GETTING AHEAD OF THE CURVE:SCALING YOUR HR

ANALYTICS PRACTICE

GETTING AHEAD OF THE CURVE: SCALING YOUR HR ANALYTICS PRACTICE | 2

THE HR FUNCTION IS POWERED BY PEOPLE ANALYTICSPeople data and people analytics are transforming HR.1 Our research supports the trends you may have observed in recent years—data analytics skills are becoming increasingly important for HR professionals at more than 4 out of 5 organizations.2 In addition, roughly two-thirds of organizations not only rely on their HR analytics practice to drive business decisions, but have set the development of people analytics capabilities as a strategic priority (Figure 1).

Thinking about your current organization, please rate your agreement to the statements below. (Percent who Agree or Strongly Agree)

FIGURE 1

The reliance on people analytics to inform talent and business decisions is fuelling a hunger for deeper and more meaningful insights and driving greater complexity in people analytics activities across organizations. Over the past four years, HCI’s research has characterized people analytics activities on a continuum from “Foundational” to “Highly Advanced” (Figure 2). While the criteria for these categories have remained the same, the proportion of organizations and people analytics professionals that identify with each has dramatically shifted, with fewer in the “Foundational” and “Building” categories over this short time span.

The accelerating shift in this curve holds significant implications for the road ahead. More sophisticated and more detailed people analytics projects require increasing amounts of information, resources, skills, and tools. What are the steps they take to maintain momentum and get ahead of the curve?

Data analytics skills are becoming more important

for HR professionals at our organization.

Developing people analytics capabilities is a strategic

priority for my organization.

Most of the analytics projects we have conducted resulted

in a business decision being made.

82% 67% 64%

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FIGURE 2

Foundational

Building

Integrated

Advanced

Highly Advanced

Categories for evaluating people analytics activities across organizations.

Proficient at descriptive reporting of single-source data.

Proficient at creating and tracking indices of variables from single-source data.

Proficient at evaluating comparisons and trends from multiple data sources.

Proficient at using multiple data sources to create forecasts and models.

Proficient at simulations and running experiments to test hypotheses that will dictate talent practices and using external, social, and internal data.

Foundational Building Integrated Advanced Highly Advanced

21% 19%

8%

45%

39%

15%

2%

10%

14%

27%

2017

2020

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GETTING AHEAD OF THE CURVE: PEOPLEKeeping pace with the increasing demand for talent insights isn’t without its challenges. At least 40% of organizations report they currently lack adequate resources to build their people analytics capabilities. These key resources include not just the time needed to create and execute analytics project, or the budget required to support these projects, but also the people needed to do the work. As a result, many organizations have prioritized building stronger analytics teams as an important piece of their strategy to meet their needs.

Building an analytics team can take many forms: buy, build, borrow, or even bot. Some organizations are actively recruiting new hires, but not every organization is able to increase staffing. Instead, more than 75% of organizations are redeploying talent already within their organization, building the skill sets they need through training and development efforts, or both (Figure 3).

FIGURE 3 How is your organization meeting its people analytics skills needs? (Select all the apply.)

“Build” needed skills and capabilities in your people

“Buy” new hires with the desired skills

“Borrow” talent from other departments inside your

organization

Hire a consulting firm or contract talent

32%

26%

24%

50%

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FIGURE 4 Percent of respondents indicating a skills gap in these areas.

Data security

ROI outcomes and measurement

Data visualization

Trend analysis

56%

54%

53%

51%

51%

49%

45%

42%

41%

40%

60%

GETTING AHEAD OF THE CURVE: SKILLSDeveloping analytics teams with additional training may be a popular approach to improving an organization’s people analytics capabilities, but it isn’t a complete solution. In fact, despite increased attention to training, only 45% of these organizations report they have the people analytics skills sets they need. And, even when learning opportunities are freely available, nearly one in five (18%) indicate this training may be inadequate. That’s why it’s important to maximize the organization’s efforts by identifying and targeting the skills that are most needed by the team and addressing these through the right training or tools.

Our research indicates that although skills gaps are greatest in the areas of data security, the evaluation of return on investment, and data visualization, similar skill gaps are also found across the development, deployment, and delivery of analytics projects. Understanding your organization’s challenges, whether these are primarily in the measurement or collection of data, blending and storing these data, performing analyses and simulations, or even sharing and communicating results, allows you to identify the most effective solution.

Data governance/policies

Communicating insights/ storytelling with data

Designing dashboards

Data extraction, transformation, and loading (DETL)

Database management

Simulations

Machine learning

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GETTING AHEAD OF THE CURVE: TOOLSBuilding the skills of people analytics team requires significant time and investment. In many instances, the better solution is to increase the capabilities and capacity of teams with technology. Access to the right tools and resources can often mean the difference between an analytics team that struggles to provide only the most basic, reactive, analyses and reporting and those providing advanced and strategic insights.

Despite this, only a third of organizations (33%) report having a technology solution specifically intended for people analytics projects. Most still rely on a combination of ad hoc solutions to meet their needs which may explain some of the challenges they report in attempting to build their people analytics capabilities (Figure 5). For instance, at least a quarter of organizations report a lack of data integration across the talent lifecycle which is vital to understanding workforce patterns and trends. Others report a lack of data integration from business functions outside HR, which poses barriers to planning and staffing.

