Organisational culture is more important than ever. Continuous digitisation, scarcity in talent and skills are a fact that organisations are increasingly dealing with. The World Economic Forum (WEF) expects that by 2025, humans and machines will spend the same amount of time on work related tasks. According to the Hopes and Fears 2021 report from PWC 23% of employees believe that their jobs will become obsolete in the next 5 years. Organisations require employees who possess tech and data skills to stay competitive in an digitising landscape and at the same create a culture that fosters learning, where employees are motivated to develop. Using culture as an asset to attract and retain the talent needed, and at the same time making sure that there is a culture that focusses on developing the workforce with the skills necessary is the smart thing to do. Therefore, organisations need to be helped by facilitating data driven insight in organisational culture.

So, for a People Analytics team and/or other relevant practitioners’ organisational culture should be addressed as a matter of importance. Organisations often are well equipped to report on ‘hard’ organisational outcomes such as safety or risk indicators. However, gaining a grasp on ‘soft’ culture indicators and their relationship to these outcomes is more difficult. Indeed, the subject of organisational culture is a hard concept to grasp. When searching for ‘Definition Organisational Culture’ , something like this will likely pop up:

“Organisational culture is commonly defined as the complex set of values, beliefs, philosophies and symbols that characterise the way in which a firm conducts its business” (Sorensen, 2002)

or

“Organizational culture is the pattern of basic assumptions that a given group has invented, discovered, or developed in learning to cope with its problems of external adaption and internal integration, and that have worked well enough to be considered valid and, therefore, to be taught to new members as the correct way you perceive, think, and feel in relation to those problems” (Schein, 1984, p.1)

These conceptualisations are broad, and therefore quantifying it can be hard. In addition, literature on how to quantify culture rarely provides a clear path for practitioners, as part of the difficulty is choosing the right dimensions. These dimensions can be more or less relevant depending on the kind of organisation you’re looking at. This leaves practitioners with little guidance on where to start on the journey of providing data driven insights into organisational culture.

At Rabobank, we have made organisational culture tangible. We believe that providing teams and management with data driven insight in organisational culture is necessary to facilitate good conversation about organisational culture. We see culture as an asset, which has impact on important business outcomes like risk indicators and financial indicators. Our people know and demonstrate in daily practice what behaviour it takes to work for a cooperative bank. Those behaviours are shaped by underlying mechanisms such as individual characteristics and group dynamics. Therefore getting a grasp on how things get done at the organisation, how the related behaviours are formed and how they relate to other business outcomes is one of the things Rabobank has been working on.

In this article five steps are shared to enable people analytics teams, organisational researchers and other relevant practitioners to start with quantifying this big concept and provide organisations with tools for working on organisational culture.

Step 1:  Come to a shared problem definition on culture

First, and this is the most obvious one, come to a shared sense of the problem and importance of giving insight in organisational culture with all stakeholders involved. Use these moments to hypothesise about aspects within the organisational culture which are of importance and relate to other important organisational outcomes. Without having a shared problem definition, and the underlying mechanisms which relate to the problem, there is a risk that the solution will not be adopted by the organisation. You can use a model to help build an understanding of what goes on in the organisation and which underlying mechanisms are of importance for culture, to keep things a bit more simple. For example, one can choose a model which is composed of different building blocks for organisational culture.  These building blocks can be Behaviour (B), which is formed by an Individual (I) and the Context (C) he or she is in. Different models that can be used for inspiration can be Lewin’s equation (Lewin, K. 1936), which states that behaviour is the function of the person in their environment, or the Iceberg Model from De Nederlansche Bank which is composed of three layers; mindset, group dynamics and behaviour (Schein, 1990; Straathof, 2009).

These are broad models, and help in getting a conversation going with the different stakeholders involved around organisational culture. After all, HR is not the only stakeholder involved in this topic. Together with other departments the model can be used to answer the following questions and draw some first hypotheses:

• What are indicators that are of importance in B, I and C?

• What does literature provide about B, I and C?

• How do B, I and C relate to organisational outcomes?

• With this approach the pitfall of not finding alignment due to the broad nature of the concept organisational culture is avoided.

• It’s important to note that the model is just a starting point, you can let it go in later stages if required.

Step 2:   Set design principles upfront

Second, agree on the design principles of the eventual product with the different stakeholders. Especially when dealing with a broad concept such as organisational culture, it’s important to pre-set expectations and keep it simple. When for example working towards a dashboard, it’s tempting to bring a lot of indictors in which does not favour interpretability. Furthermore, agree on the flexibility to change indicators. You should design and set up an initial set of indicators, and at the same time you are left with a feeling that you can do better next time. Giving insight in organisational culture is not something that can be done one-time-right. It requires an iterative process. To do this efficiently, it will also help to agree on the frequency in which the iterations are implemented and highlight that indicators can change over time. Another design principle to discuss is whether to include the product in existing decision mechanisms, or set up a new decision cycle. In short; apply stakeholder expectation management, focus on KISS (Keep It Simple Stupid) and plan for change to ensure future success in delivery and adoption.

