports and metrics. Some organizations lack the appropriate resources and require a custom approach where the consultant constructs custom (to specifications) reports and dashboards which are then delivered to the client. Finally, clients who invested in a hybrid approach are leveraging the platform to develop their own reports while transitioning more complicated analytics to the consultant.

Finally, let’s examine some of the technological capabilities you might be after when making an investment. First and foremost, the centralization of data from disparate company systems (including HR systems such as SuccessFactors, Workday, PeopleSoft, Lawson, CareerBuilder, etc.) take absolute precedence. An analytical platform has to be data agnostic and incorporate data from various systems into one comprehensive data model. For example, the client has to have the ability to query and join data coming from their ATS, Comp, and HRIS systems effortlessly without the need of complicated SQL joins or excel V-lookups. Next, platform simplicity, or what we call “Analytics for the Masses,” is another critical aspect you need to consider. Whether it be producing a list of newly hired employees, calculating headcount, or predicting attrition, enabling a wide range of capabilities to quickly produce insights is important to create buy-in and avoid regressing to the mean (i.e. The Excel Olympics). You might may also be interested in benchmarks. Benchmarks provide complete anonymity and allow companies to compare themselves against their peers as well as industry specific competitors. Lastly, the distribution of analytical insights is an important factor to consider. Distribution can mean providing automated (scheduled) reports delivered to users’ inboxes or even providing access to real-time dashboards users can view, filter, share, and download. Effective distribution is one of the more important factors to consider when attempting to establish leadership buy-in and support for your analytical progress.

Dimensional Model.png

The relatively young nature of the People Analytics industry has been mainly due to the limited availability of cloud data, but with the advent of cloud-based HCM systems, such as SAP SuccessFactors, we are well on our way. The industry is advancing at neck-breaking speed with new trends emerging on a daily basis.  Taking the current snapshot in time we have identified strategic, metric, and technological trends you might be attempting to solve as you mature your people analytics processes.    

Organizations pursuing analytical insights often need assistance with developing a people analytics strategy which supports the business goals and continues to mature as business needs expand We’ve assisted hundreds of customers along this journey, let us know if we can help.

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Kamil Mysiak

Kamil is a Senior Data Science Consultant at 3D Results. As a subject matter expert behind SAP SuccessFactors analytics and reporting tools, he has been a data scientist engaged with workplace statistics before “analytics” gained popularity as a buzzword. His combined 8+ years of experience working with data, big data and analytics, and an MA in Industrial/Organizational Psychology from Florida Institute of Technology, help shape his ability to turn statistics into meaningful insights.

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