Following on from our last blog, sports organisations have devised a multitude of ways in which different national federations (NFs) can collaborate. In our case studies, we observed that these collaboration projects between NFs are typically initiated with the goal of addressing one specific issue common to the participating NFs.
As a result, identification of a collaborative partner is a rather simple process of looking at those NFs who have a common goal or issue and engaging with them. For example, we saw that cross-sport collaborations between NFs arise to tackle or raise a common issue (i.e participation, lobbying or funding), or as a result of having similar challenges due to their innate characteristics as a sport (i.e. being a water sport, an outdoor sport, a motor sport, etc). Accordingly, these types of collaborations are based on just one variable.
From our analysis of the case studies we examined, one of our key observations we made was that a clear understanding of the cultural differences between the federations, especially at an early stage of the relationship, is a crucial activity in building successful collaborations (and this will be discussed in further detail in our third and final blog). With that said, choosing the right collaboration partner is not only about having an organisational fit in terms of culture, objectives, issues or opportunities. One must also consider which partner can maintain and deliver a sustainable collaboration activity based on a number of different variables that make up the unique operational environment of each federation. These could include their organisational structure, their decision making flow, their communication system, how they resolve conflicts, and the innate characteristics of the sport. In this sense, we have sought to capture, for each federation, the way in which each organisation operates and functions on a daily basis along with the environment and sporting factors that best describe their sport. From our study, we selected 13 different variables that could best determine the organisational culture of the federation and the innate characteristics of the sport, and used those to find NFs which are best suited as potential collaboration partners.
The method that we used to group the NFs based on these 13 variables is called “Principal Component Analysis” (PCA). This method observes possible correlated variables of the NFs' characteristics, finds the similarity pattern, and converts it into a set of NF groups. The PCA method has been used successfully on a number of occasions for conducting analysis in the research fields of sports science and sports marketing. In our research, we have employed the PCA method to help NFs find other NFs that have an organisational fit for collaboration and could potentially unlock collaboration inertia.
We managed to test our multi-variable sports mapping model across 17 NFs in England via a questionnaire that we distributed to the NFs. Based on their responses, we were able to generate 4 major groups. The membership of the groups turned out to be quite interesting. The NFs (see figure 1) that fall under the same circle are the ones who have the nearest similarity in terms of culture and characteristics of the organisation. Our model suggests that these are the ones which have a higher likelihood to reach success if they decided to collaborate on an activity. What is curious is that these are not necessarily obvious partners for collaboration on the face of it. For instance, taking the blue group (which includes Judo, Volleyball and Gymnastic, etc.) - these members are all very different sports. However, the multi-variable sports mapping model sees past the obvious and uncovers some similar organisational characteristics which indicate that there exists potential for these NFs to work with one another, even on the simplest of projects.
We believe that there is still more research needed in this area as, in the current economic and social context, there is a greater need for sports to collaborate more frequently and efficiently with one another in order to protect and promote the interests of sports in our society. Our multi-variable sports mapping model is a suggestion and a first step to test other ideas in this field and we hope we can get the opportunity to conduct further tests with larger participating NFs to see what conclusions and actions can be drawn. Most of all, our literature review on inter-organisational collaboration in the corporate world revealed that any fruitful collaboration activity boils down to 3 mains things: people, communication, and resources.
Now that we have briefly covered how NFs can better identify potential collaborators, our third and final blog will focus on how to properly manage and sustain a collaboration project by having in place sound communication and resource management systems.
