Before starting with analytics, it is important to know where you are now. Research by Bersin (2016) found that 92% of companies believe they are not optimally organized for success. It’s likely that your organization is part of this majority. Despite (or maybe because of) this, organizations are showing tremendous growth in their people analytics capabilities. This chapter digs deeper into how you can identify where your organization stands and what you need to do to develop full predictive capabilities.
The number of organizations that use people data to predict performance grew by 125% last year. In 2016, 8% of organizations have used analytics to predict performance thus far (IBM, 2016). Most organizations have not achieved this grade of analytics. Bersin named these different grades ‘talent analytics maturity levels’. Most (if not all) maturity models created over time by different companies are based on this model. According to this model, companies can be grouped in four different levels.
At the time of writing this article (late 2016), the majority of companies were at level 1 and 2. These organizations primarily focus on operational reporting. Metrics such as headcount, attrition, cost of labor, absenteeism, and attrition are also reported. However, not much is done with this information.
This kind of reporting is part of day-to-day business, and keeping the reporting up to date is usually time-consuming.
There is a high hygiene factor associated with this type of reporting. Hygiene is something that’s assumed to be present; when someone has good hygiene it goes unnoticed, but if someone has bad hygiene, people will surely notice. The same goes for HR data: you won’t get recognition when the data is up-to-date, but when it’s not, you will have a problem. Data-driven decision making is hard for these organizations. Data is often separated into different systems, so combining data to analyze it presents a number of challenges. This is the point where HR hits the wall of Boudreau, which we discussed in the previous chapter.
In level 3 and 4, HR adds increasing value to the business and to strategic decision-making. For example, organizations at the level 4 are able to predict the impact of policy changes based on the data they’ve collected. This means that HR has all the knowledge and skills to become truly strategic. Furthermore, they have the numbers to back up what they are saying. Organizations at level 4 apply predictive analytics to their workforce. They take their employees very seriously and use them strategically in order to create a competitive advantage.
A slightly different approach taken by some companies involves partnering up with existing analytics providers who then take over part of the company’s analytics portfolio. The best-known example is ABN AMRO and iNostix. This means that the organization can start with analytics without having to organize a data warehouse or doing the data analytics themselves. They skip a few levels in the model by hiring external expertise. This approach enables the organization to make data-driven people decisions while internally developing their own data analytical capabilities. It also helps the company to more quickly develop these capabilities, which can be categorized in the different levels we have previously discussed.
Using the self-audit below, you can identify the maturity level of your organization.
Strongly disagree: 0 points
Disagree: 1 point
Agree: 2 points
Strongly agree: 3 points
Add your points. Your total provides an estimation of your organization’s analytics maturity level.
0-5 points: Level 1
6-11 points: Level 2
12-18 points: level 3
19+ points: level 4
Skip to your relevant level to read more.
At level 1, HR mostly sticks to operational reporting. 56% of all organizations are at HR analytics maturity level 1.
The HR department seems to be stuck in ‘traditional’ operational reporting. This means that they report traditional metrics such as headcount, attrition, labor cost and training cost. These operational reports are usually generated with the use of a Human Resources Information System (HRIS). As was mentioned before, this kind of reporting is part of day-to-day business and has a high hygiene factor.
How to reach level 2
Level 2 is all about advanced reporting. HR departments at level 2 proactively create relevant reports to support (strategic) decision-making. They apply benchmarks to HR data to make reports more meaningful. Additionally, metrics are reported multidimensionally, then delivered to management and executives in clear dashboards.
Most organizations at level 1 already use a dedicated HRIS to keep accurate and consistent employee records. If your organization does not use such a system yet, you would do well to adopt it in order to work your way up to level 2. A proper HRIS allows organizations to maintain reliable and consistent data on their employees. This system constitutes a crucial step before beginning with HR Analytics. By using an HRIS, generating reports will become less time-consuming so HR can spend more time on becoming more strategic and working its way to the next level. Moreover, it makes the analysis more reliable. It is not uncommon for level 1 organizations to discuss the data’s validity, instead of talking about what the people data shows.
HR departments at level 2 are capable of operational and advanced reporting of HR metrics. Around 30% of organizations are at this level while only another 14% of organizations are at a higher level.
At this stage, your organization is able to report proactively. This proactive reporting provides multiple perspectives and is sufficiently advanced to influence (strategic) decision-making. HR reports are descriptive and focused on efficiency. In this case, reporting is part of day-to-day business and still has a high hygiene factor.
In level 2 you should be careful not to invest too much time in generating new HR metrics. Instead, focus on the metrics that offer real strategic value to the organization’s main business challenges.
Most organizations at level 2 deliver HR metrics to managers and executives in organized dashboards. It is more important to show relevant information than to show all information. Clear dashboards facilitate the translation of HR metrics into useful input for decision-making.
How to reach level 3
Going from level 2 to level 3 primarily deals with the transition from reporting to HR analytics. Analytics is about statistically analyzing HR data in order to develop relevant (predictive) models for better decision-making. In other words, it begs the question: What can we learn from our HR data to make better people decisions in the (near) future?
When applying HR analytics, it is very important to start with a business problem of relevance to the organization. This way time is spent on solving real problems. Hence, remedying these problems will have the greatest impact on the organization.
Applying people analytics will require you to combine different kinds of data. You will need HR data, like demographics, performance and hiring data, but also financial and operational data, from different systems. It is therefore important to have a centralized HR (analytics) department and at least some level of data integration of the various systems. Organizations typically use a business intelligence (BI) system to compound data from multiple systems, or to build up a database of relevant data that can easily be used for analysis.
After putting together all the necessary data, you can start answering questions through statistical analysis. Managers and executives are typically short on time so there is no point in showing them complicated statistical models. To ensure strategic impact, be certain to focus on key business issues and to translate all results into actionable solutions.
At level 3, you are part of the top 14%. Only 4% of organizations have a higher HR analytics maturity level. Your organization has surpassed operational and proactive reporting and has succeeded in introducing more advanced analytics! On top of that, your organization uses (statistical) modeling to solve business problems and, based on the data, is even able to predict the future!
As an HR professional working with HR analytics at maturity level 3, you can add tangible value to the organization by proactively identifying issues and recommending actionable solutions.
How to reach level 4
Level 4 is characterized by predictive analytics. Predictive analytics enables organizations to make even better decisions by showing their potential impact. In addition, it will be possible to engage in scenario planning by forecasting what is likely to happen in the future. This allows organizations to mitigate risks more effectively and thus engage in strategic workforce planning: By utilizing predictive analytics, it’s possible to tell how the workforce will develop, where leadership succession will be jeopardized and which position the organization will need to fill in the near future.
To make analytics predictive and to move to level 4, you will probably have to add additional analytical capabilities to your team. At level, it’s likely that you have a dedicated data scientist sifting through your people data. As predictive modeling goes beyond simple data analysis, you will begin to use tools that require more programming knowledge. An example of this is R, an open-source system for statistical computation and visualization.
At level 4, you are part of the top 4% of organizations.
You are no longer surprised by the feats of HR analytics, because you’ve seen most of them already. HR plays a major role in your company’s strategic decision-making; it is aware of the impact of people policies and actively uses predictive models. In fact, HR is entirely capable of playing a fully strategic role within the company. Level 4 organizations are therefore more likely to have a Chief Human Resources Officer (CHRO) in their Board of Directors, or have a people analytics center of excellence that directly reports to the CEO.