FIGURE 5 Select responses to the question: What are the top challenges to building people analytics capabilities at your organization? (Select the top three.)

25%Lack of data

integration across entire talent

life cycle

22%Inadequate

technology to aid the process

21%Lack of data

integration from other business

functions

12%Lack of access to

talent data12%

Lack of access to timely, real-time

data

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THE RIGHT TOOL CAN ADD EXPONENTIAL CAPACITYThere are a lot of tools to choose from, and none offer a one-size-fits-all solution. When chosen and managed appropriately, however, the right tool elevates people analytics capabilities without expensive investments in training, and adds exponential capacity without hiring new talent. Many augmented analytics solutions offer distinct advantages for improving the efficiency and effectiveness of HR and talent management. These tools typically integrate talent and business data in a single platform to provide a complete, secure, and accurate pool of information for generating analyses. In addition, they make it possible to automate routine analyses, freeing up HR analysts to advance more complex projects.

Augmented analytics tools can also be used to more effectively monitor performance on talent and operational plans as well as uncover connections and patterns across vast datasets that might otherwise go undetected. Machine learning algorithms help recognize anomalies in the data and predict the issues with the most importance to the organization. By searching for, and then surfacing trends, these tools can reduce or eliminate the time spent manually exploring and testing hypotheses. Finally, these tools can offer features that wrap findings in natural language, allowing analysts to share dashboards and report results more quickly, and in a way that is easily understood and interpreted by business leaders.

We’ve seen a growing number of organizations adopting these technology solutions.4 The outcomes associated with the use of these tools include more personalized employee experiences, a reduction in implicit biases during recruitment, hiring, and performance management, improved retention, and a reduction in overwork burden on HR and People Analytics professionals.5

Realizing these benefits is possible for every organization. Build your analytics teams by identifying and developing their skills. Complement their capabilities while building capacity with the tools that deliver the insights most needed by your organization. Get ahead of the curve and successfully scale your HR analytics practice by aligning people, skills, and tools.

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WHAT IT IS WHAT IT MEANSAugmented Analytics

Graph Analytics

Artificial Intelligence (AI)

Machine Learning (ML)

Natural Language Processing (NLP)

Get familiar with the new jargon in order to help you find the right people analytics tools. Here is a quick overview of some of the most common features of people analytics tools.

Leveraging a range of artificial intelligence features, including machine learning and natural language processing, to quickly surface information that is difficult for analysts to uncover manually. Augmented analytics is a blanket term for augmenting the entire process of analysis, including the preparation and interpretation of data.

Systems and software designed to make and execute “intelligent” or sensible decisions. These rely on various forms of knowledge representation, machine learning, natural language processing, and other computing and analysis techniques. These systems typically draw real-time data from a wide range of sources.

An advanced learning algorithm that improves automatically through experience. Instead of specific programming rules, a machine learning algorithm is built on a mathematical model based on sample, or training data. It improves decisions as new data becomes available to optimize your desired goal. Machine learning is a subset of artificial intelligence.

A type of machine learning specifically intended to recognize, manipulate, and emulate human speech and text. This is used in a variety of scenarios from automating help scripts and chatbots, to analyzing sentiment and themes in open ended survey responses or resumes, to providing plain-language interpretation of the results of analyses.

An approach to analytics that is based on capturing, enriching, and analyzing relationships within datasets rather than between objects or entities.

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ENDNOTES 1. Marr, B. (2018, April 13). Why Data is HR’s Most Important Asset. Forbes. https://www.forbes.com/sites/bernardmarr/2018/04/13/why-data-is-hrs-most-important-asset/#217f0e896b0f

2. Data for this report were collected from 233 HR analytics professionals in January of 2020. In this research, 64% are at or above the managerial level, and 83% are with organizations headquartered in North America.

3. Filipkowski, J. & Heinsch, M. (2017). Talent Pulse 4.4: Developing Sustainable Strategic HR. http://www.hci.org/hr-research/talent-pulse-44-developing-sustainable-strategic-hr

4. Zielinski, D. (2019, December 4). People Analytics Software In Changing the HR Game. HR Magazine. https://www.shrm.org/hr-today/news/hr-magazine/winter2019/pages/what-you-need-to-know-about-hr-people-analytics-software.aspx

5. White, D. (2019, October 21). 8 Ways Artificial Intelligence Can Transform the Future of HR Analytics. HR Tech. https://www.techfunnel.com/hr-tech/artificial-intelligence-future-hr-analytics/

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ABOUT THE RESEARCH PARTNERS

Workday is a leading provider of enterprise cloud applications for finance and human resources. Founded in 2005, Workday delivers financial management, planning, human capital management, and analytics applications designed for the world’s largest companies, educational institutions, and government agencies. Organizations ranging from medium-sized businesses to Fortune 50 enterprises have selected Workday.

We founded HCI on the principle that strategic Human Capital Management is the most powerful lever for performance and growth. We believe that your talent strategies and partnerships with the business create value and improve people’s experience at work. Since 2004, HCI’s research-based learning solutions have helped leaders, human resource and talent management professionals plan for, acquire, engage, and develop their people. In class, online, or in house, we equip HR with the capabilities to translate strategy into results. Visit HCI.org to learn more.