It has been a while since we shared our thoughts and best practices on people analytics. Over the years, we talked about employee experience (1), continuous employee listening (2), the second wall of HR (3), the 10 golden rules of HR analytics (4), and the HR analytics skillset (5). Today we want to share our 8 big tickets related to people analytics for our organization for the upcoming year. By no means do we want to suggest that our big tickets are the only important ones. For every organization, this will differ based on context. We do hope, however, that you enjoy and appreciate us sharing our views.
Before discussing the 8 big tickets for people analytics, we want to thank thought leaders, peers, academics, and vendors who continuously challenge and inspire us to shape our way forward. In itself, it could be a ninth big ticket: Ensuring you stay connected and learn and grow from all the people analytics experts that are out there. Special thanks to Insight222 for curating people analytics content and bringing together people analytics leaders from all over the world and the Deloitte iNostix team for being there from the beginning. Both organizations inspired us and ensured we continued innovating our people analytics practice.
1 – Analytics for personalization
In the next year or two, all our HR and enterprise data will be brought together in one global environment and integrated with our analytical platforms. Combining a more integrated IT and data landscape and our analytical capabilities offer us the opportunity to serve our employees more directly, more personally, and at scale. Insights from our machine learning models can nudge or advise our employees on career-related topics and enhance their employee experience. We can provide employees with custom-made suggestions for vacancies or learning interventions based on their skills or provide managers with tips on how to increase team engagement. These machine learning-based services offer the opportunity to add functionality to our HR IT landscape in a more modular and flexible way without investing in new software packages. Needless to say, our people analytics and HR IT teams are working closely together on this.
The personalized analytical services we provide need to benefit our employees
As always, we set high privacy and ethical standards when we conduct people analytics research. And there is, of course, no exception when providing personalized analytics to our employees. We are rewriting the privacy statement to ensure full transparency to our employees. We will also publish an ethical framework together with our privacy office and legal soon on when personalized analytics is allowed.
One important rule we apply is that the personalized analytical services we provide need to benefit our employees. Machine-learning-based services, as mentioned above, should help our employees to experience better and more efficient support during their careers. Furthermore, our personalized services should not exclude employees in HR services or limit their options. The concept is no different from how we manage our personal lives via nudges and recommendations via our mobile devices. We expect to deliver more of these employee-centric personalized analytical services in the years to come.
2 – Analytics for Skills
Skills is a rapidly growing theme within HR all over the world. More organizations move away from their traditional job classification system that contains task-oriented job descriptions towards a more generic framework that focuses on people’s skills, behavior, and abilities. This transition is also happening within our organization.
Based on a skill engine, we are able to see where specific skills are over- or underrepresented in our organization
We get more and more research questions in which we want to use the skills data of our employees. Currently, we know the skills of our employees only to a certain extent. We have different assessment tooling in place, where people can measure their skills. These data are well structured and of great detail. But this data doesn’t cover all employees, and it is also not up to date for many employees. This resulted in our aim to build our own skill engine via machine learning, to a certain extent based on external systems (e.g., EMSI). Based on this skill engine, we will define the skills of our employees automatically.
Our priority is on two use-cases. First, a dashboard where we can track and trace our organization’s aggregated skills provides valuable information on which skills are over- or underrepresented in a specific part of the organization. Second, as mentioned earlier, a vacancy recommendation model, based on skills, to nudge employees to look at our internal vacancies. We have our proof of concept ready and will put it in production at the beginning of next year.
3 – Analytics for Value
Whatever we do in HR, we do it to provide business value. The starting point in everything we do is to understand how we create business value. Articulating the business value is, of course, nothing new. Still, we developed a business value workshop that helps us define the exact business value in a more efficient and fun way.
The idea is simple but very effective. During these workshops, we sit down with those involved in one specific HR service (e.g., recruitment or succession management). We first look at the core of the HR product: can you mention your activities and deliverables? Can you elaborate on your specific responsibilities? Secondly, we look at various types of clients (e.g., hiring manager, employee, external clients, business manager, Business MT, society, compliance department, et cetera) and select the most important ones. Thirdly, we discuss what the main strategic KPIs should be for the just selected clients.
At the end of the workshop, we check whether the described product (step 1) still matches the KPIs (step 3) for each client (step 2). The result of this workshop is an overview of our activities and how they logically are linked to our business values, including identified gaps
Based on the first few workshops, we recently built a dashboard for HR with all main KPIs. This dashboard is available for everyone within HR and shows where we do or don’t meet our targets. In 2022 we will finalize this dashboard and use it in conversations with our colleagues when we talk about priorities, focus, and capacity.
4 – Analytics for Insights
Since March of this year, our HR analytics department is also responsible for all HR dashboards in our organization. For many HR analytics departments, this has been the case from the beginning. However, we decided seven years ago to deliberately split the responsibility for management information and building dashboards from the responsibility for advanced people analytics. In our case, this allowed us to have a steep learning curve in advanced analytics in the first years. From an internal client perspective and data management perspective, it makes sense today to integrate the two in one department.
We create all our dashboards in Power BI. Currently, we offer dashboards on topics like employee experience, diversity, workforce, talent acquisition, and mandatory learning. Some of these dashboards have different versions. A public version is open to all employees within our organization, where an expert version of the same dashboard is available for a group of specialists, containing more data features. In some cases, we automatically generate ready-to-use management team PowerPoint presentations directly from Power BI or other datasets via Python.
One of the most important guiding principles in creating dashboards is ensuring the client will use the insights in decision-making and action-taking. This is why we put much effort in the intake phase on articulating how our clients use the insights once they are available. After the dashboards are delivered, we periodically discuss the usage, possible issues, and new needs with the dashboard owners.
