The Industrial Data Revolution At GE

We talk to Beena Ammanath about her role and women in STEM


Beena Ammanath is the Executive Director of Data Science Products & Delivery at GE. She is also Board Director at ChickTech, a nonprofit organization dedicated to retaining women in the technology workforce and increasing the number of women and girls pursuing technology-based careers. She has spent over 24 years experience within data analysis, having held jobs at British Telecom, E*trade, Thomson Reuters and several Silicon Valley startups, in both engineering and management positions. We spoke to her about some of the changes she’s seen in the industry ahead of her keynote presentations at the Chief Data Officer Summit and Women in STEM Summit  both taking place in San Francisco later this month.

Her work at GE is primarily focused in the industrial space, and her team leverages big data for insights that make machines smarter, for example - help reduce unpredicted failure in jet engines, and prevent flight delays.

Big data in industrial companies is very different than its consumer-focused counterpart, and there are far higher stakes involved. Beena notes that, in the industrial space, ’network latency requirements are far higher, and security and governance is more stringent than in consumer markets. However the outcomes are also more impactful. In the consumer space, if your algorithm is slightly wrong, a user gets the wrong ad displayed. In the industrial space, if the algorithm is not trained well, it can result in flight delays, MRI machines don’t work or power failures occur. There are far more severe consequences, and different challenges to ensure it all runs smoothly, what data you can use, and what data you cannot use.’

Nowhere is this truer than at GE. GE is a large multi billion-dollar company. As a consequence, it has many data silos to deal with; a vast array of different rules around data quality and data management, and the data strategies are far more complicated than at a small company.

Beena went on to describe how the data evolution has happened over the past few decades. 30 years ago, it used to be around transaction systems data, when storage was extremely expensive, and the data structures were optimized and normalized to make best use of storage and faster response time.

Then, around 15 years ago, we saw the next phase of data evolution with BI and data warehousing - dimensional modeling, the focus was on organizing data in a way to run faster reports. Beena thinks that we’re now in the 3rd wave of data evolution, where we are looking at completely new data sets to derive insights of the data. Each wave builds on top of the previous one.

While none of these will fade out, as they are all needed to run your business effectively, the next phase will be capturing the context of data - going beyond your company data space - driven by an increase in open data sharing and crowdsourcing.

There is one real area of change that Beena is passionate about though - Women in STEM. She says that the situation holding women back is two-fold – getting girls interested in a career in STEM and retaining the mid-career women who are already in STEM careers.

Beena notes that there are very few technical women executives and leaders, and she will often walk into a meeting and it’s 25 of her male peers and her. As a side effect of this, there are also very few role models for women in STEM. The issue really needs to be addressed at every level. Not enough focus is put on retaining mid-career women, and getting them back into the workforce after a major life event.

The benefits to having more women in the technology workforce, however, are profound. ’Women bring a completely different perspective to the table compared to men, and the more diversity you have, the stronger your products are, especially in software’. Despite this, she hasn’t seen the situation change much throughout her career. “You don’t see too much of a change in terms of actual diversity numbers, but there is definitely more awareness now. The conversations are at least happening openly now, the diversity issue is now out in the open and I hope that we’ll see changes soon. In another 10 years, I hope to see roughly equal number of men and women in any STEM leadership discussion and roughly equal number of men and women speakers at the Chief Data Officer Summit.”

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