Analytics have become a crucial area of focus for every functional area, including human resources (HR). By analyzing workforce data, organizations can understand and optimize various aspects of operations, such as recruitment, training, performance management, employee engagement, and retention. Analytics enable HR professionals to identify patterns, predict future needs, and align strategies with organizational goals, leading to improved workforce productivity and competitive advantage.
Understanding the ”“Why” behind the “What” is integral to human capital analytics. Traditionally, when looking to surface root cause explanations for performance, analysts might examine past experiences or use heuristics to explain changes in these rates. They might look at variables like geography or channels because these variables have impacted performance in the past. However, this approach overlooks the potential impact of emerging trends or less frequent variables that were not significant factors in the past. Without a comprehensive analysis, HR professionals are left frustrated and unable to gain the insights they need to improve business outcomes.
Real-World Example: Kingfisher
Bringing analytics insights to HR departments means meeting different stakeholders where they are in their analytics journey. This is precisely the challenge that Iain Reid, head of People Analytics at Kingfisher, set out to solve.
As Iain says, “…across Human Resources, stakeholders that consume our analytics deliverables want to interact with data and analytics in different ways – with varying levels of detail & analysis. Some stakeholders request detailed Excel spreadsheets, while others are simply interested in seeing aggregated metrics and understanding how these metrics are trending over time.” “
For executives, the team performs more complex investigations that require blending HR data with Finance data, for example, to create more holistic views of Kingfisher’s business performance.
The challenge the team faces at Kingfisher is not uncommon for analytics teams across the globe: How do we get our data out to our internal customers in a format they can engage with and understand while also contributing to better decision-making?
“We produce a whole catalog of information. But very often, people want a slightly customized view of something, and we may already have a backlog of three months – so we can’t fit their request into a reasonable period of time.”“ (Iain)
This is familiar territory for most analytics teams – how do you service the business and their needs while also creating efficiency and scale advantages? So often, the customization of reports to add or remove a single metric takes up a disproportionate amount of time for analysts. To solve this problem, Iain incorporated Alteryx Auto Insights into his approach.
“To solve this, we need to be able to react quickly to specific, ad hoc, follow-up questions people have. These are important questions that need to be answered, but given that we don’t have unlimited bandwidth to deliver analytics, these one-off investigations likely do not merit intervention from a central reporting function. We need to empower domain experts to do this themselves.” (Iain)
Moving from what’s happening, to why?
This approach empowers a whole tier of domain experts to use data to drive their decision-making without becoming data experts. But for this approach to succeed, domain experts need a packaged solution they can work with. They need something that is intuitive, easy to use, and easy to explain to others.
Iain and his team can control the data layer using tools like Alteryx Designer, ensuring that high-quality, trusted data is prepared and governed centrally. Once the data is ready, it is loaded into Auto Insights. Auto Insights then acts as the first line of defense for end users; they can interact with relevant data stories that display intuitive narratives and explanations for metrics performance, such as why particular metrics are trending up or down over time.
“With Auto Insights, these folks can do their own self-service and answer their pressing questions at the pace of business.” (Iain)
Looking at attrition rate as an example, Auto Insights helps Kingfisher quickly understand what is impacting the company’s ability to retain employees.
In the past, Iain would provide stakeholders with a dashboard to track attrition rates over time so that they could be up to speed on the latest attrition rate by week, month, quarter, or annual intervals.
However, when his team released an attrition dashboard, the process typically looked like this: The end stakeholder would see the latest attrition rate and immediately ask a follow-up question – “Why has the attrition rate changed since last month?” Understanding the root cause for the change is an anticipated initial question from most domain experts.
“Then, we get variations of this question across the business – for example, why has the attrition rate changed for a specific population of the workforce? Something like this happened recently, where we were able to apply Auto Insights to help solve the problem. We had a noticeable increase in retail attrition one month. When we looked at this metric trending in Auto Insights, it clearly explained that the segment causing the decline was a specific demographic of workers. Auto Insights informed us that the attrition increase was largely due to short-term workers leaving, which we expect in this area of our business. It helped us quickly realize that this was more or less a false flag – and that we shouldn’t dedicate more resources to a deep dive investigation into the matter.” (Iain)
At most companies, analytics backlog queues are constantly overflowing. Analytics investigations are usually prioritized and expedited based on their perceived urgency from leadership. Auto Insights can act as a first line of defense to resolve ad hoc investigations for HR analytics inquiries. Iain’s approach with Auto Insights offers a clear path to resolve analytics inquiries by empowering true self-service that allows users to leave with clear answers rather than more questions.
Auto Insights: Unveiling the Why behind HR Metrics
Auto Insights, powered by advanced analytics and machine learning algorithms, offers a transformative solution to the challenges faced in extracting key insights from human capital analytics. Automating the insight generation process empowers organizations to uncover the underlying reasons for metrics performance – for example, changes in retention and attrition rates – thus enabling more informed decision-making.
Auto Insights makes analytics insights available to all HR employees by bridging the gap between data analysis and decision-makers. It empowers stakeholders to access comprehensive insights about retention and attrition rates, regardless of their technical expertise. With these insights, organizations can make well-informed decisions, proactively addressing factors influencing employee turnover and developing targeted retention strategies.
Auto Insights can revolutionize the way organizations understand and address talent management. Organizations like Kingfisher can unlock the value of their human capital data more quickly and effectively to drive sustainable growth and success by automating the insight generation process.