Information Systems for Environmental Sustainability

How IT can make the world a greener place


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Conference Roundup: Green IS Topics at AMCIS

Several interesting Green IS papers were presented at AMCIS last week in Savannah GA.

Here’s a partial list:

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).


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Climate Risk Regulations Vs Enforced Regulations: The IT Elephant in the Room

In 2010 the SEC published “interpretive guidelines” for corporate disclosure of risks related to climate change, summarized in this table by Ceres (p. 8):

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The Interpretive Guidelines were hailed as an important step forward in providing material information to investors regarding climate change risks.

Did the Guidelines impact corporate disclosures in financial statements (10-Ks)?

Ceres analyzed all S&P 500 10-k filings from 2009 to 2013, finding that:

Most S&P 500 climate disclosures in 10-Ks are very brief, provide little discussion of material issues, and do not quantify impacts or risks. Based on this report’s 0-100 scoring scale, electric power companies received an average score of 16.7 for the quality of their SEC reporting—by far the highest industry average. Even within this group there was high variability in the quality of reporting. (Ceres, p. 5 [my emphasis in bold]).

What to make of these results?

Ceres recommends that the SEC: “devote increased attention to climate risk disclosure by issuing additional comment letters in response to inadequate disclosures, and educate registrants about how to comply with the Guidance.” (p. 28).

Regarding firms, Ceres essentially says: do a better job identifying climate risks and opportunities and disclosing these to the SEC. Ceres refers to the need for “systems, processes and controls to gather reliable information” but misses an important opportunity to address an underlying necessary condition to fulfilling SEC guidance:  implementing and managing specialized information systems for capturing, processing, and analyzing information related to energy, carbon emissions and other important environmental sustainability information.

It would be impossible for firms to comply with financial regulations without such systems, and it’s no different with environmental regulations. Imagine global corporations trying to comply with complex accounting and finance regulations using homegrown spreadsheet models developed and managed by one person: it wouldn’t work. The same applies to environmental regulations.

Here’s the bottom line.

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Guidance, regulations, board-level oversight, internal controls, emission reduction targets, management incentives, and reporting requirements are all well and good. But without addressing the IT elephant in the room – grossly inadequate information systems focused on environmental management information – I don’t foresee any significant changes in actions and impacts.


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Ceres Report – Why do Tech Companies Lead in GHG Emissions and Energy Efficiency?

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Ceres and Sustainalytics recently published “Gaining Ground: Corporate Progress on the Ceres Roadmap for Sustainability.”

613 publicly traded companies were assessed on 58 indicators (governance, stakeholder engagement, disclosure, etc.).

Based on these indicators, the companies were grouped into 4 tiers based on their relative performance (tier 1 is best).

Regarding GHG emissions and energy efficiency:

More than half of the companies falling into Tier 1 for this expectation are Technology companies, including Hewlett Packard, which has not only set timebound targets for reducing GHG emissions and increasing renewable energy sourcing, but also sources more than 10 percent of its primary energy needs from renewable sources. (page 7). 

Why is this the case? The report does not elaborate on underlying causes. 

But it’s part of a larger pattern that I’ve observed (albeit anecdotally) in similar reports in recent years.

My own hypothesis is that tech companies excel in energy and GHG emissions management and reductions given their expertise in managing data and information (necessary to setting and meeting reduction objectives), combined with external pressures based on popular perceptions of energy hungry data warehouses. In essence, tech companies appear to have both the motivation and the ability to lead in energy and GHG emissions reduction efforts.

Could it be that tech companies are natural sustainability leaders? If this is the case, perhaps their strategies and tactics can be studied so that best practices can be diffused to other industries. I’ve spent much of my three-month sabbatical forming partnerships and developing projects related to these ideas. 


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New Research on Energy and Carbon Management Systems (ECMS)

Information systems for managing energy and carbon emissions data are critical to corporate environmental sustainability efforts.

Yet there is a lack of research on how these systems are adopted, used, implemented, etc.

