Almost a third employees quit before reaching six months on the job. The financial impact is equally severe, with research showing that replacing an employee can cost between 50% and 200% of their annual salary. These early exits represent lost recruiting spend, wasted onboarding time, and disruption to teams that were just starting to gel.
But what stops HR leaders from spotting turnover signals early and salvage them?
In a recent webinar, SplashBI CMO Marc Ramos summed it up: “Data and data everywhere.” HR leaders are swimming in reports from payroll, ATS, learning systems, and compliance tools. Yet, thanks to the complexity in reading data signals, early warning signs of turnover often get lost in the noise. Click here to watch the full webinar on demand.
By the time resignations appear, the damage has already been done. The challenge is clear: HR needs to see the signals sooner, and act before it’s too late.
Why HR Data Feels Like a Puzzle with Missing Pieces
“You have HR and people data everywhere… payroll, ATS, even legacy systems. The trick is visibility across all this complexity,” said Marc Ramos. His point captures the reality for most organizations: there is no shortage of HR data, but making sense of it is another story.
Ragu Veeraraghavan, SplashBI VP of Analytics, added his perspective: “One of the toughest asks is effective HR analytics… So many different systems, trying to get them in one place is a challenge.”
Unlike finance or sales, which often operate with fewer, more consolidated systems, HR touches nearly every part of the employee lifecycle. Core HR, recruiting, payroll, learning, compliance, and performance each live in their own silos.
The result is a reporting environment that resembles a half-finished jigsaw puzzle. You can see some pieces – turnover stats, course completions, recruiting metrics – but the picture is incomplete. Without the missing connections, early turnover warning signs stay hidden until employees hand in their notice.
The opportunity lies in connecting those puzzle pieces quickly and well in time. Unified visibility turns scattered reports into a coherent view of risk. With the right integration, HR teams can move from asking, “Why did people leave?” to “Who might be at risk of leaving, and what can we do about it now?”
Where Early Turnover Signals Hide
Spotting early turnover risk is not about waiting for resignation letters. The signals are already present in the data most HR teams collect every day. The challenge, as Ragu highlighted throughout the session, is knowing where to look and how to connect the dots.
1. Learning Data: Registration vs Completion
Ragu explained: “You want to know how many people registered, how many started, how many completed. And you can drill into who started but not completed.” When a large group of new hires enrolls in mandatory courses but never completes them, it is a clear red flag.
Stalled completions often point to disengagement, confusion about expectations, or lack of manager support. These are the kinds of issues that can turn into early exits if they are not addressed.
2. Engagement Insights: Which Training Works
Not all courses are created equal. Ragu emphasized: “Which training is engaging? Which is least engaging? You can see completion rates correlate with engagement.” If completion rates are low in compliance training, it may signal fatigue or resistance.
If onboarding courses show weak completion, it could mean the content is outdated or irrelevant. Knowing which programs energize employees and which ones lose them provides a direct window into potential turnover risks.
3. Timing Patterns: When People Avoid Training
Completion trends also reveal important signals. As Ragu pointed out: “Looks like Saturdays and Sundays aren’t great unless this company works 24×7.” If employees consistently delay or skip training at certain times, it can point to lack of motivation or competing priorities.
Timing data helps HR spot disengagement trends early and adjust training schedules or follow-up accordingly.
4. Churn Dashboards: Spikes That Tell a Story
Beyond learning, churn dashboards give HR a timeline view of risk. Ragu noted an instance: “October 2024 was when most of the churn happened.” Spikes like this rarely occur at random. They often align with workload cycles, compensation events, or leadership changes.
By tracking turnover as a timeline instead of a single annual figure, HR can identify hotspots and prepare interventions before the next spike arrives.
5. Recruiting Funnel: Where Candidates Drop Off
Recruitment data provides another set of signals. Ragu explained: “You can see between interview and assessment how many dropped off. That funnel tells you where candidates are getting stuck.”
High drop-offs at specific stages highlight mismatches in expectations, role clarity, or assessment design. Even when candidates are eventually hired, those early frictions can sour the experience and carry into their first months on the job. Early mismatches in recruiting often cascade into early turnover later.
Each of these areas – learning, engagement, timing, churn, and recruiting – contains valuable clues. On their own, they may look like isolated data points. Together, they form a story of how employees are experiencing the organization. The sooner HR teams connect those pieces, the better chance they have of predicting and preventing early exits.
How Clear Insight and Definitions Drive Better Decisions
One of the simplest but most powerful features Ragu highlighted was the use of embedded tooltips in dashboards. “Hover over early turnover and it points out anyone who leaves within the first six months. Why it’s important: you lose your recruitment effort and training investment.”
This clarity may sound fundamental, but it is often what separates numbers that sit on a report from insights that actually shape decisions. When HR leaders, line managers, or executives see a metric, they should not have to guess what it means or why it matters. SplashBI’s approach builds that context directly into the dashboard, ensuring that such insights are consistent and accessible.
By explaining both the calculation and the business impact, these cues transform data into a shared language. That shared understanding is what allows organizations to act quickly and confidently on early turnover risks.
The Next Frontier: Using AI to Predict and Prevent Early Turnover
Looking ahead, Ragu pointed to the role of artificial intelligence in making early turnover insights even more actionable. “We can use AI to tie learning with turnover and productivity. That’s definitely coming.”
The idea is not just to look at dashboards but to surface relationships between data points that humans may overlook. For example, AI can highlight that employees who fail to complete onboarding courses within 30 days are three times more likely to resign within six months, or that specific managers with high spans of control also see elevated early churn.
Conversational AI – SplashAI, SplashBI’s conversational assistant, specifically – takes this a step further by making these insights accessible on demand. Instead of filtering through dashboards, an HR leader could simply ask, “Which departments are showing early turnover risk this quarter?” and receive an answer in natural language, backed by data.
This evolution makes analytics proactive rather than reactive. HR teams will not only spot risk signals earlier but also receive AI-driven prompts about where to intervene. By connecting learning, performance, and turnover data through AI, organizations can transform scattered information into a predictive model that helps prevent costly early exits before they occur.
Conclusion: From Chore to Early Warning System
Early turnover is not inevitable. The signals are present long before employees decide to leave, and the right reporting approach can make them visible. As Marc Ramos put it, “Let’s arm not only HR but your managers with the insights they need so they can go about their day productively.” When leaders and managers are equipped with clear, timely insights, they can take action before disengagement turns into attrition.
What once felt like a chore – pulling spreadsheets, reconciling metrics, chasing reports -becomes an early warning system that helps protect retention and strengthen employee experience. The move from reactive reporting to proactive insights is already happening, and SplashBI users are proving how powerful it can be.