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Step 3:  Develop culture indicators

In the third step make the translation from the sketched hypotheses (step one) to quantified culture indicators which can be used to test the hypotheses. Let’s take an exemplary organisation to clarify this step: this organisation has a lot of manufactories and focusses heavily on safety measures as important organisational outcomes. Together with the stakeholders you came to the hypothesis that feedback is a key differentiator in following up on safety regulations. Individuals who followed the mandatory training about safety regulations and who work in diverse teams are more likely to give each other feedback on behaviour which impact safety outcomes. A following equation can be formulated:

Feedback (Behaviour) = Followed Mandatory Training (Individual) x Working in Diverse Team (Context).

Now you know that you want to design data points around these three indicators. Some more clarification about these indicators as well as other examples for inspiration are mentioned below:

• For Individual: Insight into the completion of mandatory trainings, in this example about safety measures, provides information about the mindset the person needs to have from an organisational perspective. Another angle is to look at data on how employees are feeling. For example, employees feeling involved in changes may come with a different mindset to the organisation then their peers who feel less involved.

• For Context: Think of measurable data points which reflect the context in which employees work in. Group dynamics for example can be identified by providing insight into diversity within teams. Different perspectives help in looking at challenges from multiple views, increasing the chance of successful decisions, especially when it comes to more complex tasks Kanfer, R. (2008). Other culture indicators for context could include co-operation between teams and experiencing psychological safety in teams.

• For Behaviour: Use information about behaviour which is important for the organisation. Behavioural values and statements are often given in board-level documentation. Use these as input for the development of indicators on behaviour. In this example, feedback behaviour is shaped by individuals who followed mandatory training, therefore knowing which behaviour is desired regarding safety measures combined with working in a diverse team, where it is okay to bring different perspectives on the table.

When you have developed measurable culture indicators, you are able to further research the culture indicators and relate them to important organisational outcomes.  

Step 4:  Gather data and test hypotheses

In step four, it’s (finally) time to get into the data, and test these hypotheses to determine which culture indicators to use in the product. Let’s continue working on the example above.

For employees following mandatory trainings use learning systems to extract data points. Think about different types of information you can get out of the same data. You can solely look at completion of the trainings, and you can add a time component, providing information about the time it takes before an employee accumulates information which is of importance for the organisation. To combine these data points with diverse team data, the analytics team needs to take data from the core HR system. First, identify teams. Second, compose a diversity score. After this, you know which employees work in a diverse team, and which employees do not. For the behaviour part, in this case data on feedback behaviour, the team could look at usage of feedback systems or at employee survey data . It is highly probable that surveys in the organisation capture the behavioural values deemed important by the organisation. If these are not already measured, look for related questions and start there. Stakeholders know that change is imminent based on step two, which provides you with the opportunity to add relevant questions later on if needed.

Now, you can check the relation between the different culture indicators. Can you for example show that employees who completed the necessary trainings and work in a diverse team report higher scores on the feedback questions? Following up, can you find a relationship with safety outcomes per manufactory? Use this analysis to determine which culture indicators to keep and which to not utilize when providing the organisation with steering information around organisational culture. Finding just a few relations is already something great for a first iteration, and remember; keep it simple.

5.  Step 5:  Implement and Act

The fifth step is to implement and act. By now the team has come to a problem definition, identified hypotheses, developed quantified culture indicators that relate to organisational outcomes and tested these hypotheses. This led to a first glance at what quantified organisational culture looks like. Based on this, different indicators are now ready to be provided to management, teams and employees. Team up with HR business partners, compliance officers and other colleagues involved in discussing the insights to ensure the right interpretation. In this way working together and coming to a good product which facilitates a great discussion about organisational culture and other organisational outcomes. Providing these insights together with organisational outcomes such as risk or safety data is of the utmost importance. Imagine having a lot of safety incidents reported in a team with a high score on the feedback culture indicator, and having the same amount of incidents reported from a team with a low score on the feedback culture indicator. In this comparison, the safety incidents can be placed in the context of organisational culture. This is what makes the difference in decision making.

Having followed these 5 steps, the organisation made a leap forward in quantifying organisational culture and providing insights that will help the organisation work towards and foster a desired culture. And of course, in this process ideas are generated for future steps. It is likely that you will find that the value of these insights can be increased by working towards more differentiation in type of data points being leveraged. When using employee surveys for example, you are using self-reported measures. These can be biased by the employee filling them in. Finding other measures for the same indicator is a next step towards a more balanced measures design. Also, continue to test for relations between the culture indicators and other organisational outcomes. In this way, laying the base for predicting where important outcomes are more likely to happen as a result of organisational culture. For example, predicting where risks are more likely to happen, or where work-related accidents are more likely to take place.

Remember, this is one way to quantify organisational culture, not the only nor the best one in every situation. By sharing their approach people analytics teams are given more tools to help them facilitate organisations better in making organisational culture an asset. Helping organisations in successful execution on transformational strategies in digitising times and designing great places to work for talent by making the intangible concept of organisational culture tangible.

ABOUT THE AUTHOR

Martijn Wiertz is part of the Global HR Data & Innovation Department of Rabobank. The goal of the team is to help employees thrive by understanding their needs and translating those into insights facilitating data driven actions and promote innovation for people at work.

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