The built environment is one of the major contributors of greenhouse gas (GHG) emissions. To tackle climate change, global targets have been set for this sector. Although life-cycle assessment (LCA) methods are typically used to evaluate a building project's embodied energy in its final stages of development, this evaluation would be especially valuable at early design stages, when the opportunity to modify the design is greatest. In this paper, an extensive review of methods to improve the usability of LCA at the early design stage is presented. Three major issues regarding the application of LCA arose from this analysis at this stage: its time consumption, the lack of design details, and the non-reproducibility of results. Moreover, LCA makes it possible to assess environmental performance, but does not provide design alternatives, which are crucial to introduce environmental targets into an iterative design process. To that end, existing techniques that can address the major LCA issues were identified, together with their respective limits. These include some promising tools that provide and explore design alternatives and their respective environmental performances. Among these tools are exploration methods, which have not been applied to LCA insofar as it is not possible to do so in a reasonable computational time. To bridge this gap, the paper outlines the structure of an LCA-based data-driven design method, which uses a combination of LCA, parametric analysis, data visualization, sensitivity analysis, and target cascading techniques.