Cristina grew up in the San Francisco Bay Area as the child of two computer scientists. From an early age, she loved being outside, particularly river rafting and hiking through the northern California forests, rivers, coastline and mountains. She moved to DC for college where she studied International Relations and Conflict Resolution at George Washington University and Georgetown, respectively. Following this, she spent five years at the State Department and two years at Tufts University. She is particularly interested sustainable materials, water, and energy management in the corporate environment. At DUSP, she gained a deeper understanding of transboundary environmental planning, economics, and environmental policy as well as how corporate policies can be aligned to promote environmental and social sustainability. In her free time, Cristina continues to love hiking, travelling, black/white photography, yoga, and reading science fiction and fantasy books. She also likes to think of herself as a pretty decent cook and baker in addition to a old fashioned connoisseur. She lives in Davis Square (Somerville, MA) with her partner and cat.
Cristina is now an Associate with Sharma Strategy Group and is looking forward to her career in corporate strategy and planning consulting.
As water crises continue to occur globally, it would be invaluable to have easy-to-access, comparable and localized data on public water management worldwide; unfortunately such information is not available from a single public source (Koelbel et al. 2018). Information on water risk that does exist does not cover public water management at a granularity that would be useful to industrial facilities and local utilities. Even at a national or state-level, datasets on water risk are woefully incomplete. Given these gaps, the World Resources Institute (WRI) and the Massachusetts Institute of Technology Sloan Sustainability Initiative (MIT-SSI) are seeking to crowdsource multinational companies' information on public water management and water risk to see whether a reliable, globally comparable, and centralized geodatabase can be developed by pooling information that private actors use to map and identify local water risk and public water management efforts essential to their decision-making.
WRI and MIT-SSI began an initial pilot study in 2017 with a survey of six multinational companies and 41 of their industrial processing and manufacturing facilities in 14 countries. These corporations were selected because they operate facilities globally, pursue extensive internal environmental sustainability work, and regularly collect data on water use and discharge at the site level. The initial pilot survey instrument covered (i) the availability of quantified, public information on water availability, demand, and quality; (2) the state of the relevant infrastructure including reliability of water supply and availability of wastewater treatment services; (3) existing water access regulations and consistency of regulatory enforcement; and (4) crisis response.
I was asked to analyze these survey responses along with the results of follow-up interviews conducted in coordination with site visits to a selection of the survey respondents from California and India. I set out to determine whether the risk indicators used by the WRI/MIT-SSI partnership accurately portray on-the-ground public water management circumstances at the facility level for companies operating in both low and high-risk areas. I also tried to determine whether the water risk indicators developed by WRI/MIT-SSI are comparable, credible, and relevant across a range of manufacturing and industrial processing sites.
In order to assess the validity of the initial survey instrument and the data it generated, I completed 27 interviews of 32 academics, public water managers, corporate facility managers, and individuals associated with non-profit organizations engaged in water and sanitation. I also visited two facilities in Southern California and Maharashtra, India while following up with six facility and environmental managers who completed the initial surveys in these regions.
I found the pilot study responses generally reflected local public water risk management conditions and were trusted and found credible by all stakeholder groups interviewed. Furthermore, officials and stakeholders engaged in public water management, advocacy, and oversight thought the data generated by the survey instrument would be useful in a variety of ways as long as enough data points are provided and anonymity of corporate respondents is maintained. Unless responses can remain anonymous, there were fears that particular sites might be subject to litigation or regulatory retaliation. Facility managers said that they were able to answer all the survey questions based on what they already knew from their facilities' daily operations and from information regularly collected for internal environmental reporting and efficiency efforts. In my view, the responses appeared reasonably accurate and they were generated in a timely manner. Furthermore, collecting this information from corporate actors is not only feasible but is preferred in some contexts.
My recommendations for improving the survey instrument emphasize the need to expand the scope of the survey while remaining cognizant of the need to keep the instrument brief. This includes collecting data on the availability of recycled and reclaimed water and addressing the existence of regulations that require the use and treatment of wastewater on-site. Furthermore, concerns about whether the survey respondent is qualified to answer the questions regularly arose; therefore, an additional recommendation is to provide a question to validate whether the respondent works onsite or has operating knowledge of water management in the region. WRI and the Pacific Institute, who will be superseding MIT-SSI in the project as it moves forward, should collaborate with additional institutional and corporate partners to ensure that more data points are collected globally as this will enhance the global credibility of survey findings.
You can read Cristina's thesis on MIT DSpace