Boosting cultural change with data
How to get from intuitive ideas to data-informed actions
Do you think data and culture don’t go together? Think again! The perception of culture as observable practices allows you to look at your cultural transformation from a data perspective. By incorporating data into your endeavour, you have another lever to increase urgency and a source of inspiration from which to derive concrete actions. On the way towards self-organization, the right data infrastructure can provide the necessary feedback for coordination.
“Culture eats strategy for breakfast.” Anybody working in the field of consulting knows this quote by Peter Drucker. Many case studies have been written about how corporate culture influences the long-term success of a company: It can be a motor for innovation, a powerful attractor of talent, and the reason to stay with a company. Today, many practitioners and scholars believe that it might just be the only remaining source left when it comes to creating a sustainable competitive advantage. But while its importance certainly is undeniable, there is still little consensus in the literature on how to define, let alone change corporate culture.
I do not want to bore you with the countless definitions of culture and change models that are out there. Many have tried to summarize and compare them and have done a way better job than I ever could. However, I would like to point out one interesting observation: Data rarely plays a role in any discussion surrounding culture or cultural change. Of course, most case studies are based on questionnaires about people’s perceptions of corporate culture, but it seems that this complex construct itself cannot be measured. Or can it?
When we hear the word culture, most of us probably immediately think of the famous iceberg model. And while it may be true that the deeper layers of culture such as beliefs and values certainly go beyond any form of objective measurements, practices don’t. In 1984, Edgar Schein proposed a model of organizational culture, in which observable and therefore measurable artefacts such as architecture, language, leadership behaviour, and stories make up the tip of the iceberg. In their book “Cultural Strategy”, Douglas Holt and Douglas Cameron continued this line of thought by stressing how important practices are when it comes to driving cultural change.
Today, many firms are desperately trying to change their culture. They want to become more agile, self-organized, or — my favourite — more innovative. Usually, change is initiated by top-management because they either feel like the competition is catching up or because they are having trouble finding and retaining the right talent. Then follows the big speech about why and how the company has to change. And more often than not, nothing happens. Why? Because people are reluctant to change and always need an undeniable reason to do so. This is precisely where data should come into play.
1. Measure: Make your case
If you think about culture as being expressed in all kinds of practices, gathering data about these artefacts can help to make the case. Data can significantly increase the perceived urgency of change by substantiating vague requirements for the redefinition of corporate values. To get there, one simply has to follow the basic principles of science: Form a hypothesis and then use scientific measurement to test it. For example, a company wanting to become more self-organized first has to prove that today, too much importance is being placed on formal hierarchies. It might do so by analyzing the language used in internal communication: How often are titles used compared to simple statements of competence (“He’s a marketing manager” versus “He’s in marketing”)? Another relevant source of information might be the satisfaction rates of interns and trainees: Is it generally lower than that of mid-level personnel? Or the people in charge could look at the quantity and quality of feedback people give their supervisors: Are they hesitant to state concerns or suggestions?
All this data can help everyone in the organization understand why the future of the company and even more critical, the happiness of colleagues depends on the success of the cultural change. To achieve this effect, think about how to turn the information you gained from your data into an engaging story. A good story often starts with the grand vision for the future, followed by an overwhelming list of problems and challenges to get there. Use interactive data visualizations that let your employees discover what is happening right now and what this means instead of presenting them with raw data.
2. Test: Induce effective change
Suppose you start gathering data about relevant practices. In that case, change becomes a lot easier because it helps you to already focus on those areas of collaboration, structure, and behaviours that are most destructive to the desired future of the culture. So instead of just publishing some form of mission and value statement, you can initiate concrete actions that prove that you are serious. In our example of the company desiring to become more self-organized, one might introduce regular one-on-ones between the employees and their supervisors or establish a non-bureaucratic channel of communication for feedback and ideas from interns and trainees.
More importantly, you can continue to use data to observe if the practices have changed, and if so, if this also leads to a different perception of culture. To do so, supplement your monitoring activities with regular surveys among employees for qualitative insights. Besides optimization, this creates another benefit: When it comes to cultural transformation, you are in it for the long haul, and keeping up the spirit and motivation of employees is one of the most pressing challenges. By continuously communicating how the initial data has changed, you provide employees with the appraisal and information they need to keep up the excellent work. How often was the new channel of communication for interns and trainees used? Do we still need it, or can we even witness direct communication within the team increasing, e. g. via Slack messages?
3. Learn: Allow for self-organization
I am a huge supporter of all forms of self-organized collaboration. But I am also a realist and have gained some first-hand experience of how difficult it can be to make the switch.
If self-organization is an essential goal of your cultural transformation (and it most likely should be due to our fast-moving environment), data represent the backbone on which to build feedback and collaboration. Because the less you rely on formal hierarchies for coordination, the more alternative ways you need to find to ensure that the members of the organization are aligned with its philosophy and strategy.
It is essential to involve different members of the organization into the process of identifying which data is relevant for their daily work. Because in a self-organized setting, peer feedback becomes one of the most important steering mechanisms for the organization. By involving people right from the start, you increase commitment and buy-in from everyone. Moreover, you can make sure that you gather the right data not only in terms of its information content but also in terms of how comfortable members of the organization feel with regards to transparency issues. Depending on the initial situation, reluctance might be high so that it is better to be considerate. You should evaluate the expressed needs and wishes in terms of their dependencies. This will also give you an impression on a suitable organizational structure: If there are dependencies where people normally do not collaborate, it might be worthwhile reconsidering the way work is organized.
Besides involving people in the process, there are three other ways how you can make sure that people build their work and collaboration on data: First, you should display the data in an adequate existing format or tool of communication. Try avoiding establishing yet another channel that people have to check and instead, create a seamless work experience. Second, make sure people talk about data by making it a fixed point on the agenda of regular meetings. Last but not least, you have to be consequential and act on the data your employees gather by integrating it into your reward system.
All this isn’t to say that cultural transformation should be only about data. As with everything else, data can inform decisions and actions, but it cannot substitute for human intuition and emotion. That’s what I mean by data-informed in contrast to just data-driven thinking. So every company has to find the right variety of additional means to target values and beliefs and underlying assumptions, the other two, more implicit levels of culture in the iceberg model. In my opinion, this is something that has to come from within, from a sincere intention and an emotional source. Sorry, but data just can’t do that — yet …
Sources:
- Schein, E. H. (1984): Coming to a New Awareness of Organizational Culture. In: Sloan Management Review, Jg. 25, Nr. 2, S. 3–16.
- Holt, D. & Cameron, D. (2010): Cultural Strategy. Using Innovative Ideologies to Build Breakthrough Brands. United States: Oxford University Press.