Dashboards and their insights need to drive concrete decisions and trigger specific actions
The next steps in our dashboard services are a further investment in usability and visualization and user support in the form of introduction movies for the more essential dashboards. Two new dashboards are on our backlog: a manager dashboard where a manager finds all his team data integrated. This dashboard will include benchmarks, e.g., diversity ratios, that should trigger managers in their way of working. The second dashboard is related to organizational design and includes ratios and forecasts.
5 – Analytics for Experience
More and more organizations are developing the capability to listen to their employees using surveys and analytics. It is essential to continuously listen to our employees’ thoughts, ideas, and problems and learn from them to enhance employee experience. Some organizations started or accelerated their efforts in employee listening because of covid and hybrid working. Organizations that already had a continuous employee listening framework before covid were immediately equipped to learn and act based on the employees’ voice. Covid and hybrid working proved the value for continuous listening and checking the experiences of your employees instantly.
Let’s shortly recap our framework. It is pretty simple. (1) Start listening to your employees by using survey data and transactional data, (2) love the problem, by putting effort into understanding what your employees are telling you via deep dives and extra data analytics, and finally (3) try a solution and take action. We repeat these steps per quarter. In that way, we can evaluate if our actions are effective and if the employee experience increases. We repeat all steps periodically and share them with employees, experts, and business management teams.
We use open questions in our employee experience survey. We classify employee answers with sophisticated topic detection into tips (suggestions and complaints) and tops (satisfaction). I refer to our previous posts, ‘Visualizing the voice of the employee’, for more technical details on how we perform topic detection. The results are captured in the employee experience dashboard, open to all employees. This specific case is also included in the recently published book by Jonathan Ferrar and David Green, ‘Excellence in People Analytics’.
Although our current approach gives excellent insights into what our employees think and feel, we don’t know if the most frequently mentioned topics are also the main drivers for employee experience. That is why we developed a first model (XGBoost), using multiple data sources of which employee experience, to find those topics that really impact employee experience. The first results are promising, and we will continue to optimize the model in the next half year. We will link the employee experience drivers to other business goals in a separate model, such as client satisfaction, sales, or retention.
6 – Analytics for Organizational Design
An emerging topic for our organization is organizational design. We are currently developing the organizational design product within our HR analytics team. So it will be a big ticket for the next year, but we are just at the beginning, in all honesty. We do have a strategic workforce management practice, which is, in our opinion, strongly related to organizational design. Thinking about organizational design conceptually, we like to separate macro design from micro design. With macro design, we mean understanding the business strategy and models and translating them to the most critical organizational capabilities the business or business unit should excel in. This is a vital step but often not executed in enough detail. Identifying the organizational capabilities your organization needs to be good at is the basis for defining workforce interventions
Identifying the organizational capabilities your organization needs to be good at, is the basis for defining workforce interventions
Micro design is about providing organizational design information, forecasting, and scenario planning. Via Power BI dashboards, we can start sharing organizational design ratios like span of control, way of working, organizational layers, etc. With more sophisticated tools, we can advise the business by forecasting FTE and headcount or present organizational design scenarios. In the end, as an HR analytics team is used to do, we can evaluate the organizational design choices or interventions we made on its effectiveness.
7 – Analytics for Evaluation
Traditionally, our department investigates the impact of HR activities on specific business goals. These types of projects continue to be an essential big part of our portfolio. The outcomes tell us if our HR interventions are effective or not. And they provide information on what to change in our interventions to become even more effective. These projects are very impactful because they clarify the underlying business case of the HR intervention investment.
A few examples of projects we executed last year:
- What is the impact of one on one skill coaching on sales within our Retail Bank? We see that employees sell more mortgages and more insurance after going through a skill coaching process.
- Which type of training affects our employees’ commitment to help our customers in their transition to sustainability? Especially the more job-specific training courses contribute to raising awareness.
- Women deserve equal pay for equal work, but are they getting it? The analysis shows that at ABN AMRO, men and women in the same pay scale receive equal pay. They also are given equal promotion opportunities (link)
We prioritize our projects based on the strategic pillars of our organization: reinvent to customer experience, support our customers’ transition to sustainability and build a future proof bank (in which Employee Experience is one of the focus areas).
8 – Analytics for Evidence-based Culture
We often hear from other organizations that they do not have an evidence-based or fact-based culture in their HR function. And sure, an existing evidence-based culture makes the implementation of people analytics easier. But we argue that by implementing a people analytics function, you will create or improve the evidence-based culture within your HR organization. So please do not wait for a perfect culture before starting with people analytics. You can influence it and steer it.
We have to stay alert when it comes to our evidence-based culture within human resources.
We try to teach and preach analytics in various ways. Of course, on the job, or more accurately, within the project, we find time to talk to our clients and educate them where needed. We also tap into our enterprise-wide data analytics offering, available via our learning platform to all employees. On top of that, we specifically designed workshops with interactive cases at the beginning of our journey, and we implemented a fact-based escape room to teach critical thinking when working with data. The company Fresh Forces created a white label version of this escape room available to other organizations. Improving or maintaining this data-driven culture needs continuous attention.
Besides these capability-building examples, we have quarterly sessions with our HR process owners and HR business representatives. We discuss our analytical services and how they use and experience them, what we have done in related business units and which insights they need. Like you can imagine, these discussions will also help them work in a more data-driven way, which in his turn influences our evidence-based culture.
We have to stay alert when it comes to our evidence-based culture within human resources. People leave and join the organization, so culture needs our constant attention, also in 2022.
Some final words
We hope you enjoyed reading our thoughts and appreciate us sharing what is important for our organization related to people analytics. Again, based on context, you might have different priorities in your organization. Thanks to our team, who are doing the actual work. And let us wait and see at the end of next year what we achieved. Feel free to contact us directly via LinkedIn if you want to hear more.