People Person AND Numbers Fluent

HR exists to help people thrive, and to help the business achieve measurable results. This is not a choice between being a people person or a numbers person. The job is both.

And yet, we often find that HR professionals defer the “numbers” work to the analytics team, and go on being “people persons”. This is not how it should work. People Analytics is everyone’s job in HR.

Why being both matters

• Credibility at the table. Business leaders listen when HR can show the link from a people policy or practice to revenue, profit margin, risk, or customer outcomes.

• Better trade-offs. Hiring, training, rewards, and scheduling compete for capital and time. Quantifying impact lets you fund what works.

• Faster learning. Small tests with clear metrics beat long cycles based on opinion.

• Resilience. Evidence helps you defend decisions when conditions change.

• Career impact. Numbers fluency raises your influence, your scope, and your options for senior roles and board work.

How to get there, personally

• Build a small core, then apply. Basic statistics, which includes distributions, sampling, statistical significance, confidence levels, simple regression and t-tests. These can be done in excel or you can use ChatGPT or other AI models.

• Then move to more complex models. Forecasting basics, including multiple regressions, seasonality, simple time series, Montecarlo simulations and causal drivers like hire rate and tenure mix.

• Add Finance and Accounting basics. P&L, balance sheet, ROI, cost analysis including Activity-Based Costing for, including  true cost per activity.

• Practice on live work. Move one business decision per month from descriptive to predictive. Work with the HRBPs to find out where are the “low hanging fruit”. Once a model works in one area, replicate it elsewhere!

• Write it down. Question, evidence, recommendation, expected impact, review date.

• Pair up. If you have a PA team, link an HRBP with an analyst for up to three months to see what they can come up with, then rotate the HRBP.

• Use ChatGPT well. Generate hypotheses, method plans, Excel formulas or code, draft plain-language summaries. Validate in your BI tool. Use aggregated or synthetic data.

If you lead HR, how to enable it

• Set the standard. In HRLT and EXCO packs, show one decision with the question, the evidence, the action, and the expected effect on a business KPI. Ask directs to do the same in their forums.

• Make time. Protect two hours per week for HRBPs and COEs to do the work, not just review it.

• Give ownership. Name the People Analytics lead as owner of upskilling and productization. Assign an HRLT sponsor to each use case.

• Incentivize adoption. Add a simple KPI, percent of HR decisions with hypothesis, evidence, and recommendation, and the ratio of predictive to descriptive outputs.

• Teach finance, accounting, statistics, visualization and HR Analytics. Short clinics on reading financials and ABC costing, statistical concepts, analytics frameworks, running analytics in excel, creating graphs, storytelling, etc. Ideally, there are action learning projects at the end of each training to apply this knowledge on actual business issues.

Five applied skills, that every HR person should master

1) Frame the business problem through an HR lens

• Learn: Translate a business KPI, revenue growth, service levels, safety, cost to serve, into a people question, skills, staffing, capability, pay, experience.

• Practice this month: Pick one KPI from your business partner’s scorecard. Write a five-sentence brief that states the people levers you can influence and what success looks like in 30 days. Show it to your business partner and your HR boss. Make any adjustments needed and get to work on designing the analysis to help achieve improvements in the business KPI

2) Generate and test multiple hypotheses

• Learn: Good analysis starts wide. List at least three to five plausible drivers. Expect to reject most.

• Practice next month: For the problem you identified above, run a quick test, a holdout check, a simple model, or a controlled pilot. Keep the drivers that explain the outcome and quantify effect size.

3) Interpret data and derive insight

• Learn: Separate signal from noise. Show context, effect sizes, confidence, and risk.

• Practice next month: Once you have the results from the test in the prior step, and write a one-pager, what is the cause of the problem, what are not causes (that we had assumed were but the data says otherwise), what is the insight from the test

4) Turn insights into a clear recommendation

• Learn: Link what we should do next as an HR solution to a business problem, including why it matters, expected impact on business KPIs and people KPIs, timeline, owner, review date. 

• Practice next month: Develop a recommendation for each of the insights you identified in the step before. 

5) Tell the story so others act

• Learn: One message, supporting data, one ask. Plain words. Put the human impact and the business impact side by side.

• Practice in the next 90 days: Present a story to the business partner or senior leadership team that ends with the decision and the expected result.

Apply analytics to how HR works

Use the same discipline on HR’s own operations.

• Recruiting, speed, quality, efficiency, cost. Time to accept, time in stage, quality of hire at 90 days and 12 months, cost per qualified applicant by channel, ABC cost per resolved recruiter ticket. Use this to redesign steps and sourcing mix.

• Learning, ROI. Forecast the effect of modules on defect rates, call handle time, first-contact resolution, or sales conversion. Fund the content that moves those outcomes, retire the rest.

• Rewards, impact. Model how market position, pay mix, and targeted equity affect quota attainment, ramp time, regretted attrition, and DEI representation in critical roles or gender pay equity.

• Engagement and retention, outcomes. Link manager practices to engagement and to sales, NPS, safety, or SLA adherence. Prioritise fixes by business impact.

• Workforce schedules and service levels. Predict understaffing risk by tenure, skill, and demand patterns. Redesign shifts where risk is highest.

• HR service, cost to serve. Use ABC to find true unit costs, then set targets for digital, automation, or policy changes.

The HRBP advantage, bridge business needs and COE practices

HRBPs sit closest to the business problem and their KPIs. COEs control the practices that can move it. Use analytics to close that gap.

• Start from the line KPI. Pick one KPI your business partner owns this quarter.

• Translate to people levers. Skills, staffing, capability, pay, experience.

• Run a quick test. Use data you have, run a forecast or pilot, quantify expected effect.

• Pull the right COE lever. Recruiting channel, training module, job design, pay mix, manager enablement, policy or process change.

• Publish and review. One page, question, evidence, action, impact, review date. Repeat quarterly and expand throughout the organization.

Bottom line

Being a people person and a numbers person is the full job for every HR professional. Master the five skills, frame the business problem, test multiple hypotheses, interpret results, recommend a clear action, and tell the story so others move. As an individual, your influence and career options grow. As a leader, you raise HR’s impact on the business. Start with one decision this quarter, make it visible, and hold the review date. And let me know how it goes!