Workforce Analytics 101: How can it help your business?

Mr Siddharth Mehta shares how workforce analytics enables businesses to retain employees, raise profits and refresh branding.

16 Aug 2022 Interviews Performance management Recruitment Best practices Human capital partnership

Mr Siddharth Mehta, Senior Specialist in Strategic Workforce Planning (SWP) & People Analytics at chemical manufacturing company SABIC.

Q: What is workforce analytics (WA)?

Workforce analytics, or people analytics, is the application of data to design and deliver human resource (HR) programmes that lift business value. It is the use of a certain set of methods, frameworks and tools to derive learning from data and apply it to different business domains, be it in marketing or sales.

Q: Do companies have to invest in large-scale software or collect large volumes of data?

Most organisations would already be tracking customer interactions, sales transactions, production volume and operational logistics, and have HR data showing profiles and details of people working at the organisation.

Since such basic data is already being collected by organisations, investing in expensive technology isn’t necessary, contrary to popular belief. Instead, what is needed is a data science mindset, where HR and business leaders can translate their day-to-day work into problems that can be solved through data.

Q: What are the benefits of WA? 

WA allows us to be more deliberate about designing projects to generate insights oriented around enhancing business value. When you do this in the HR domain, you can tweak your programmes and policies to make that connection.

The benefits are better employee experience and therefore greater retention rate and employer branding.

Q: What are some of the challenges of WA?

What HR leaders and businesses struggle with is how to adopt data science skills and mindset. The ability to convert their day-to-day work into problems, in order to find solutions, is a difficult leap for some people to make. This is because there is a huge premium on speed and not so much on being thoughtful or deliberate.

On top of that, many organisations are short-staffed and constrained in terms of how much they can spend on a data science team. If hires are expected to handle multiple things at a quick pace, that doesn’t allow them to do the critical thinking that’s required.

To overcome these challenges, managers and leaders should be more deliberate in focusing on the big three to five problems or decisions that truly matter for business success.

Q: Could you share a case study of a company? In simple terms, how did WA work for the company in lifting business value?

I once worked with a client to optimise HR insights on a software as a service (SaaS) tool to better understand the traits of successful sales performers. To do this, we added more basic HR data to the pool, including the experience of salespeople and their product knowledge and promotion history. 

The key insights gathered were intriguing. Both successful and unsuccessful sales performers were similarly extroverted and spent the same amount of time on customers. But successful ones targeted fewer customers and engaged with their internal stakeholders (such as product managers and account managers) to reach a higher number of prospects (potential customers). The big insight gathered here is that sales competency is not so much about effort, but intelligent effort.

This enabled us to incentivise salespeople on an individual level and create an environment to optimise for this skillset through programmes and policies such as incentives, compensation, and training programmes. The effect of managers was another important realm we looked at. What we found was managers of successful people were extremely rigid about one-on-one time. They didn’t only spend time with less experienced salespeople. Instead, they spent equal amounts of time with experienced and less experienced salespeople.

Q: What are some tips for organisational leaders as they embark on their WA journey?

The first is to identify high-impact opportunities. The hope here is that the insights generated from HR or business value-oriented projects allow you to understand what within your organisation’s unique culture enables success. Once you have that knowledge, then you can create programmes that are customised for your work environment, impacting the outcome that you're after. This makes HR a lot more intelligent, while improving employee experience.

The second is to appreciate the iterated process of generating value through data science. Leaders might not be able to solve a problem because they don’t have enough data or the quality of data is poor, but this understanding itself is an insight. Then they can proceed to improve the data collected.

The third is focusing the outcome on driving change, rather than just generating insight. Unless the insight is acted upon and turned into improved business outcomes, the job hasn’t been done. I call this the last mile.