Written by Pamela Rucker, CIO Advisor and Instructor, Harvard Professional Development

ESG (Environmental, Social, and Governance) topics have emerged as critical issues for organizations of all sizes. Among those issues, sustainability has seen a surge of interest, rising steadily on CIOs’ priority lists. Via a series of interviews and panels at Schneider Electric’s Innovation Summit 2022, a snapshot of the challenges, triumphs, and next steps shows that IT and business leaders are focused as never before on data center sustainability. But it’s going to require unprecedented cooperation among all stakeholders to drive change.

With a stellar line up of speakers and sustainability topics, Schneider Electric demonstrated recently that they are not simply a leader that sells commercial sustainability solutions. At its annual Innovation Summit in Las Vegas, NV., the company showed that its investments in emerging technology, educational programs, and ecosystem partners are the result of a deep commitment to create competitive advantage for themselves and their customers with an eye squarely focused on the triple bottom line. 

While watching the demonstrations, it was obvious that the sheer magnitude of their sustainable innovation is a feat in and of itself; however, even greater power lies in the fact that Schneider’s products and services make other companies better too. Their theme of “Digital + Electric = Sustainability” represents a real opportunity for companies to pivot away from products and processes that offer profit with a high environmental price tag. And that’s where I found myself mesmerized by the possibilities. 

One of the biggest challenges I see organizations grappling with is having the right capability when it counts. We are living in a world faced not only with the impact of climate change, but also with the impact of a changing demographic. Schneider’s CEO, Jean-Pascal Tricoire, opened with a keynote that declares “The Moment is Now,” and he couldn’t be more accurate in that statement. Numerous studies have found that today’s consumers want to buy products and services from companies that not only care about ESG, but can prove that they’re doing something about it. Panelists at the conference noted that 75% of people would select a company based on their ESG goals, and 85% would stay loyal to them. That’s a staggering statistic, and it means that people want to buy from companies that have similar values as theirs, and they’ll also refuse to bring their talents to places that don’t engage in meaningful change. 

Getting Started: Steps for Meaningful Change

The problem most companies have though, is where to start. This is where Schneider shines. They have published a framework to help leaders know what specific steps they can take right now to make meaningful change. In a great discussion about partnerships, metrics, and redefining data center sustainability, the group noted that data runs the planet, and that is true. We have bigger and bigger data centers because we rely on more and more data to get things done. Our obsession with instant searches, free information, and two-day delivery has come at an incredible cost. Humans can’t work that fast, so we need machines to do it, and those machines require energy. The group went on to note that even when we try to work in ways that use less energy, we are impacting the water supply. So, one definite way to reduce any environmental impact is to tackle the way data centers are managed, and to require a similar type of management from partners.

Look, every company today will build, buy, sell, or service their products using a digital process. That means every company should be capturing data about how they operate. All of that data ends up in a data center somewhere: with you, your partners, or your suppliers. I agree with final thoughts of the panel: You can’t understand and address the full impact of your operations unless you work with partners that are digitized and have similar goals as yours. Even if they aren’t there today, they have to want to get there, and be willing to do the work now.

In a world that’s becoming more digital every moment, we all need ways to understand and address the impact of our desires. The devices we watch, the dances we post, the data we consume all create footprints that must be managed. While Schneider’s tools can’t change the world overnight, they can help keep us honest about our promise to do better. And that’s action we can all be glad about. 

This post is brought to you by Schneider Electric and CIO Marketing Services. The views and opinions expressed herein are those of the author and do not necessarily represent the views and opinions of Schneider Electric. 

To learn more about Schneider Electric’s ESG solutions, click here.

Data Center

The benefits of analyzing vast amounts of data, long-term or in real-time, has captured the attention of businesses of all sizes. Big data analytics has moved beyond the rarified domain of government and university research environments equipped with supercomputers to include businesses of all kinds that are using modern high performance computing (HPC) solutions to get their analytics jobs done. Its big data meets HPC ― otherwise known as high performance data analytics. 

