By Michael Koploy, Analyst for SoftwareAdvice.com

According to a study from the MIT Sloan Management Review, two-out-of-three executives believe that sustainability is required to stay competitive in today’s business environment. Additionally, seven-out-of-ten said that sustainability has earned a permanent spot on the corporate agenda.

David Schatsky astutely points out, however, that sustainability goals aren’t created equally. In an article on Environmental Leader from July 2011, he defines the most powerful sustainability goals as aggressive, public, quantitative, and future-thinking.

Sustainability initiatives must be measured, benchmarked, analyzed and acted upon. This is best achieved through data collection automation, analysis with business intelligence tools, and crafting sustainability teams around data-minded and analytical individuals.

The Benefits of Automated Data Collection

As companies are being asked to prepare for strict regulations on emissions–such as the proposed 80 percent reduction of CO2 for U.K. businesses by 2050–continual progress with ensure that companies are ready once regulations are enforced.

To do this, quantifiable data is necessary. But SAP’s Senior Sustainability Solution Manager Kevin Ramm notes that many businesses suffer from data that is “incomplete”–lacking information from every activity within the corporation.

“Data collection continues to be a major challenge,” says Ramm. “But sustainability benefits from good data–information that is timely, pertinent, relevant and has the right degree of robustness.”

Ramm suggests that businesses move away from manual data collection and instead toward automated systems. This way, it’s less laborious to collect the information, the data is less prone to human errors and information can be updated in (almost) real-time.

Business Intelligence Tools Assists Analysis

Data holds little intrinsic value if it cannot be analyzed. Even if a business accurately collects data and measures the right Key Performance Indicators (KPIs)–greenhouse gas emissions, carbon footprints, et cetera–the ability to pick out trends and make informed decisions will separate the best from the rest.

The answer is Business Intelligence (BI) applications, or software systems designed to analyze large, convoluted sets of data. These applications have been used by companies for years to analyze their “big data” issues. However, a number of trends within the BI software market are leading to these systems becoming much more usable by sustainability teams:

• In-memory processing, or the ability for users to conduct analysis directly rather than having to ask data architects and/or IT teams to process the data, means users can more quickly and dynamically ask questions about their progress within sustainability projects.
• Better data visualization modules means that users will be able to quickly find “outliers” in the data. In addition, visualization will make it easier to present data to management in a way that is easily digestible and actionable.
• Improved collaboration functionality with mobile device deployment and interactive analysis modules. Users in the field and in the corporate office will be able to communicate and access the results of data analysis.

Data-Minded Sustainability Teams Lead to Accountability, Results

By benchmarking sustainability and accurately analyzing the impact, sustainability will move from an altruistic project to a strategic and proactive initiative. However, this means that corporate executives will require these teams to be accountable for the results of sustainability projects–as both the impact on planet and profit will be easily obtainable.

The end result, though, will mean sustainability teams that are more accountable, business that are more accountable, and a world that is more accountable.

Tags: automation, BI, Business Intelligence, collection, data, Michael Koploy, sustainability