Tuckman and Lencioni’s models were devised for more linear, stable and long lasting teams who don’t operate in agile or virtual environments. In the case of Lencioni’s model, we were aware that there was some research, for virtual teams, that clearly disagreed with his model. Researchers found that it was better to build task based trust before building interpersonal trust, which directly contradicts the writing and model that Lencioni recommends. To be precise, more recent studies do not say the best place to start to build a team, is to deal with an avoidance of conflict, as Lencioni’s model claims. They point us in a different direction. Logically the science made sense to us too. Very rarely, if at all, in today’s fast paced corporate world, do any teams have the luxury of building the psychological safety before they start making progress on their goals. Personally, I have always argued, that it’s better for a team to start the journey of improvement by galvanising around the nature of the tasks at hand than to sit in a circle navel gazing.
We wanted to explore this more and separate the truth from the fiction. So we started a 5-year deep dive exploration into what makes for the most effective teams. Five of us immersed ourselves in academic studies, to explore the conditions and behaviours that predict team success. We wanted to know the relationship between these factors so we could create a playbook for leaders to follow to help them get the best out of their teams. Despite some commentators arguing that teams are so complex and the context is so simple that using any form of playbook is unhelpful, we felt otherwise. Imperfect yes. Unhelpful – that was only a ‘maybe’ for us. Whilst every team and their context is different, could we find a code or sequence that would, for the vast majority of teams, stand up to scientific scrutiny?
We had two additional reasons for deciding to do this.
1) A Dodgy Track Record
Brutal as it might sound leaders have a distinctly dodgy track record of developing the high performing team, with 79% of top teams have been found to be mediocre at best
(3) and 60% of all teams failing to achieve their goals (4). Even leaders themselves admit that only 10% of organisational teams are high performing (5). Numerous other studies have shown that only 1 in 5 teams are considered high performing (5). This poor track record also extends to how teams have failed to collaborate well with other teams. Most employees don’t cooperate or share their knowledge with other departments(6). So not only do our teams not work that well, they don’t appear to be connecting with other teams that well either.
2) A Perfect Storm of Pressure
Secondly we felt that leaders today desperately need a playbook. A number of factors conspire to make a ‘perfect storm’ of factors making team working even more challenging: the speed and impact of digitalisation, growing levels of societal individualism, worsening mental health, increasing levels of diversity, more regulatory pressures and the growing phenomena of virtual working. When we started our research we didn’t have Black Lives Matter, the Me Too movement nor COVID 19. Each of these, especially COVID 19, has simply exerted even more pressure on team leaders. We felt a playbook was required 5 years ago. Today we are even more convinced team leaders need one.
Our Research Process
We were scrupulous. We only wanted to look at the very best science available so we didn’t bother reading business magazines or research conducted by other consultancies. We felt these ‘papers’ were more often than not unreliably constructed or were too commercially self –interested. So we sought out only peer related respected academic journals studies.
We invested in work psychology search engines and employed an organisational psychology research company. We extracted data from literally hundreds of thousands of academic studies, published in respected peer related work psychology journals during the last 30 or 40 years.
We found a bunch of team behaviours that were found to predict positive performance outcomes and we found a bunch more that predicted other behaviours that in turn predicted positive performance outcomes. In other words we found the makings of some sort of code or sequence. We poured over the data and I tore much hair out of my already balding head as we tried to construct a code to meet our 3 criteria.