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Welcome to the New Enlightened World of Sustainability – How Big Data Will Help Achieve Sustainability Goals

According to a recent McKinsey study on Big Data and innovation, “The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future.”   There is -- and will be -- an ever increasing wealth of information to be mined from data generated by applications, people, mobile devices, smart meters, industrial machines, automobiles, etc.  It is structured and unstructured data.  It is increasingly social in nature.  It is enriched with geospatial information.

And it is accelerating.  The worldwide digital content will double in the next 18 months. 

As we look at Big Data through the lens of energy and sustainable operations, the questions are obvious.  How do we harness this data to run businesses more sustainably and profitably?   How will this data explosion enable new strategies?  What are the technology trends underpinning our ability to access and use Big Data?

We see companies looking to leverage this data to successfully reach sustainability goals and improve their profitability as they do so.  The use cases are numerous.  If we leverage the data appropriately, we will have an increased opportunity to avoid deadly and costly accidents; ensure consumers are buying safe and eco-friendly products; lower product costs by controlling energy consumption and spend; provide timely transparency into corporate social responsibility initiatives; and create more accountability across the supply chain.  The focus of this piece is on several use cases where Big Data presents both the biggest opportunities and the biggest challenges.

Before getting started with these use cases, let’s take a look at new technologies that are allowing us to access and use “Big Data” in real time. Traditionally, analytic applications run on databases that store all their information on disk. To get that data out, you need to extract, massage and store the information in a data warehouse designed to analyze a particular business problem. Those databases typically only include structured data – or data from business applications. Now we have newer technologies that help us analyze unstructured data generated by anything from an e-mail to Twitter to a motion sensor – and to do it on the fly.   One of the key technologies is something called in-memory computing which essentially allows companies to bypass the physical limitations of traditional disk-based databases and store it in a virtualized, in-memory database. This allows massive amounts of data to be stored, accessed and then sliced and diced at a very detailed level – all in real time. By breaking the deadlock between flexibility, granularity and speed, we’re able to address problems in completely new ways.

Let’s now look at how this enables us to approach companies’ sustainability challenges in ways not possible previously.

First, in-memory technology will enable radical improvements in energy usage. 

From the supply side, smart grids provide the promise for utilities and consumers to increase their collaboration to ensure the delivery of safe, reliable, secure, and clean energy.  However, the addition of smart meter data fundamentally changes data intensity – moving from 12 monthly readings to over 35,000 measurements per year, per household.  This data is then increasingly enriched with customer attributes, weather information, and other data.  In-memory technology is critical to the aggregation, benchmarking, and pattern recognition required to analyze this data – with some queries 15,000 times faster than traditional analytics. With this technology, utilities can more effectively provide energy services, conduct leakage analysis, avoid bill shock through better communication, and offer demand side management activities that help consumers concerned with environmental and energy resource management. 

From the demand side, we see the opportunity to provide industrial manufacturers real-time visibility into their energy consumption, converted into costs, translated into CO2 equivalents and allocated to cost centers.  This energy accounting will enable new scenarios for both lowering consumption levels and costs.  It will be a win-win for business and the environment.

Second, in-memory based analytics will greatly improve manufacturers’ ability to understand the exact composition of their products and identify chemicals or components that are either dangerous or non-compliant with regulations like REACH or ROHS.  For example, imagine you are a fragrance company with half a million products and chemical formulas. These companies require instant visibility at granular level to ensure the safety of their product, understand geographic regions to which a product can be marketed, and avoid potential regulatory fines or hits to brand reputation.  How does big data help here?   It is critical that the compliance checks occur up-front in the product selection and development process to avoid downstream issues.  These checks become increasingly difficult as the number of government, industry, and customer compliance requirements increase.  In-memory technology can provide the analytical power required to keep the checks to only a couple of minutes enabling perfumers to maintain compliance responsibility in designing new fragrances and flavors.  Harnessing Big Data in this instance is an opportunity to both develop compliant products and contribute to meeting their sustainable corporate strategies.

Third, Big Data technologies can help mitigate risk to operations in industries like transportation, oil and drilling or mining. These are areas where very public accidents are often deadly, can cause massive environmental damage, and are costly both in terms of interrupting business-as-usual and managing the after-effects.  In-memory technology will enable greater predictive capabilities, critical to providing increased data enabling the creation of safety cultures.  For example, the combination of flight data, weather information, maintenance records, and employee training has the ability to create a step-wise improvement in flight safety.

As corporations strive to deliver against publicly stated sustainability commitments (including transparency), they need to accurately and quickly analyze their progress.  Over the last few years, sustainability has become embedded into all lines of business.  Every process in the enterprise – develop, buy, make, ship, sell – requires sustainability data.   We are excited to be working with corporations across industries around the globe in leveraging innovation in Big Data to accelerate competitiveness through improved energy management and more sustainable operations.


Scott works in SAP’s Sustainability Organization, where he leads a core team of experts defining SAP’s overall sustainability strategy – both for SAP’s internal performance and for its solutions which enable customers to achieve greater sustainability performance.  He also ensures… [Read more about Scott Bolick]


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