Data-Driven Team Development – How OTTO Leads Tech Teams to Success

A very well-known model that has been widely used for many years is Tuckman's team clock model (Tuckman, B. W. (1965). Developmental sequence in small groups. Psychological Bulletin, 63 (6), 384–399.), which describes team development as a sequence of different phases. According to this model, an initial formation phase in teams is followed by a storming phase in which conflicts and tensions arise, before common values and norms are developed in the norming phase. Only then, according to this model, does the phase in which a team actually performs come. The classification of a team in the “team clock” is not based on quantitative measurements, but solely on observations. Phase models such as Tuckman’s offer qualitative guidance, but leave the concrete effectiveness of teams in the work context largely open. Accordingly, approaches that focus more on measurability, productivity, and working conditions of teams have become established in recent years.

A more technical perspective and starting point for team development is provided by the DORA framework (https://cloud.google.com/resources/content/2025-dora-ai-capabilities-model-report). This approach, which is specifically geared toward software development teams, is based on a model that predicts organizational performance using four technical metrics. The standardized collection of these key figures offers a number of advantages, but completely ignores the consequences of ongoing stress within the team and the influence of collaboration practices. This fact has led to a number of further developments.

One of the resulting developments is the SPACE framework (Forsgren, N., Storey, M.-A., Maddila, C., Zimmermann, T., Houck, B., & Butler, J. (2021). The SPACE of Developer Productivity. Communications of the ACM, 64(6), 46–53.) for measuring team productivity. Based on the findings of the DORA framework, SPACE includes metrics on efficiency and performance as well as well-being and satisfaction, communication and collaboration, and the quantity of work results to ultimately assess team productivity. This framework therefore takes into account various dimensions of team productivity, not only those that can be measured quantitatively. In particular, the emphasis on the importance of employee satisfaction and well-being was a novelty and is being intensified in the work of subsequent frameworks.

One example of this is the DevEx framework (Noda, A., Storey, M.-A., Forsgren, N., & Greiler, M. (2023). DevEx: What actually drives productivity? Communications of the ACM, 66(11), 44–49.). DevEx stands for “Developer Experience.” This approach focuses specifically on the work experiences of software developers and pursues the thesis that anything that makes the work of software developers more enjoyable or their environment more suitable increases overall productivity. Three components are recorded: flow state, feedback loops, and cognitive load. Outputs or outcomes are not recorded within the DevEx framework. The entire “developer experience” is recorded using qualitative surveys. In contrast to DORA and SPACE, the DevEx framework focuses on recording the quality of the framework conditions for software developers. Instead of directly measuring performance in terms of output or outcomes, the framework thus focuses entirely on factors that determine this performance.

The findings from DORA, SPACE, and DevEx have now been combined and further developed in DX's Core 4 framework. Core 4 is a mixture of the previous approaches and identifies four core constructs: speed, effectiveness, quality, and impact.

At OTTO, we have made use of these findings and established frameworks, combining them with extensive literature research on the current state of team development and team effectiveness to develop our own team development model. This model now serves as the basis for regularly measuring the effectiveness of over 100 teams and forms the basis for decisions within the teams and for organization-wide processes for the distribution of team developers. We would like to describe these two aspects, our team development model and the process for measuring team effectiveness and the team development measures derived from it, in more detail below.

The development of a team does not usually follow a linear progression, nor can we ensure that our international IT teams will work together in the same constellation for long enough to go through all the phases up to “performing” as defined by Tuckman's team clock. It is therefore very important for us to systematically and specifically assess the current development status of our teams in each phase of team development so that we can use these findings to focus on the strengths and potential of each team. We have therefore decided against a phase model and, similar to the SPACE and Core 4 frameworks, focus on the results and effects of teamwork, which we describe as effectiveness. As in these models, we focus on the well-being of employees and their performance in terms of work results. In addition, our definition of effectiveness also includes the viability of the team, as in today's complex working world, the adaptability of teams is a key success factor for long-term economic success.

