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SAP at WiDS: It’s Not About the Data, It’s About the Science

Feature Article | February 8, 2017 by Christiane Kubach

SAP has launched a movement to inspire women with data science and find solutions to the UN Global Goals.

SAP is leading a joint movement to inspire young women to pursue education and careers in data science. The initiative is driven by Ann Rosenberg, vice president and head of Global SAP University Alliances. “Women learn best through a community,” Rosenberg says.

The movement was launched last week at the Women in Data Science (WiDS) conference, where Rosenberg is SAP’s global ambassador for the event in partnership with Stanford University’s Institute for Computational & Mathematical Engineering (ICME).

One of the speakers at the event was Sinead Kaiya, COO of Products & Innovation at SAP: “We all have to act to save our fragile planet earth and business is not sitting still.”

According to Kaiya, we are at an inflection point and data is a given. To truly change the world, we need to start applying science to this data and solve today’s big problems like climate change and food waste or more business-related, efficient global productivity.

In the past, company leaders may have made decisions mainly based on their gut feeling. This is not possible anymore as problems are just too complex. Data is not the problem, Kaiya stated, the problem is gaining the right and timely insights from the raw data. “It’s not about the data, it’s about the science,” she explained. “This would change the way how business is done in the future.”

Take the “Barcode of Life” as an example. The international organization of institutions across 26 nations wants to build a database of DNA barcode for every type of species on the planet.

SAP collaborated with the Barcode of Life project on multiple fronts. The company co-developed a citizen science mobile application called “LifeScanner” that allows citizen scientists to discover the amazing Barcode of Life dataset that contains over 4 million DNA barcodes to data. SAP also worked on a pilot with the FDA and the Biodiversity Institution of Ontario (BIO) on a regulatory solution for biomaterial sample collecting and analysis including accelerating steps within the genomics computational pipeline using SAP HANA. With the data available, its business applications are becoming obvious, for example in uncovering food fraud or identifying and tracking invading species.


WiDS conference sponsors included SAP, Google, Microsoft, and Walmart Labs, which partnered with Stanford’s ICME on the WiDS conference at Stanford’s main campus and at over 75 locations worldwide.

The SAP Next-Gen team organized 24 events at SAP offices and SAP Next-Gen campuses. The talks from the conference in Stanford were broadcast at satellite events and more than 90 SAP speakers gave perspective in live talks at the locations. More than 2,500 people participated in these satellite sessions. From New York, Berlin, Shanghai, and ​São Leopoldo to Silicon Valley California and Silicon Plateau India, participants met and were inspired by talks from SAP speakers and the live broadcast from Stanford.


Diverse Ideas to Save the World

Business Beyond Bias was an inspiring example to the audience. Diversity and inclusion in the workplace are no longer optional; they are a business and economic imperative. Business Beyond Bias is a comprehensive, highly integrated company-wide initiative focused on SAP’s leadership and commitment to enable an inclusive culture for better business results, starting inside the own company.

This is why SAP SuccessFactors came up, with features in the HCM portfolio to detect unconscious bias and ultimately prevent it, at every step of the HR lifecycle, and making use of machine learning. For example in recruiting, the use of machine learning can take human bias out of resume screening. To get there, it requires a team as diverse as possible to define the science behind the data, Kaiya pointed out.

Why We Need Women in Data Science

All these examples are based on the value that data science adds to the pure technology. Kaiya concluded her talk with the question why we need women in data science. Industries went through three major revolutions in the past but today’s problems would require a more diverse and multidisciplinary approach to make the fourth industrial revolution happen.

On top of technical skills, curiosity, creativity, and strong communication skills are required to build connections and eventually asking the right, unbiased questions and gaining new insights. According to Kaiya: “Choices that we make today will decide about our planet. We need as many diverse ideas as possible to save our world.”

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