7 Benefits of Working Together with Academia in People Analytics

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“…whenever we are faced with a new people issue at Google now, we don’t ask ourselves, what does successful organization X do with this topic? Instead, we ask ourselves, what does the literature say? And if I have one piece of advice to give all the businesses that are in the audience out here, it is to develop better relationships with academics…” – Prasad Setty, Vice president of People Analytics & Compensation at Google.

Google is arguably the most advanced company when it comes to people analytics. According to Prasad Setty, VP of People Analytics and Compensation at Google, working with academia is a must. In this article, we will discuss 7 key benefits of practitioner-academic collaboration in people analytics. 

Introduction

The strategic value of HRM has been a popular research topic for decades. Academic research has been fruitful in generating insights and building theoretical frameworks. These frameworks link employees’ competencies, behaviors, and attitudes to desired results (Pearce, 2009). 

Also, practitioners have been fruitful in increasing the strategic value of HRM and human capital. Through people analytics, practitioners are able to make data-driven human capital decisions (Van den Heuvel & Bondarouk, 2017). As a result, the quality of those decisions can be demonstrated. This makes it more likely that the newly implemented HR practices will have the desired effects (e.g., increased performance, less turnover, increased employee well-being). Thus increasing the strategic value.

In practice, people also recognize the strategic value of HRM and human capital. People analytics enabled practitioners to make data-driven decisions on human capital (Van den Heuvel & Bondarouk, 2017). This helped in increasing the strategic value of HRM and human capital.

So, it’s beyond doubt that both practitioners and academics strive to enhance our HR-related decisions in organizations. Yet, sometimes practitioners and academics talk past each other. Researchers may focus on a different set of problems than practitioners (Tenhiälä et al., 2016). At the same time, HR practitioners are sometimes unaware of the results of the research performed by academics. So they might miss information that could boost the performance of their organizations. Luckily, practitioner-academic collaboration is becoming more prevalent.

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This brings us back to the opening paragraph. Google’s project Oxygen is perhaps one of the most well-known examples of how HR and science got together. Fortunately, the project is no longer an exception to the rule.

But what exactly are the benefits for organizations to work together with academia in people analytics? 

1. Academics have a broad range of knowledge 

Academics are often experts in a specific area (e.g., employee well-being, innovative work behavior, job design, leadership, HR practices, etc.). Yet, they are often also educated in and familiar with a broad range of related topics. So academics are not tied to a specific product or subject that they would like to sell. This means that academics are to a large extent flexible in the constructs they can research. 

So when cooperating with academics you can expect a tailor-made research project. A project that will fit the business problem at hand. 

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2. Academics are trained statisticians and methodologists 

In our previous article, we explained the concept of validity in people analytics. There we explained that validity says something about how sound your research is. As we explained, validity is complex and can be difficult to achieve. A related concept is reliability. Reliability is the degree to which research methods produce stable and consistent results. 

Yet, the consequences of invalid and/or unreliable research have major consequences. Consequences can include meaningless or inaccurate results and unsuccessful implementation of changes. In the worst case, it can even lead to the implementation of changes that in the end harm the organization. Academics are trained in study design and methodology. Thus, they are very capable of improving or achieving the validity and reliability of research. They do this all the time in their own research. 

So, one way academics can help is to safeguard the project’s validity and reliability. In our previous article, we explained that doing valid research is an iterative process. Academics can assist in this iterative process. They can suggest ways to improve the process of data collection. Also, they can suggest how to improve the quality of the data itself. This will benefit future analytic endeavors and, in turn, benefit future decision-making.

Academics are also highly trained in statistics. They have been trained in statistics throughout their academic careers. Academics spend a large proportion of their time at work on research-related tasks. This means they need to continuously improve and expand their statistical skills set. For that reason, academics are often aware of the latest developments in the area of statistics and methodology. 

As a result, academics can test complex issues (models). This includes models that explain developments over time (i.e., test causality) and models that take into account different levels of analysis (e.g., employee-level, team-level, organization-level data). 

So, when working together with academics, you are guaranteed to go far beyond simple descriptive statistics!

3. Academics can link your data to scientific literature

As mentioned before, academics know a broad range of topics (benefit #1). Academics have to stay up to speed on the latest developments in their field. This means they know about recent publications containing the most novel evidence in their field. This enables academics to think along with the organization about the business problems and what might explain or cause it.

At the start of the practitioner-academic collaboration, there are often two different scenarios: 

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  1. Organizations have a lot of data available and want to use it to make better people decisions. However, they don’t know how to use the data, what to use it for, or how to structure the data to make it usable. 
  2. Organizations can identify the business problem but are not sure why or how the problem occurs. In other words, they identified the business problem (e.g., high turnover rates) with the data. But they do not know how to use data to identify why, how or when these outcomes occur. Sometimes organizations already have a hunch about what is causing the problem but are not sure if this is the complete story.

