The HR Metrics I use the most

I’ve been using Excel for 18 years now and in that time, it has probably been my most used piece of Office productivity software. From collecting data to producing graphs and reports. I’m on a journey discovering how to turn data into analytic insights and how data can make predictions.

I mentioned in a previous post about the difference between Metrics and Analytic’s people still get confused! I am sometimes asked about the metrics that I use in a working environment, and I have given some below. Note: this isn’t an exhaustive list!

Pay and benefits

  • Calculating part-time holiday pay
  • Calculating statutory sick pay
  • TOIL – Time Off In Lieu

SMP and SAP

  • Calculating statutory maternity pay
  • Calculating statutory adoption pay

Absence and capability

  • Calculating the frequency of absence
  • Calculating the rate of absence
  • Calculating the cost of absence
  • Calculating the cost of stress-related absence
  • Using Excel as a Bradford factor calculator

Termination

  • Calculating staff turnover
  • Calculating the rate of staff turnover
  • Calculating statutory redundancy pay
  • Calculating enhanced statutory redundancy pay

The differences between Metrics and Analytics

Recently it seems to be getting more common for people to be confused over what exactly HR Metrics and HR Analytics are! Some people seem to use the terms interchangeably, so in this post, I will try and explain the difference and give some examples.

A simple definition is Talent Metrics looks at Tangible Data (Easy to measure, Low Value) whilst Talent  Analytics looks mainly at Intangible Data (Hard to measure, High Value).

Metrics are Informational

Metrics focus on counting, tracking and presenting past data derived from (for example): web visits, the volume of candidate applications, how many (and what kind of) recruitment campaigns were done in a year and other “low value” data gathering.

Metrics give an inside perspective on a business because they use (tangible) data from in-house sources, such as aggregated HR data. Whilst useful it should be remembered that this type of data can only give basic insights (over functional/operational/systemic areas).

Analytics are strategic

In complete contrast, Analytics looks at both past and present data (using both tangible and intangible information) giving powerful insights, optimisations and predictions. Data can be collected by a diverse range of systems and software which can be worked on, and analysed to find data which is transformational and equally high value. Because Analytics use both external and internal sources they give an “outside-in perspective” on a business.

Here are some examples from Metrics and Analytics which should highlight the differences .

Talent Metrics (HR): How many top sales reps left last quarter?

Talent Analytics (Business): Why do my top performing employees keep leaving?

Talent Metrics (HR): What is the average compensation for engineers across the organization?

Talent Analytics (Business): Why are our top software engineers dissatisfied even after we’ve given everyone a department-wide raise?

Talent Metrics (HR): Who is next in line to become our CEO?

Talent Analytics (Business): Will the CEO candidate align or conflict with the rest of the executive team?

Talent Metrics (HR): How many customer service reps do we have?

Talent Analytics (Business): Is our customer service staff optimized to meet this quarter’s customer service improvement goal?

This was originally posted on 5th March 2014 in the Numbers Game blog  http://wp.me/p3MIOJ-s