Some amazing articles were written last month. We searched the web and compiled a list of the five most shared HR analytics articles of June. It includes some great reads for you to enjoy!
5. HR Should Understand the Risk and Rewards of Using Data Analytics
In this article, Dr. Zen Eigen explains the role of data-science in HR. “Data and data-science are really the best way to gather data and analyze data to improve decision making across domains”.
Eigen, who works at Littler Mendelson, a U.S.-based law firm, continues to explore the legal constraints of data-science in people analytics. Check the full interview below!
4. Three critical measurement problems in People Analytics
Keith McNulty global director of people analytics and measurement at McKinsey, writes about measurement problems in people analytics.
Whenever we compare data, we want to deal with the same data every time. Yet, measurement in people analytics often goes wrong in terms of:
- Data discrimination;
These problems cause different statistical and interpretation challenges. An example Keith gives is job performance: When most people score at the 90% mark it will be hard to relate recruitment or engagement practices to performance. Because everyone performs well it is impossible to discriminate between the good and the bad apples.
The second element is connection. Team effectiveness, satisfaction, retention, but also engagement relates to connection. Yet connection is hardly ever effectively measured.
The take-home lesson from Keith’s article is that we should spend more time on the psychometrics in HR analytics. I think he makes a good point. Everything we do with data boils down to validity and reliability.
Validity, and in particular construct validity, is about: Do we actually measure what we want to measure, or do we think we measure one thing but measure something else instead?
Reliability is about getting the same outcomes when we measure the same thing a second time. If we get a wildly different outcome, reliability is low. We should not underestimate the importance of practical applications with regards to psychometrics in people analytics.
You can read the article here.
3. The perfect match, HR analytics and strategy
In his article, Patrick Coolen writes about the importance of looking for things that are of strategic value to the company. Everyone should remember that statistics, data mining and strategic workforce planning are a means to an end. That end is building strategic capabilities for the organization.
After starting off on this important note, Patrick continues to describe how people practices at ABN AMRO have taken shape. Techniques, tools and capabilities have evolved and so have the internal product offering and the positioning of the HR analytics department.
This department has developed into a strategic department, providing answers to questions concerning HR strategy. I think this is a perfect example of analytics done right.
Patrick continues to describe current analytical capabilities and concludes that by leveraging agile analytics an organization can build a business HR strategy. How? Check Patrick’s article here.
2. Analytics on HR analytics: What Really Works
We often talk about analytics but does it even work? In this month’s number 2 Dave Ulrich performs analytics on analytics.
Ulrich and research fellows collected information on 123 competencies of 4,000 HR professionals in 1,200 businesses. This information was then compared to three outcome variables:
- Personal effectiveness
- Stakeholder value
- Business performance
I will just quote the results for you:
- In predicting individual effectiveness, analytics is the 6th (out of nine) most relevant competence (explaining 8.2% of overall individual effectiveness).
- Likewise, knowing analytics has relatively low impact on stakeholders, including customers (10%), investors (11.4%), communities (7.6%), regulators (12.8%), line managers (8.4%), and employees (negative 6.8%).
- In delivering business value, analytics is the 7th most important competence (8.8%).
To read more about the implications of these findings, check Ulrich’s article here.
1. HR Must Make People Analytics More User-Friendly
This month’s most shared article was written by John Boudreau. He argues that progress in HR analytics has been glacially slow.
Despite the sluggish start, executives have high expectations when it comes to HR analytics. 15% of executives said to use predictive analytics based on HR data. 48% predicted to do so within the next two years! Unfortunately, only 5% of big data investments are in HR…
The question remains what HR can do to advance analytics progress. According to Boudreau and Cascio, HR should push using the LAMP framework.
- Logic: articulate the connection between talent and strategic success.
- Analytics: use the appropriate tools to transform data into insights. This coincidentally integrates nicely with Patrick’s article.
- Measure: create accurate and verified numbers and metrics. This integrates nicely with Keith’s article.
- Process: use the right channels to motivate decision makers to act on data insights.
HR departments that use all of the LAMP elements play a stronger strategic role in their organizations. Balancing these four push factors creates a higher probability that HR’s analytic messaging will reach the right decision makers.
Read the full article to find out more about the implications of the LAMP framework and how HR can advance analytics even further.
Do you want to learn more about analytics? Read the top trending articles of May here.