We are currently working in detail on the possibilities of generative AI and a European standard for sustainability reporting (ESRS) in line with the CSRD, which came into force at the beginning of January 2023. What does this mean for people analytics? Is the next stage of development due?
The clear answer to these questions is: YES. Over several maturity levels, People Analytics has evolved from descriptive reporting, benchmarking and dashboards into predictive and prescriptive analytics:
Predictive analytics
refers to the use of data and statistical algorithms to predict future events or trends. It relies on historical data and modeling techniques to create forecasts. This form of analysis helps companies identify patterns and trends.
Prescriptive analytics
goes one step further than predictive analytics. It not only uses predictions, but also provides recommendations for actions and decisions in order to achieve a desired result. This form of analysis combines predictive models with decision rules to answer “what should be done?”. It helps to optimize decision-making processes.
Let’s be honest: Although current figures vary and depend on various factors such as company size, industry and technological maturity, in the DACH region it is mainly large companies and multinational corporations in sectors such as automotive, financial services and pharmaceuticals that are already using such analyses.
Systemic people analytics as the next stage of development?
In his essay analyzing the development and progress of people analytics, Josh Bersin claims that “people analytics has grown up”. This requires company-wide integrated data to make decisions about goals, next steps and employee needs.
Systemic People Analytics (SPA) means taking almost all the data we have (including employee time tracking, email traffic, organizational network data, and skills) and putting it all in one place, under an integrated metadata-centric system. This means you can find any information you need, sort and filter by any dimension, and drill up and down or go back in time to see trends.
Josh recommends: go out and buy an integrated people analytics platform; development takes too long and is not effective. These new systems, offered primarily by Visier, Charthop, OneModel and CruncHR, are designed from the ground up to do exactly what organizations need for systemic people analytics. These vendors are specialists in HR data integration from many sources, multi-dimensional analysis, and end-user reporting and analysis.
SPA and ESRS
… are closely linked:
- SPA can help measure employee engagement around sustainability and social responsibility. This includes assessing how engaged employees are in ESG goals and practices.
- SPA enables companies to collect and analyze data on diversity and inclusion. This is an important aspect of the “social” component of ESG.
- ESG-focused companies are proven to be more successful at attracting and retaining talent. SPA can help to continuously improve the performance and retention of these talents in such companies.
- Companies must disclose ESG data. SPA helps to collect and analyze this data to make reporting transparent and meaningful.
- SPA can help to identify and mitigate risks related to ESG, such as social conflicts or human rights violations.
- Overall, SPA can help to improve the management and implementation of ESG strategies in companies and integrate social and HR-related aspects into sustainability efforts. This helps to combine long-term economic success and social responsibility.
Concrete practical example: The HR manager of a battery manufacturer was able to use SPA to show her managers in production that their overtime pay, bonus decisions and rewards were completely inconsistent and contradicted the productivity and quality measures in production. By linking manufacturing data directly to HR data, she was able to prove to them that they were mismanaging their teams.
SPA and generative AI
… open up completely new potential:
- GenAI can be used to create personalized training materials or career recommendations based on the results of SPA.
- SPA can identify the requirements for new employees. GenAI can then help create personalized job postings to attract the right candidates.
- SPA can detect early warning signs of employee turnover. GenAI can suggest personalized incentives or measures to increase employee retention.
- GenAI can automate processes for collecting and analyzing employee data, saving time and resources.
- SPA can help identify patterns of diversity and inclusion. GenAI can help shape messages and initiatives to promote these values.
- In times of change in the workplace, GenAI can be used to create personalized communications for employees, while SPA helps to assess the impact on staff.
A concrete example of leveraging this potential is Vee, Visier’s AI-powered conversational intelligence for HR. Vee combines generative AI with the Visier People Platform so that empowered employees can easily ask questions to get systemic analytics information.
Requirements for systemic people analytics
Systemic people analytics platforms access the core of the transactional data itself, making it possible to use statistics and analytics to display, analyze and report on urgent problems as they arise. The crucial basis for this is comprehensive data governance. By maintaining data integrity, data quality, and data availability, organizations can make informed decisions with greater confidence, lead strategic initiatives and ultimately be more successful.
Steven Comingdeer, Head of Global People Analytics and HR Data Governor at Accenture, defines data governance as follows:
- Data governance refers to a set of standards, policies, and best practices that organizations implement to ensure the proper handling, security, and quality of their data.
- In contrast, data management encompasses the activities that support these standards and best practices, such as identifying metadata, establishing data quality controls, reviewing business case requests, creating data architecture documentation, and facilitating change management.
- Data governance and management go hand-in-hand and are equally essential in fostering a repeatable, accessible, and efficient end-to-end data ecosystem
What does successful data governance achieve?
- Data and Metric Standardization: Agreed, centrally-defined descriptions for data elements and metrics.
- Operational Consistency: Equal rigor across all business areas in entering, formatting, and aligning data requirements.
- Reporting Confidence: Decreased risk of drawing skewed conclusions due to poor data quality.
- Data Democracy: Minimize data silos and enable access, quality insights, and analyses for all.
- Data Protection: Confidence in limiting access – especially for sensitive data – only to those who should have it
By focusing on the right investments, a culture of data stewardship, solid processes and engaging the right people, organizations can create an environment where data governance thrives and unlocks the potential of data to create value.
Conclusion
The WHY of people analytics is based, among other things, on making data-based decisions in HR management in order to increase efficiency and productivity while taking relevant personnel risks into account. As we have learned in recent months, this is not enough. All ESG factors must be taken into account. A recently published article by Brian Eastwood, for example, looks at a three-step approach to sustainable productivity.
The HOW of people analytics is well described and well known.
In this article, I have tried to explain the WHAT of people analytics:
- Predictive and prescriptive analytics can help organizations make better-informed and data-driven decisions.
- This requires an integrated, systemic people analytics platform. This provides managers and their analysts with real-time data so that they can identify problems immediately without turning the analysis into a “strategic project”.
- A data governance framework, such as that provided by Alteryx, is required for this platform to realize its potential.
Would you like to find out more and discuss practical examples? Join us in Mannheim!
This insightful article navigates the cutting-edge realm of People Analytics, emphasizing its evolution and future prospects. From predictive analytics foreseeing trends to prescriptive analytics recommending actions, the depth of analysis presented is fantastic.
The synergy between Systemic People Analytics (SPA) and the European Standard for Sustainability Reporting (ESRS) highlights a transformative impact on employee engagement, diversity, and sustainable practices. The integration of generative AI amplifies potential, shaping dynamic HR strategies for workforce management.
Data governance stands as the cornerstone, ensuring data integrity and informed decision-making.
This article offers a deep dive into People Analytics, underlining its crucial role in sustainable productivity and empowering data-driven decisions for a forward-thinking future. Great overview Volker!
Thank you Matt for your valuable comment.
The new reporting standards on the one hand and the technical possibilities on the other hand now make it possible to reach the next stage of development in people analytics.
Together with you and your colleagues at Visier, we have a tool at hand that will help us reach this stage of development as quickly as possible and accelerate the gain in knowledge in companies.