Furthermore, we believe that results and employee satisfaction in our work context cannot be predicted solely on the basis of technical metrics, as envisaged by the DORA framework. Instead, at OTTO, we pursue a mixed assessment approach similar to the DX Core 4 productivity framework.

Our team development model, which is shown in Figure 1, is based on the Input-Mediator-Output (IMO) framework, as are numerous other team effectiveness models.

The model comprises three pillars: the framework conditions of the team as input variables, performance factors as mediators, and effectiveness as output. This representation of the impact structure is based on the assumption that the framework conditions determined by the organization influence the effectiveness of a team through various processes (e.g., teamwork and taskwork). Since the mediators are not exclusively processes (cf. I-P-O model), but also states within the teams (e.g., trust or psychological safety), the underlying model can be described as an IMO model. This structure underlies numerous scientifically researched models on the effectiveness of teams (Ilgen, D. R., Hollenbeck, J. R., Johnson, M., & Jundt, D. (2005). Teams in organizations: From input-process-output models to IMOI models. Annual Review of Psychology, 56, 517–543.; Mathieu, J., Maynard, M. T., Rapp, T., & Gilson, L. (2008). Team effectiveness 1997–2007: A review of recent advancements and a glimpse into the future. Journal of Management, 34(3), 410–476.), the content and findings of which have been incorporated into our team development model.

After presenting the scientific approach behind our team development model, we would now like to discuss how we use our team development tool Check'n'Swarm to collect data on the effectiveness of our teams.

With Check'n'Swarm, we measure team effectiveness using quantitative questionnaires that mainly contain subjective assessments. In order to avoid basing effectiveness solely on the purely subjective assessments of team members, we evaluate team effectiveness from multiple perspectives. In addition to the assessments of the team itself, there is the option of external assessment by stakeholders and users. Furthermore, an assessment of the team is made by a person in the role of team developer, and the team's direct manager is also given the opportunity to provide feedback on the team's effectiveness. Although surveys are generally subjective measurement methods, our multi-perspective approach and standardized data collection enable us to increase the objectivity of the data. In addition, in line with state-of-the-art practice, we are planning to combine survey-based measurement methods with data from automated monitoring systems (cf. DORA) in order to obtain a holistic overview of a team's effectiveness.

However, conducting the survey from different perspectives alone does not represent added value, either for the team itself or for the organization. In order to generate impact with the help of the collected data, it is essential to also work with the collected data. This is done initially within the teams, once a quarter in a workshop based on a retrospective format, which is usually conducted by a team developer from the respective department. With the aim of identifying relevant areas of action for the team, the results of the respective perspectives are discussed in this workshop. If necessary, so-called “in-depth modules” can be used to support the teams in delving deeper into individual identified areas of action and learning. This allows aspects of teamwork that are relevant to the team to be examined and discussed in more detail before the team decides on specific team development measures.

This process is illustrated in Figure 2 below using an OODA loop:

The measures are implemented either in the area of performance or they address the team's framework conditions. As part of team development, work is therefore carried out precisely in the areas of action that have been identified from the analysis of the effectiveness data. To improve performance, the focus is either on work processes, teamwork, the team's ability to learn, or the team's conditions. In terms of the framework conditions, the focus is on the team's tasks, the team itself, or the leadership of the team and within the team. The teams are supported by a team developer in selecting and implementing the appropriate team development measures. In addition to the work within the teams, organizational cross-team processes are also initiated on the basis of the data to ensure the systematic distribution of team development capacities among the teams according to their needs for action. In addition to the quantified effectiveness of the team (based on the assessments of the team developers), information on the relevance of the team's contribution to the achievement of current corporate goals is also incorporated into this mechanism. Based on these criteria, effectiveness, and the team's contribution to corporate goals, team development capacity allocations are reviewed and adjusted every 3 months.