With any developing science, it is extremely important to take care during the early years to build a foundation of credibility. A single-score LCA is just like any other tool in that it can be used well or poorly. Here are a few best-practice suggestions for how to use, discuss and present a single-figure (or scoping) LCA.

1. In presentations, discussions, and slides, always emphasize terminology that clarifies that this is a single figure LCA, not a multi-score LCA. For instance, the term “scoping LCA,” accurately describes what this LCA is intended to do, and implies some limitations.

2. You can use graphs judiciously. While bar graphs and charts are the best possible way to make an impact with your information, you should try to avoid any potential exaggeration. If your design only improves the environmental bottom line by a small amount, so be it. You can resist the temptation to use your presentation skills to make it look more dramatic.

3. Instead of showing a single LCA result, you can consider showing the range of ways in which the LCA can be mapped. This can give depth to your discussion, and can also forestall criticism about how you have determined crucial variables such as length of life or modes of use. Modes of use vary widely – from minimal use, to extensive and irresponsible use – and this can skew the data. You can show data for a spectrum of use possibilities instead of averaging out for just one.

4. You should state your assumptions clearly and directly in the presentation. Nothing builds trust better than admitting right away that the assessment does not include hardware, for example. Or, if there is no data available for hemp polymer, explaining that the data for the most similar polymer was used as an approximation.

5. If you are modeling impacts over many multiples of a manufactured product, you should model the product’s most believable market forecast. A small improvement multiplied over millions of units sold might look impressive on a graph, but it’s worth the effort to show the same data multiplied over a more conservative number of units sold… as in point # 3 above, this shows that you strive to model the real situation.

6. You should reinforce that this is a comparative study. The data by itself has little meaning, and is only understandable when compared to something else. We all need regular reminding that the new product X is not necessarily “green” but that it is “greener than Y”.

7. In presentations and discussions, you can avoid jargon and stick with common-sense language. Terms like functional unit can be useful inside your team, but might sound unnecessarily complex to others – base unit for comparison, or unit of service are more direct ways of saying this.

It’s easy to give in to the temptation to oversell the very idea of sustainable design – particularly when you face a skeptical product manager or client. That’s all the more reason to state your case with precision. The more carefully we do our work now, the more solid our foundation for the future – in every respect.