Two Ways Human Beliefs Affect LCA

By John Rooks, Senior Research and Culture Advisor

Quality life cycle assessment (LCA) necessitates access to quality data. It’s math and science. There are formulas to follow and accepted models that expose risks and opportunities to mitigate negative impacts. The data and decisions of the process are seemingly fairly predictable, requiring a comparison of one process or material or supplier with others, and then weighing those impacts against cost, effort, impact and feature benefits. Hardly simple, I admit, but to a large degree knowable with degrees of uncertainty. Still, LCA does require a creative approach to yield the greatest insights; that creative approach is what sets EarthShift Global apart.

Adding human beliefs into the LCA equation can make the process and the reliability of the data more complicated, but also more valuable. When measuring the impact of transportation for mangos, for example, we don’t concern ourselves with the beliefs of the driver. But doing so where appropriate presents (at least) two strategies to remove enormous environmental impact from your products and organizations.

#1 Use Phase Research and Interventions

Consider five common life stages of an LCA – Material Extraction, Processing/Manufacturing, Transportation, Product Use-Phase, and Product Disposal. Three are metric-driven factors based on existing data modeled using well-established methodologies and LCI datasets. Two - Product Use Phase and Product Disposal – are unique in that the impacts are largely driven by human behavior – not corporate procurement policies or kilowatt hours. Consider what the apparel industry already knows – their Use Phase is the source of the largest water and carbon-related impacts in their products’ life cycles. If LCAs are designed to expose impact hot spots in a life cycle, then understanding those behaviors is critical. But understanding behavior is not enough if we want to shift that behavior. Shifting behavior requires an understanding of the beliefs that support the behaviors. If you think LCI data is complicated (and fun), try modeling human belief patterns.

But we can do it. In fact, we must do it because generic use phase data is particularly problematic in understanding actions, and ideally intervening with the worst of them.

Using a variety of research techniques (journey mapping, ethnography, personas and segmentations, diary and journal studies) can provide organizations with first-hand actionable research to accurately identify realistic Use Phase scenarios to model impacts. A combination of quantitative and qualitative methodologies allows us to develop rigorous belief - and action-based models of product use. It’s not enough to simply ask “do you wash your jeans in hot or cold water?” We must understand why. What do consumers believe and where did that belief come from that creates the habit of a hot water double rinse? Once we understand the why, we can generate a series of interventions to “correct” the behavior. Levi Strauss’ CEO Chip Bergh famously went on a multi-year media blitz imploring consumers to not wash their jeans after Levi’s had completed an LCA. Their goal: make washing jeans uncool.

Once an accurate depiction of Use Phase – user beliefs, attitudes and barriers to change – is understood, we then develop and consult on the design of interventions (communications, campaigns, best-practices, language, instructions, even new product design) to change Use Phase Beliefs (UPB1) required to modify Use Phase Behaviors (UPB2) positively for the product life cycle assessment.

I was fortunate enough to work (shout out to partner organization More Than Sustainability) with Google’s hardware team on what are called Hibernating Devices – hardware no longer in use but still stored in homes. Go look in your drawers or closets and count the old tablets, phones, computers, boxes of misfit cords, digital cameras and so on, I’ll wait….

We conducted in-depth quasi-ethnographic interviews with consumers who were screened carefully to own hibernating devices. We wanted to know where in the house they were stored, how long each device had been unused (up to a decade in many cases), how do you feel when you see them once or twice a year, what did they know about e-recycling, did they believe that climate change was man-made or a hoax, and so on. We would dig throughout the hour-long interviews to discover the devices they said they would never part with and then role play scenarios that might convince them to recycle it. In nearly every single interview, consumers realized they had more devices than they recalled when filling out the screener.

Conventional industry logic led the tech sector to believe that poor electric recycling rates could likely be solved by (1) awareness of options, and (2) convenience of options. Full stop. Solve for these and recycling rates will skyrocket. Not so fast. Our hibernation study identified 5 additional barriers to recycling these hibernating devices.

• Perceived Value – “I paid $1,000 for this laptop, surely it is worth more than the $50 the manufacturer is willing to give me.” This is an economic perception barrier.
• Good Times - “I remember listening to this iPod Shuffle walking to work when I got my first job.” This is a relationship with things barrier (a relationship by the way that tech brands have engineered).
• The Backup Plan – “If my new phone breaks, I’ll need a back-up (or three).” This is a fear barrier.
• Schrodinger’s Photos – “I think there might be photos on there that I want, but it won’t start anymore.” This is a technical barrier.
• Data Security – “Even if I wipe the hard drive, I know hackers can still get my data.” This is a fear and technical barrier.

Some of these (sometimes all) must be solved before moving on to the convenience barrier.

(Read the full Google whitepaper on this research here.)

(Research was sponsored by Google’s Hardware Sustainability Team, and through their generosity and support of sharing this information we are able to make it freely available. For full access to videos transcripts and interview demographic and application data, please contact us.) 

The research confounded industry assumptions that education and convenience were the first solutions. A city-wide pilot program was launched to develop and test interventions for many of the unexpected, invisible barriers. – all in the service to changing the dynamics of Use Phase and Disposal impact for the better.

Note: These same research techniques can be used during the product design phase to engage with potential users weighing the value of environmental benefits against other product attributes, attitudes toward competitive products, concept testing and even ideation and co-creation. I recommend this highly if you are doing an anticipatory LCA on a new product.