Get an En-Gager user-licence or approach one of our experienced business partners to give you support.
Determine together what the cooperation KPI’s or agreements in your organization or team are? You can choose 3. For instance: ‘I ask feedback on my performance’. Or: ‘I plan one new customer visit each week’. Or: ‘I have my client proposal checked by a colleague’. Anything that you think will help you to collectively learn and move forward. Best is, to focus on specific (new) behaviors. Things that you and your team really need to learn to do more or more consistently. Also: think of a proper team reward you want to collect ‘points’ for using En-Gager. A team outing? A joint course? A donation to a good cause related to your project…?
As a team member you get a push message on a weekly basis (default) on your phone. Then you can check-in, meaning that you ‘score’ the three statements. This takes about half a minute. So no, worries about losing a lot of time entering long questionnaires. Easy does it.
Your new score and recent past scores will be graphically displayed in the app. So will your team’s average, so you can compare your score to that of your team (anonymously). You can leave a comment on your score in the app as well.
At regular intervals En-Gager will provide an overview of team scores and analytics in-app and online. This should serve as input for your regular team review. (see ‘how to make En-Gager work best’ for suggestions as to how to deal with En-Gager analytics).
Get an En-Gager user-licence or approach one of our experienced business partners to give you support.
Determine together what the cooperation KPI’s or agreements in your organization or team are? You can choose 3. For instance: ‘I ask feedback on my performance’. Or: ‘I plan one new customer visit each week’. Or: ‘I have my client proposal checked by a colleague’. Anything that you think will help you to collectively learn and move forward. Best is, to focus on specific (new) behaviors. Things that you and your team really need to learn to do more or more consistently. Also: think of a proper team reward you want to collect ‘points’ for using En-Gager. A team outing? A joint course? A donation to a good cause related to your project…?
As a team member you get a push message on a weekly basis (default) on your phone. Then you can check-in, meaning that you ‘score’ the three statements. This takes about half a minute. So no, worries about losing a lot of time entering long questionnaires. Easy does it.
Your new score and recent past scores will be graphically displayed in the app. So will your team’s average, so you can compare your score to that of your team (anonymously). You can leave a comment on your score in the app as well.
At regular intervals En-Gager support will provide an overview of team scores and analytics. This should serve as input for your regular team review. (see ‘how to make En-Gager work best’ for suggestions as to how to deal with En-Gager analytics).
En-Gager was conceived and designed from a humanistic view on professional cooperation. This view asserts that everyone in a (working) community usually wants to make a positive contribution.
Professionals want to have the feeling that their contribution matters, that it is recognized and appreciated by colleagues. We inevitably need others to be optimally productive and to bring out the best in ourselves. To shine. In this view, problems in organizations are nearly always due to issues of cooperation.
For some reason, we often do not succeed in optimizing our joint productivity. This means that improving cooperation is one of the main development opportunities in most organizations. Clearly, the most important conversation that should be conducted in organizations is: how can we help each other to become more productive?
Unfortunately, we have that conversation far too little. So what is keeping us? Maybe it’s lack of time. “Priorities”. Maybe we think we can do it all on our own, being blind to our interdependencies. Maybe we find it difficult to indicate what it is we need from the other, because of our inability, fear or shame. Or maybe because we're not open to what others ask of us, out of indifference or out of fear to be abused or to be overburdened.
En-Gager helps to start and continue that respectful conversation. It aim at targets and agreements on projects or (change) programs that together we find important. Bottom-up, with attention and respect for all involved, because only then the proper context is created in which cooperation can prosper. In this way, En-Gager helps to build productive communities.
Productive collaboration is a verb, something that occurs from moment to moment in the workplace. In real time.
So it is right there -in the context of day-to-day work- that proper and realistic agreements among professionals must be made. Concrete cooperative agreements that really matter and make sense to all involved in that particular community. As a result, management plays only a modest but important role in all this. They need to facilitate the creation of such productive agreements and be role models of professional conduct. En-Gager is not a ‘management tool’, but an instrument of the productive community itself to learn and optimize their cooperative game. This brings all project targets closer.
En-Gager originated from academic research at Maastricht University. Researchers Solinger, Roe and Van Olffen designed and built a new measurement instrument to track people’s commitment to their employing organizations over a longer period of time, taking very frequent measures. (a practice known as ‘experience sampling’ in the social sciences). This instrument ran on a server as it pre-dated the app era. Using this new instrument, the researchers found that the patterns of our commitments to projects and organizations over time can be compared to a hike through a rugged landscape: many hills (high points) and valleys (low points), sharp turning points, and occasional stability. To make sense of all this data they interpreted the various patterns as reflective of a limited number of underlying, ‘proto-typical’ scenario’s. In a paper published in Organization Science they described the following dynamic scenarios:
And three relatively stable patterns:
Prediction algorithms allow for early recognition of which scenario seems to be developing, allowing early intervention with a Mismatch scenario or prevent unnecessary or possibly hurtful intervention in case of a Learning to love scenario.
The current En-Gager app is a very much elaborated and professionalized version of the original instrument.