I had the incredible opportunity to be part of an enlightening panel discussion hosted by the amazing Minola Jac . The Hacking HR panel topic was “Connecting the Dots Between Data Analytics and People Strategy: Designing Data-Informed HR Strategy and Operations.” A big thank you to Minola for moderating and to my fellow panelists Heather McBride-Morse, Andreas Kyprianou , Trent Cotton , and Michael Atilano for their invaluable insights. 🙏
Some of the main questions discussed in the panel included:
– What made each panelist fall in love with people analytics?
– What kinds of quantitative and qualitative data are needed for data-informed HR strategies, and how can these be married?
– How can data integrity and accuracy be improved to build data-informed people strategies?
– How can meaningful data analytics be brought into HR strategy when working as an HR team of one?
– Where should someone start if they want to design the best data-informed strategy for HR?
🔍 Main Takeaways
The overarching theme was the power of data in making informed decisions in HR, moving beyond gut feelings and intuition.
🔍 What made each panelist fall in love with people analytics?
– Heather McBride said what made her fall in love with people analytics was how it helps make things more applicable to the business by backing things up with data. Her first exposure was during her Six Sigma certification.
– Andreas Kyprianou said he fell into people analytics when working at an early startup. He saw the power of using data to stop relying on gut decisions and how people reacted better when things were backed up with numbers.
– Trent Cotton said he came from a line of business background so was more accustomed to numbers than touchy-feely stuff. He likes using data to see what insights it provides rather than coming in with preconceived hypotheses.
🔍 What kinds of quantitative and qualitative data are needed for data-informed HR strategies, and how can these be married?
The panel discussed that both quantitative and qualitative data are needed to provide a full picture for data-informed HR strategies.
Quantitative data can be used to understand what has happened in the past, identify trends, and measure factors that contributed to outcomes. However, qualitative data is needed to understand why things are happening and gain insights into potential solutions.
Michael Atilano provided an example of how he used turnover rate data (quantitative) to identify an issue in one division, but then used employee feedback (qualitative) to understand what specifically needed to be addressed through coaching. Bringing both data types together allowed them to create an effective strategy and then scale it across other divisions.
The key is using quantitative data to identify issues and trends, while qualitative data provides the necessary context and a human element to help determine the best path forward. A combination of both is required to truly understand an issue and develop an informed strategy.
How can data integrity and accuracy be improved to build data-informed people strategies?
The panel discussed several ways to improve data integrity and accuracy to build data-informed people strategies:
– Audit existing data sources to identify and address issues through cleaning and validation.
– Ensure clear and consistent definitions are used when collecting data to avoid inconsistencies.
– Involve HR in implementing any systems used to house HR data to ensure it is structured properly for analytics needs.
– Establish guidelines around ongoing data governance to maintain integrity as collection grows.
– Leverage data quality tools to help identify and address errors.
– Be transparent about known data issues or risks rather than pretending data is perfect.
– Validate conclusions drawn from data by supplementing with qualitative sources like conversations.
– Address root causes like system ownership and implementation that can undermine quality.
Starting with high confidence metrics like demographics can also help when data maturity is low. Continuous improvement is important as well.
How can meaningful data analytics be brought into HR strategy when working as an HR team of one?
When working as an HR team of one, the panel recommended:
– Focus on understanding business priorities and goals to identify the most relevant metrics to analyze
– Partner with others in the organization who have analytical skills, such as finance, to help obtain and interpret data
– Leverage available tools in the HRIS system that already have some built-in data sources
– Start small by addressing clear problems and using metrics you can reliably track, rather than trying to analyze everything at once
– Seek help from external communities of HR professionals who can provide templates, examples, and advice from their own experiences as solo practitioners
Where should someone start if they want to design the best data-informed strategy for HR?
The panel provided some recommendations on where to start if you want to design the best data-informed HR strategy:
– Understand the interests and problems/questions that fascinate senior leadership to identify strategic focus areas
– Start with high-impact but low-complexity projects to get quick wins, rather than taking on complex problems initially
– Define clear problems to solve rather than just presenting descriptive data
– Involve all relevant stakeholders through a design thinking process from the beginning
– Focus on identifying problems clearly and bringing potential solutions, rather than relying solely on data
– Build skills in both operating/technical aspects and consulting/storytelling to identify insights
– Ask leaders and subject matter experts for their input and perspectives on solutions
Panel Summary:
The panel discussed best practices for using data analytics to inform strategic HR decision-making. Key topics included the types of quantitative and qualitative data needed, improving data quality, and leveraging analytics as a solo HR practitioner.
The panelists emphasized starting small by focusing on high-impact but low-complexity projects. This allows practitioners to get quick wins that demonstrate value. They should also partner with others who have complementary skills in business, finance, or technical analysis.
Presenting data in a way that is easily consumable and relevant to the business was highlighted. Practitioners should identify clear problems to solve rather than just presenting descriptive data. Both quantitative and qualitative sources are important to fully understand issues.
Continuous improvement of data governance and integrity was advised. Practitioners should validate conclusions, be transparent about limitations, and address root causes impacting quality. Leveraging external resources and seeking help from experienced peers was also recommended.
Key Recommendations:
– Start with well-defined, high-impact projects that can deliver fast results
– Partner with others who have skills you lack in business, finance, or analytics
– Make data presentations clear, concise, and relevant to the intended audience
– Use a combination of quantitative and qualitative sources
– Continuously improve data quality through governance and issue identification
– Leverage outside resources, communities, and subject matter experts for support
👏 A huge thank you to everyone involved. Your insights have not only enriched me but also everyone who tuned in. Here’s to more data-informed decisions in HR!
🔗 #DataInformedHR #PeopleAnalytics #HRStrategy #Kyndryl #BusinessIntelligence #DataAnalytics #HRIS #KPIs #DesignThinking
Let’s keep the conversation going! 🌱