At the upcoming International Conference on Information Systems, Daniel Rush will be presenting new research empirically examining the association between enterprise information systems capabilities and greenhouse gas emissions in large organizations. The research, co-authored with myself, Ron Ramirez, and Kevin Kobelsky, suggests that IS capabilities may be a critical enabler of achieving corporate sustainability goals. The program session is Tuesday from 3:00 – 3:30 pm. in the Convention Center. Drop by to hear more from Dan!
What professional responsibility do scholars who don’t study climate science have to their students and others who look to them for knowledge about climate change and potential solutions? How to respond to such questions in terms of the nature of the problem, its implications, and approaches for mitigating and adapting to the problem?
Science of Climate Change (nature of problem)
Regarding the science of climate change itself, based on their developed scientific expertise 97% of well-published climate scientists agree that “anthropogenic greenhouse gases have been responsible for “most” of the “unequivocal” warming of the Earth’s average global temperature over the second half of the 20th century,” according to a peer-reviewed study published in the Proceedings of the National Academy of Sciences.
Another peer reviewed study, this time of 3,146 earth scientists finds a similar result: 90% respond “risen” to the question “When compared with pre-1800s levels, do you think that mean global temperatures have generally risen, fallen, or remained relatively constant? and 82% answer Yes to “Do you think human activity is a significant contributing factor in changing mean global temperatures?”
To emphasize, these are the views of truth-seeking scientific experts who study various aspects of climate change and subject their analyses to rigorous peer review and criticism within scientific journals and in research lectures.
Implications of Climate Change (impact of problem)
Regarding the implications of rising mean global temperatures on human life, there’s been widespread research on impacts to food and water supplies, human health, economic growth, conflict and security, disease, etc. For example, a recent study of “Climate Change Impacts on Global Food Security” in Science results in a set of precepts, including
- Climate change impacts on food security will be worst in countries already suffering high levels of hunger and will worsen over time
- The consequences for global undernutrition and malnutrition of doing nothing in response to climate change are potentially large and will increase over time
- Food inequalities will increase, from local to global levels, because the degree of climate change and the extent of its effects on people will differ from one part of the world to another, from one community to the next, and between rural and urban areas.
Overall, and according to the latest 2014 IPCC report: “Based on many studies covering a wide range of regions and crops, negative impacts of climate change on crop yields have been more common than positive impacts (high confidence).” IPCC goes on to summarize that: “Increasing magnitudes of warming increase the likelihood of severe, pervasive, and challenging irreversible impacts”
Importantly, some effects of climate change are impacting human life now, including increased coastal flooding, longer and more damaging wildfire seasons, more frequent and intense heat waves, forest death in the Rocky Mountains, and changing seasons.
Mitigating and Adapting to Climate Change (solutions)
Regarding solutions, arguments can be made for a variety of approaches, including moving away from fossil fuels by pricing the CO2 externality, technological ingenuity, dietary changes away from beef and toward local and organic foods, carbon sequestration, adoption of low-carbon energy sources, enacting regulations, etc.
Two Fundamental Tenets of Professional Responsibility
So what is the professional responsibility of non-climate science scholars in the face of the above knowns and unknowns? I propose two basic principles:
P1 Clarity in communicating consensus of climate scholars and what their research says: most of global warming is being caused by increased concentrations of carbon emissions from human activities such as the use of fossil fuels.
P2 Clarity in communicating the scientific understanding that impacts of climate change are occurring now, and the range and intensity of impacts is likely to increase and be more negative than positive in the future, creating significant risks.
Below, I provide two example statements from professors who are not climate scientists that illustrate alignment and misalignment with the two principles.
1. Roger Pielke Jr., professor of political science in the environmental studies program at the University of Colorado.
Roger uses a simple and easy-to-understand “bathtub model” of carbon dioxide buildup on page 9 of his book “The Climate Fix,” clearly fulfilling P1. He goes on to say that “Many, if not most, scientists believe that the impacts [of accumulating carbon dioxide] will be on balance negative and significant,” in line with P2.
