The science of HR data storytelling

In 2023, we find ourselves amid a digital revolution characterized by the daily generation of an astounding 3.5 quintillion bytes of data – a figure comprising 3.5 followed by an astonishing 18 zeros. The statistic revealing that 70 percent of business leaders contemplating relinquishing their decision-making to robots should be no surprise. With such an overwhelming volume of data available, it can be a daunting task to draw meaningful conclusions.

Let’s take the example of employee turnover. While the prevailing notion suggests that higher pay leads to longer employee retention, this perspective contradicts the findings published by HBR. According to the Harvard Business Review, 9 out of 10 people are willing to accept lower salaries for more meaningful work. In this era where numbers seemingly do not lie, it’s crucial to recognize that data can be misleading without adept interpretation. This is where the art of data storytelling emerges as an invaluable guide, bridging the gap between raw data and meaningful insights.

In our recent workshop, we explored the vital role of data storytelling in HR, specifically through external market data insights. The workshop featured Florian Fleischmann, managing director of HRForecast, who discussed how data-driven HR strategies, driven by external data, are transforming the HR landscape.

Data storytelling in HR is an essential practice involving the strategic use of internal and external data to construct compelling narratives guiding talent management and HR decisions. It transcends conventional data presentation, transforming raw information into actionable insights through persuasive storytelling. This approach addresses the limitations of relying solely on internal data by incorporating external sources like job postings, offering insights into skills demand and location-specific salary variations. Advanced algorithms help identify emerging job market trends, facilitating data-driven recruitment strategies.

Data storytelling empowers HR with the knowledge to adapt to changing skill requirements and align workforce development with industry trends. Ultimately, it ensures HR decisions are rooted in comprehensive data and meaningful narratives for a competitive edge in talent management.

In the compelling contest of narratives, the emphasis extends beyond mere data to the art of narrative delivery. To exemplify the considerable impact of data storytelling, consider an organization’s focus on mitigating employee turnover and promoting elevated employee retention. On one front, a riveting narrative stands as sharp as a blade, while on the other, a convoluted storyline requires a protagonist. This example elucidates how the craft of data storytelling functions as the guiding beacon for the transformation of HR strategies.

1) Data quality challenges

Data integrity: Maintaining data integrity ensures accuracy, completeness, and consistency. It’s about entering data correctly and preventing errors, duplications, and inconsistencies across different HR systems and sources. This involves data validation, cleansing, and ongoing monitoring.

Data relevance: In a sea of available data, the challenge is identifying which HR metrics and data are most relevant for effective storytelling. This process requires HR professionals to determine which data points have the most significant impact on their decision-making processes.

2) Data interpretation challenges

Complexity: HR data can be incredibly complex, involving numerous variables, from performance metrics to employee demographics. Extracting meaningful insights from such complexity requires advanced analytical skills. Complex data might include data from multiple sources, structured and unstructured data, and multi-dimensional data, adding layers of complexity to interpretation.

Bias: Bias can creep into HR data at various stages, from data collection to analysis. Identifying and addressing these biases is challenging, as it requires domain expertise in HR and the ability to recognize subtle biases that can affect storytelling objectivity.

3) Technical challenges

Data integration: HR systems often comprise multiple components, from HRIS to applicant tracking systems and performance management tools. Integrating data from these various sources is technically complex, and it necessitates the use of integration platforms, APIs, and data transformation processes to ensure that data is consistent and accessible for storytelling.

Data analysis: HR professionals must leverage advanced analytical tools and techniques to derive meaningful insights. This requires expertise in data analytics, statistics, and data modeling. Data analysis also involves dealing with large datasets, which can be technically challenging.

4) Communication and presentation challenges

Data visualization: Visualizing HR data in an accessible and engaging manner for non-technical stakeholders is an art. The challenge here is to present data through effective graphs, charts, and visuals, which convey complex insights intuitively.

Narrative building: Creating a compelling narrative around data is no small task. It requires not only data expertise but also storytelling skills. The challenge is to tell a coherent and engaging story that contextualizes data, making it meaningful and relevant to the audience.

5) Privacy and compliance challenges

Data security: Ensuring data security while using sensitive employee information for storytelling is a paramount challenge. It involves robust data encryption, access control, and compliance with data protection regulations like GDPR.

Compliance: Keeping up with evolving legal and ethical standards related to HR data usage can be challenging. HR departments must stay informed about changing data protection laws and ensure compliance in data usage.

6) Change management challenges

Resistance to change: HR professionals often encounter resistance when transitioning from traditional HR practices to data-driven decision-making. Resistance can stem from employees and even leadership who are comfortable with traditional methods. Overcoming this challenge requires effective change management strategies that involve communication, education, and addressing concerns.

Aligning with organizational goals: Ensuring data storytelling aligns with HR and broader organizational objectives is challenging. Data-driven HR strategies must be effective and seamlessly integrated with the organizational plan. To address this, HR professionals need to align their data storytelling efforts with the organization’s strategic goals, demonstrating how data-driven decisions contribute to achieving those goals.

7) Cultural challenges

Data-driven culture: Fostering a data-driven culture within HR involves changing mindsets and practices. This cultural shift challenges the conventional wisdom that has existed for many years. HR professionals must instill a sense of data literacy, encouraging all HR team members to use data effectively in their decision-making processes. This might involve educational initiatives, mentorship, and leadership that promote data literacy as a core competency.

Overcoming silos: Silos often develop over time, lacking collaboration and communication between HR and other business units. Addressing this challenge requires promoting cross-functional collaboration, possibly restructuring the organization to facilitate information flow, and instilling a mindset of shared responsibility in data utilization.

8) Measurement and ROI challenges

ROI measurement: Quantifying data-driven HR initiatives’ impact and return on investment is complex. Not all outcomes can be directly translated into monetary terms. For example, the impact of employee engagement initiatives may not have a clear financial value. HR professionals must explore ways to measure the effectiveness of initiatives beyond simple financial metrics. This can involve surveying employees, monitoring changes in performance, and assessing qualitative improvements.