In most of our articles, we assume that our readers are working at large enterprises. However, we’re getting the question more and more whether people analytics also applies to small and medium enterprises. In this article, we will answer this question.
To answer this question we should first take a look at the building blocks of people analytics and see if they are also relevant for SMEs. Each of the three essential building blocks for people analytics help to manage Human Resources in a better way. These three building blocks are:
- Information Technology
- HR Data
- Statistics and data analytics
How do these apply in the context of smaller companies? Let’s start with the first one, Information Technology (IT).
The application of IT in managing people becomes relevant with the first few employees. At Analytics in HR, we now have a total of 12 employees and we use Google Sheets to keep track of monthly employee costs, sales metrics, and absence days. In addition, we will soon start using software to take care of pension allocations for personnel, and we use Google Calendar to keep track of employee holidays.
When your employee count starts to grow, your systems become increasingly important. Once you start scaling up to 50-100 employees, these systems will have to be professionalized. You cannot keep working in Excel sheets but need to upgrade to professional systems.
The systems you use impact the data you have. Systems keep track of the data that you will use in your analysis. This means that when the systems are well designed the data they produce will be more valuable later on.
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In our case, HR data entry is done on an ad hoc basis. This is a shared responsibility between the employee and management. Faster moving data like sales bonuses and monthly employee expenses are reported and extensively discussed on a monthly basis.
We don’t use elaborate dashboards yet – with the exception of our monthly financial information. We don’t use dashboards yet because with such a small number of employees, there is fairly little HR data to keep track of.
While on the topic of HR data, a problem that smaller and larger companies alike are running into is their inability to combine data. According to Josh Bersin, 2/3 of companies are still at level 1 and 2 of the Talent Analytics Maturity Model. These companies focus their people analytics efforts on getting basic and advanced reporting up.
If the challenges for the SME you work in are similar to this, then starting with people analytics earlier will pay dividend in the future. The more data you have, the harder it will be to get your data in dashboards. In addition, questions like: “which are the key people metrics I should focus on?” are just as relevant for companies with a 100 employees as for companies with 10,000 employees.
So how about data analytics? This is where the added value of people analytics starts to differ significantly between large companies and SMEs. Let me start with two examples of how an understanding of statistics and data analytics helps before turning to the advantage of large companies over SMEs in regards to applying people analytics.
- Absence: An SME company of a friend of mine had an employee who was ill for 11 days within the first half year of employment, in multiple instances from 1 to max 3 days. The big question for us was: Is this more than what’s normal?
In this instance, some knowledge of benchmarks proved useful. A 1.5 to 2% absence is acceptable – an absence rate that is much higher without any clear causes is something to worry about. As an SME, the company didn’t have standardized procedures so this realization was the reason to start paying more attention to this issue.
First of all, they inquired about absence insurance to mitigate the risk of long-term absence. Absence is very costly for the employer in the Netherlands (sometimes requiring him to pay up to 2 years of pay while the employee is ill). Next, the manager had a sit-down with the employer and asked how they could help.In this conversation, the person reported stress due to high expectations and their own perfectionism. By giving the person more autonomy to manage their own workload and by actively helping the person with planning this, productivity actually stayed stable while absence dropped to zero for the following year.
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- Drivers of sales: In this same company, a sales team of two people kept track of the number of emails they receive, send, the number of deals they create in their lead management system, and the average value of sales.
One of the salespeople outperformed the other on a structural basis. What they found when analyzing the data was that there was a relationship between the number of deals created in the system and the number of sales.
This may seem logical. However, because both salespeople got all the leads 50/50, you would expect an equal amount of deals. This was not the case. By creating a deal quicker, one salesperson received more automated reminders to close that lead. These reminders proved to be very effective.
As a result, this person generated more revenue. This was something they wouldn’t have known if they didn’t track and analyzed this data. After learning this, they changed our policy – and as result have been able to close more deals.
These examples show that having an understanding of data analytics and statistics can be very helpful, also in SMEs. However, there are a few specific conditions that are required before data analytics can add real value for these kinds of companies.
- There should be business problems that can be solved using data.
- There should be sufficient data to analyze. Note: this doesn’t mean that you need many employees. You can get data to do people analytics from hundreds of employees – or you can get hundreds of data points for a single employee and add just as much value. This was the case in my second example about sales.
- Although this is not a must, it helps if the organization has the ambition to grow fast and scale up. This kind of organization will have to deal with a growing complexity in systems and challenges in data reporting.
You can get data to do people analytics from hundreds of employees – or you can get hundreds of data points for a single employee and add just as much value
The key benefit for larger companies
Although there are tangible benefits for mid-sized companies, larger companies do have two advantages over their SME counterparts. Two key concepts help in explaining this value.
- Economies of scale: This concept refers to a lower cost-per-unit when output is produced at a larger scale (efficiency through volume). Applied to people analytics, this means that a people analytics practitioner will be cheaper when an organization employs more employees because one analyst can analyze many more employees – and results can be implemented at a much larger scale. The cost of people analytics per employee is thus lower while the value is higher.
- Economies of scope: This concept involves a lower average cost by producing multiple types of products. In analytics, you see this when an analytics department analyzes marketing data, financial data, and people data. Offering these services simultaneously in one center of excellence leads to higher efficiency. Although not yet common practice, this is much easier to achieve in larger organizations compared to SMEs.
So, larger organizations can achieve efficiency through volume or variety. This explains also why people analytics was first adopted in large companies.
So does people analytics add value to SMEs? It offers more value to larger companies – but can still add tremendous value for smaller companies as well.
In the end, it all depends on what the company tries to achieve – and what you are looking for in your own career. I have been able to help smaller companies like the one in my example make better decisions just by being able to understand data and knowing how to analyze it. My people analytics knowledge has also helped me in my role within Analytics in HR on multiple instances already. Is it a full-time occupation for me? Absolutely not. Does it add value? Without a doubt.
Mastering people metrics, aggregating relevant data, and reporting on it to create insight is just as essential in SMEs as it is in large companies. However, in smaller companies this usually won’t be a full-time function.
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