In both scenarios, an academic’s expertise can come in handy and we will explain why. 

The digitalization of many HRM processes and databases have made it possible for organizations to generate vast quantities of data (e.g., performance data, absenteeism, employee records, employee resumes, etc.). However, organizations oftentimes do not know how valuable the data they possess is. 

This is also the case in scenario (1) described above. In this scenario, academics can provide theoretical frameworks and research evidence. This will help structure the data and determine which part is relevant for the project. The theory can help to look at the business problem from a different perspective and bring up possible explaining factors. This will help to formulate specific and detailed questions to examine the data.

In scenario (2), academics can first make an inventory of the available data and use the data as a starting point. By linking the data to the literature, academics are able to distill theoretically related constructs from the data. This can lead to aspects that the organization did not consider before. Yet, these aspects might very well be an important piece of the puzzle. So, academics can use the literature to shape the project and formulate specific research questions.

This way, organizations can thoroughly investigate the business problem. In other words, identify as many pieces of the puzzle as possible.

4. Academics’ performance appraisal is largely based on high-quality research

Universities are non-commercial institutions. A university’s foremost goal is to be leading in the areas of top education and high-quality research. As such, academics’ performance appraisal is largely based on their publications.  

So, for academics, the project must be practically and scientifically relevant. An academic’s goal is to inform the scientific community of the obtained insights. As scientific papers need to cover high-quality research, you can be reassured that the research will be of high-quality. This means that the project will yield many relevant practical recommendations. Most likely, they will improve HR decision-making as well as your organization’s performance.

5. Academics are committed to researchers ethics and academic integrity 

Academics are educated to follow comply with research ethics, integrity, and confidentiality. Also, universities have ethic committees that have to assess and approve all research. 

Since May 2018, organizations in Europe have to comply with the General Data Protection Regulation (GDPR). And organizations are working hard to become GDPR compliant. Violating the GDPR can have severe consequences for the organization and the people within it. Thus, it is in organizations’ best interest to collaborate with parties that use, process, and store data in compliance with the GDPR.

Many universities work with procedures directed towards data protection and subjects’ privacy. These procedures were often already in place long before the GDPR. For example, universities usually have two-factor verification databases on which they store data. Another example is that universities usually work with confidentiality agreements. Without signed agreements, university ethic committees will not approve research projects. 

So, organizations that collaborate with academics, can be assured that their data is in good hands! 

6. Access to the future labor force 

A good relationship with academics can benefit an organization in different ways. As mentioned above, academics spend a lot of time on research-related tasks. The other main task of academics is teaching. By building a relationship with academics, you can simultaneously build a ‘talent pipeline’. Academics can reach out to students to communicate your open vacancies. In other words, this relationship can function as a recruitment tool. Your future intern, part-time employee, or new graduate could be one of those students!

Occasionally, we see practitioner-academic collaboration evolve and extend to the ‘classroom’. For example, practitioners get invited to give guest lectures. Doing so, they introduce the organization and talk about their experience working there. 

Another example is business case competition. Practitioners come to introduce the business case. They invite students to work together and come up with innovative solutions for the business case. This creates a good learning opportunity for students. At the same time, your organization might benefit from the ideas students present. At the minimum, it gives you the opportunity to make students excited to work for your organization!

7. Contribute to expanding existing knowledge 

By working together with academics, you provide them with the opportunity to collect data and test theories or models. This will expand the current literature and thus increase knowledge. This may sound like a benefit for academia and not so much for the organization itself. Yet, organizations will reap the benefit of this indirectly. 

The acquired knowledge can be applied in organizations, including your own. You can use this information to enhance the quality of HR data, HRM practices, and human capital decisions. Besides, it will inspire and encourage other academics to conduct further research. This, in turn, will lead to new emerging knowledge which you can use in your organization.

Conclusion

It goes without saying that every collaboration is unique. Organizations have different needs, resources, and challenges. At the same time, academics have different ways of working, different expertise, and different skillsets. This means that the exact benefits may be slightly different from one collaboration to another. Yet, we do believe that the 7 benefits described in this blog apply to every collaboration to some extent. 

Maybe some of you are already collaborating with academics. If so, this article perhaps showed you additional ways to (fully) benefit from practitioner-academic collaboration. Either way, we hope that it will be a fruitful collaboration! 

For those who are not yet collaborating with academics: We hope that this article has convinced you of the many different ways your organization can benefit from practitioner-academic collaboration. Don’t hesitate to benefit from practitioner-academic collaboration and make the most out of your human capital!  

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