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Getting Started with Sustainability Analytics 

Companies must prioritize and address the gap between what has been said with sustainability efforts and what has been done to align corporate strategies with gathered data and analytics. 90% of executives think that sustainability is important, but only 60% have a defined sustainability strategy. Focusing on specific efforts is one way to help bridge that gap and turn statements into actions and enables leaders to make strategic decisions and create change within their organizations. Sustainability analytics can create new opportunities in strategy (roles, processes), become a company’s competitive advantage, and be a long-term investment as society becomes more inclined to take environmental impact into consideration. 

What Are Sustainability Analytics? 

Sustainability has moved far beyond the traditional definition of environmental impact, and now includes social and economic factors along with ecological impacts. Analytics intersects with sustainability as organizations evaluate their current state processes and identify ways to improve.  

Sustainability analytics can help make data driven decisions. By analyzing a variety of metrics, this helps improve the following: 

  • Material and Resource Usage: Reduction of greenhouse gas emissions, energy, waste, and water. 
  • Product Development and Efficiency: Better manage research and development, warehouse productivity, and supply chain efficiency. 
  • Partnership with Other Organizations: Provide a benefit of working together in global and local communities. 
  • Growth and Financial Health: Identify cost savings and create strategic sustainability goals. 
  • Risk Mitigation: Pursue potential negative environmental, social, or financial areas to combat large-scale disasters. 

Organizations are making their efforts known. Below are some examples of companies that are making sustainability movements and are benefiting from using analytics: 

  • Apple has been moving towards sustainability and carbon neutrality for years. Their product release events have been further showing their dedication to the environment, but they also publish regular progress reports to their goal of complete carbon neutrality. Apple focuses heavily on data to measure and track their progress towards goals. Whether it’s how many metric tons of material are expected to be saved by removing power adapters, reduction of product energy to lower carbon impact, or increase the usage of recycled aluminum, Apple is creating ways to improve its global environmental footprint by using data.  
  • In 2020, Roche was recognized as the most sustainable pharmaceutical company of the Dow Jones Sustainability Indices. Roche broadens sustainability beyond just environmental impacts, but also looks at social responsibility and governance efforts. They use data to evaluate their employee demographics to ensure that minorities in the workplace are elevated to leadership roles and match the population. 
  • Philip Morris International has leveraged data to create the “Our World is Not an Ashtray” movement. This effort highlights the impacts of improperly disposed cigarette butts and encourages their customers to properly dispose of their litter. The website shows the results of this litter on the world, and helps connect visitors to resources to learn more or help clean up the mess.  

What Data Do You Need for Sustainability Analytics? 

The data required will vary based on each organization’s sustainability goals. This can include data from both the manufacture and transport of products. The amount of water, energy, and byproducts of the manufacturing process are all valuable inputs in any environmental impact study. This data can come from owned factories, but some may have to be sourced from suppliers for both raw material and finished goods. Similarly, transportation data of distance and method can be reviewed to determine carbon emissions, and then strategies to reduce. 

To further improve these sorts of analyses, organizations could seek to gather lower-level data. Leveraging flexible data storage, machine and manufacturing line level data can be captured to identify machines or lines that may not be operating as efficiently as others and overproduce waste. Companies may already have data on the required volume of inputs in manufacturing, but they may not know what yield, or the waste amounts are for each step. This data could be collected to further drill down and make processes more efficient both from a sustainability and cost perspective.   

Beyond that, organizations could seek out 3rd party customer sentiment data to evaluate public opinion of their efforts. These data could also be collected via survey or other in-house methods, and then run through advanced sentiment models to measure the effectiveness of sustainability initiatives. There are also benchmarking services that can provide data for environmental impact to compare your performance against organizations within the same industry and beyond. 

Most organizations already have a large portion of data required to do this analysis, depending on their goals. Creating partnerships with vendors / suppliers and acquisition through 3rd party data can be leveraged to help make the analysis more comprehensive. 

Final Considerations 

Growing investor and consumer sentiment is forcing companies to make more targeted approaches to sustainability. Organizations increasingly seek out analytics as a way to identify and measure sustainability initiatives, helping them move from reactive practices to be more proactive ones. Sustainability analytics can demonstrate measurable steps a company is taking to improve the world around them, impacting policy, consumption, and economic development within their local areas, as well as globally.  

Being informed of this data and highlighting insights will allow companies to take smarter actions in the ever-changing ecosystem of government policies, economic factors, and technological advancements.

Contributions by Brandon Regnerus and Hannah Kim 

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Tags: Data & Analytics, Data Analytics & Insights, Data Strategy, Sustainability