Lessons Learned for Data-Driven Implementation Intentions with Mental Contrasting

Goal setting and realization are important but challenging. These challenges can be mitigated through effective application of behavior change realization techniques such as implementation intention and mental contrasting (IIMC). IIMC relies on identifying situations compromising desired behavior (i.e., obstacles) and creating action plans to handle those situations (i.e., identifying what, when, and where of actions to prevent or overcome the obstacles). We explore ways historical personal data can enhance the efficacy of IIMC application in the context of improving work-nonwork balance in a probing study with 16 information workers at a large technology company. We share lessons learned from this study that can help designers in further supporting goal realization with data, guide researchers interested in more formal studies of IIMC, and point the research community to important areas of future work on data-driven IIMC, particularly in the work context (e.g., the social dimensions of sense-making and planning).