To shed some light on this topic, I decided to explore how organizations are implementing and applying ECMS. Together with my colleague Ryan Whisnant, we looked at two different systems in two different organizations to identify patterns of use and make recommendations for practice.

Here’s the abstract and a link to the SSRN paper (a revised version of which is forthcoming at the Journal of Industrial Ecology):

This article examines an important class of information system (IS) that serves as the foundation for corporate energy and greenhouse gas accounting: energy and carbon management systems (ECMS). Investors, regulators, customers, and employees increasingly demand that organizations provide information about their organizational energy use and greenhouse gas emissions. However, there is little transparency about how organizations use ECMS to meet such demands. To shed light on ECMS implementation and application, we collected extensive qualitative interview data from two service-sector organizations: one that uses a spreadsheet-based ECMS and another that implemented an ECMS provided by a third-party vendor. Our analysis of collected data revealed numerous challenges in the areas of business processes, managerial capabilities, data capture and integration, and data quality. Though our results derive from only two organizations and require confirmation in large-sample surveys, we provide several general recommendations for organizations regarding ECMS. We also provide suggestions for future studies to build on our tentative results. Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2411879

While this paper represents an important early step in this research stream, much more needs to be done. In particular, one of the most important next steps would be to examine the business value implications of these systems.

Continue reading


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Visit to Mauna Loa Observatory

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_1

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:

MLO-2

Fast-forward to the digital age, and here’s the new equipment that is better-faster-cheaper:

MLO_3

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.

HILO1


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Many Large US Companies Internally Price Carbon

Do U.S. companies view energy and carbon emissions management as being strategic, and are they taking actions to back this up?

On the one hand, business lobbying groups such as the U.S. Chamber of Commerce don’t think government should be involved in pricing carbon emissions:

In a letter to Congress, the Chamber, which represents more than 3 million businesses, says the Clean Air Act is “not the appropriate vehicle to regulate greenhouse gas emissions” and warns the EPA’s GHG emissions limits for power plants will raise power prices with “negative implications extending to nearly every segment of the economy.”

On the other hand, CDP disclosures indicate that some major US companies appear to be self-regulating:

Twenty-nine major publicly traded companies based in or operating in the U.S. disclosed an internal price on carbon pollution to CDP (formerly known as the Carbon Disclosure Project) in 2013, detailing both the risk and potential business opportunity for early action by their companies.

What does this mean in practice? It’s possible that these 29 firms (and possibly others which price carbon but chose not to disclosure it) are using these prices in investment decisions. This means that these companies are taking actions to back up beliefs about carbon emissions pricing and the impact on the cost of doing business going forward. It also means that information systems for capturing, storing, analyzing, and reporting such data (which I call Carbon Management Systems) are becoming increasingly strategic.


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Big (Smart Meter) Data: 1 billion data points per day and counting

According to the Edison Foundation, in the U.S. alone there are over 46 million smart meters installed as of July 2013.

At a read rate of 24 per day, this equals to about 1.1 billion data points per day, or just north of 400 billion per year.

What to do with all this data?

Greentechmedia reports that at the recent Soft Grid 2013 conference, several views were shared:

This is the beginning of a very long evolution that may or may not end in our lifetimes

- Josh Gerber, smart grid manager for San Diego Gas & Electric

You have to reach out to those customers and give them something that interests them

- Scott Young, senior director of software platforms for Silver Spring Networks

Other examples that I quote from the greentechmedia article include:

  • analyze household power usage data to help customers learn where they’re wasting energy, how different appliances are affecting their usage, and the like — in other words, to turn utilities into “trusted energy advisors” to their customers.
  • predict individual customers’ likelihood to want to sign up for load curtailment programs (demand response), or perhaps install solar panels on their property.
  • pairing third-party information of the kind you might get from the retail and customer service bid data world with the usage details … from their meters

This is a new scale of data, and extracting valuable insights will require thoughtful pairing of user needs with technological capabilities to create compelling new services. In other words, turning data into information and knowledge for better decision making. It can’t happen fast enough.

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