These statements align with P1 and P2 and indicate professional responsibility.
2. Jaana Woiceshyn is an associate professor of strategy at the Haskayne School of Business, University of Calgary, Canada.
Jaana has recently written that “there has been no significant global warming in the last century” and “CO2 is not a significant cause of temperature fluctuations”.
These statements contradict P1 and do not indicate professional responsibility.
In a working paper that will be presented in a few months at the HICSS conference, I describe how leveraging technology trajectories is one of four principles of Digital Fitness. Digital fitness is how I refer to the digital capabilities and mindsets required of all organizational leaders in order to succeed in today’s chaotic digitally enabled business world.
Leveraging technology trajectories is encapsulated by the moving gears in the illustration below. IT continues to get faster, smaller, and cheaper. This leads to increasing and innovative uses to substitute away from older methods or complement existing ones. This ultimately leads to the data avalanche facing most large companies and the use of analytics and other creative software approaches to convert it into value.
Source: Melville, N.P. “Digital Fitness: Four Principles for Successful Development of Digital Initiatives,” paper accepted to HICSS-48, January 5-8, 2015.
A good example of leveraging technology trajectories in the environmental sustainability space is provided in a post on SustainableBrands by Paul Bosworth, which summarizes the critical role that data plays in driving sustainability at USPS:
Data, Data, Data
Sustainable business these days requires data, and lots of it. Companies are using sustainability data for a multiplicity of reasons: to inform corporate strategy, comply with regulations, evaluate investments, improve transparency, develop products and processes, manage risk, benchmark themselves against competitors, change organisational culture, and engage with supply chains.
Increasingly, companies that take a well-organised and data-driven approach are more likely to see investments in their sustainability programme pay off. This means using analysis to better inform decision making, leading to methodically prioritised initiatives that get off the ground far more quickly.
Once the data management programme begins to mature and data inputs are integrated that reach across a company’s financial planning databases and other operational information resources, opportunities for cost savings and revenue generation can be routinely identified and acted upon.
Driving Value From Data
My favourite example of an organisation using data to drive sustainable development is the United States Postal Service (USPS). Across 32,000 facilities, their Office of Sustainability designed an employee-led programme to address goals in waste reduction, energy conservation, fleet fuel reduction, consumables spending, recycling, and water use.
To aggregate and display relevant data, USPS developed a Green Initiatives Tracking Tool (GITT). This features dashboards that allow cost efficiencies and performance enhancements to be monitored across the organisation. The GITT system achieves this by providing status updates for core projects, as well as financial information, through direct connection with the accounting system for each facility.
GITT is also designed to be interactive. It includes a start-up list of 41 suggested projects for facilities as well as guidelines and training modules for their completion. Managers can also understand clearly what projects are in place and where via sustainability performance metrics that are triggered upon project implementation. Ready access to GITT information and comparative tables enable comparison between facilities and geographies. Most importantly, USPS can now track progress in real time at a national level and support those facilities that need additional help.
By using data aggregation and analytics, USPS was able to gain visibility into its progress on sustainability and isolate over $52m in savings in 2012 largely due to employee-led initiatives.
Unfortunately, as I argue in the article, too many digital initiatives fail to meet expectations. It’s my hypothesis that the lack of digital fitness is one source of these high rates of failure. If this is true, it would be interesting to refine the concept of digital fitness by studying leaders at companies that seem to excel at the intersection of IT and corporate environmental sustainability, including SAP, IBM, Danone, Intel, Nest, OPower, and Ebay. What might we learn?
Several interesting Green IS papers were presented at AMCIS last week in Savannah GA.
Here’s a partial list:
- Extending Enterprise Management Systems: The Case of Energy Management (Richard Rößler, Hannes Schlieter, and Werner Esswein).
- The Quest for Environmental Information – Towards a Mobile Application for GHG Emission Tracking in Meat Production Processes (Hendrik Hilpert, Bjoern Pilarski, and Matthias Schumann).
Learning from Adopters: Critical Factors for Achieving Smart Grid Value, (You Zheng and Jason Dedrick).