Bigger, Faster, More Compute-intensive Data Analytics

Big data analytics has relied on HPC infrastructure for many years to handle data mining processes. Today, parallel processing solutions handle massive amounts of data and run powerful analytics software that uses artificial intelligence (AI) and machine learning (ML) for highly demanding jobs.

A report by Intersect360 Research found that “Traditionally, most HPC applications have been deterministic; given a set of inputs, the computer program performs calculations to determine an answer. Machine learning represents another type of applications that is experiential; the application makes predictions about new or current data based on patterns seen in the past.”

This shift to AI, ML, large data sets, and more compute-intensive analytical calculations has contributed to the growth of the global high performance data analytics market, which was valued at $48.28 billion in 2020 and is projected to grow to $187.57 billion in 2026, according to research by Mordor Intelligence. “Analytics and AI require immensely powerful processes across compute, networking and storage,” the report explained. “As a result, more companies are increasingly using HPC solutions for AI-enabled innovation and productivity.”

Benefits and ROI

Millions of businesses need to deploy advanced analytics at the speed of events. A subset of these organizations will require high performance data analytics solutions. Those HPC solutions and architectures will benefit from the integration of diverse datasets from on-premise to edge to cloud. The use of new sources of data from the Internet of Things to empower customer interactions and other departments will provide a further competitive advantage to many businesses. Simplified analytics platforms that are user-friendly resources open to every employee, customer, and partner will change the responsibilities and roles of countless professions.

How does a business calculate the return on investment (ROI) of high performance data analytics? It varies with different use cases.

For analytics used to help increase operational efficiency, key performance indicators (KPIs) contributing to ROI may include downtime, cost savings, time-to-market, and production volume. For sales and marketing, KPIs may include sales volume, average deal size, revenue by campaign, and churn rate. For analytics used to detect fraud, KPIs may include number of fraud attempts, chargebacks, and order approval rates. In a healthcare environment, analytics used to improve patient outcomes might include key performance indicators that track cost of care, emergency room wait times, hospital readmissions, and billing errors.

Customer Success Stories

Combining data analytics with HPC:

A technology firm applies AI, machine learning, and data analytics to client drug diversion data from acute, specialty, and long-term care facilities and delivers insights within five minutes of receiving new data while maintaining a HPC environment with 99.99% uptime to comply with service level agreements (SLAs).A research university was able to tap into 2 petabytes of data across two HPC clusters with 13,080 cores to create a mathematical model to predict behavior during the COVID-19 pandemic.A technology services provider is able to inspect 124 moving railcars ― a 120% reduction in inspection time ― and transmit results in eight minutes, based on processing and analyzing 1.31 terabytes of data per day.A race car designer is able to process and analyze 100,000 data points per second per car ― one billion in a two-hour race ― that are used by digital twins running hundreds of different race scenarios to inform design modifications and racing strategy.  Scientists at a university research center are able to utilize hundreds of terabytes of data, processed at I/O speeds of 200 Gbps, to conduct cosmological research into the origins of the universe.

Data Scientists are Part of the Equation

High performance data analytics is gaining stature as more and more data is being collected.  Beyond the data and HPC systems, it takes expertise to recognize and champion the value of this data. According to Datamation, “The rise of chief data officers and chief analytics officers is the clearest indication that analytics has moved from the backroom to the boardroom, and more and more often it’s data experts that are setting strategy.” 

No wonder skilled data analysts continue to be among the most in-demand professionals in the world. The U.S. Bureau of Labor Statistics predicts that the field will be among the fastest-growing occupations for the next decade, with 11.5 million new jobs by 2026. 

For more information read “Unleash data-driven insights and opportunities with analytics: How organizations are unlocking the value of their data capital from edge to core to cloud” from Dell Technologies. 


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Data Management