It appears that Green IS scholarship is shifting from generalities to specifics, which I think is a good thing as we move out of the nascent stage and the literature slowly matures. We still need more studies that connect IS investment to environmental and financial value (more on that soon).
I just returned from the Hawaii International Conference on System Sciences (HICSS) on the Big Island.
While there, I decided to take an extra day to visit the Mauna Loa Observatory (MLO) located on the Mauna Loa Volcano.
As this is a research facility, I was fortunate to get access after contacting MLO Station Chief John Barnes (Thanks John).
Here’s me at 11,141 ft, chugging more air due to the reduced oxygen content.
MLO is an important baseline for atmospheric CO2 measurement and is home to the famous Keeling Curve (here’s an interesting historical account from the American Institute of Physics). Physical scientist Aidan Colton showed me the original Keeling instrument and described its operation (IR spectrophotometry: measurement of reflection or transmission properties of a material as a function of wavelength). Here it is:
Fast-forward to the digital age, and here’s the new equipment that is better-faster-cheaper:
In addition to C02, I also got a great overview of solar radiation monitoring. Thanks Ben and Greg.
Concentrations of greenhouse gas CO2 in the atmosphere are exceeding 400 parts per million (ppm) for the first time in human history. Given the connection between CO2 and global warming, we are entering uncharted waters for human life on earth.
We can’t all visit Mauna Loa to see CO2 measurement first-hand. But we can collaborate to find systemic ways to reduce CO2 emissions and make daily choices that are climate positive.
Four things I’ve done this year in line with Earth Day.
1. Published a conference paper with Dan Rush suggesting that investors positively value investments in IT for managing energy and carbon emissions (rather than not valuing them because they think it’s greenwashing). Dan is leading the effort to broaden the sample and confirm the findings under more robust conditions.
2. Finished drafting a case study examining how two organizations manage energy and carbon emissions. The study revealed numerous environmental data management challenges, including
- integrating energy and carbon management systems (ECMS) with other corporate systems to enable valid and efficient data transfer;
- importing global indirect emission data from utility companies;
- workflow processes involving multiple and iteratively emailed spreadsheets; and
- keeping spreadsheet-based systems current with the latest calculation methods and parameters.
The study recommends that firms conduct total cost of ownership analyses of ECMS adoption and that standards bodies add specific guidelines regarding information systems and their role in calculating estimation uncertainties and conducting validation checks.
4. Designed, developed, and taught an MBA elective that included an online section (is virtual learning more green due to lack of commuting?) for students to learn a design thinking framework and have the opportunity to apply it to projects with a sustainability theme (transport, energy use, local food, etc.). This gets students thinking about the meaning of environmental sustainability (framing), current practices (exploring the design space and synthesizing insights), and how to concept and develop new IT-enabled solutions that satisfy human, economic, and technical constraints. Fantastic experience and student engagement!
Not enough, but it’s a start.
I scraped the EPA website for University GHG emissions (not available for download), made a bar chart excluding those with < 50K MTCo2e in 2011, and added colors to group by climate (my own eyeballing of cold, mild, warm):
- This is not normalized on a per capita or area basis, so comparisons are tentative.
- Top 5 emitters (MSU, Purdue, Iowa State, Michigan, Illinois) are all in the midwest.
- UCLA is the largest emitter in a warm climate.
- Given the nature of the data, it is unclear whether reported emissions derive from generated electricity, heating, or cooling (or other stationary sources?)
- Not inculded in the chart are a few universities that reported with fewer than 25K (rule minimum). Not sure why this is.
- Certain cold weather climate unis have far lower emissions (BU at 53,900) versus others in cold climates (Purdue at 408,928), probably due to how they heat buildings (but I don’t have data to back this claim up).
Thanks to the EPA for making these data visually available. Also, thanks for their ruling that these data are not confidential (allows them to release to the public). It would be great to have better analytics – top of my list would be some kind of normalization to allow for apples to apples comparisons (by sq. ft. or by heat production technology or something).