"We all should learn to esteem diverse personal qualities and recognize their value for the team." – According to Helene Staader, Chief Product Owner at SAP AI, this is one of the keys to establishing diverse work teams and, with that, reaching balance and equality that empowers employees.
Read along to learn about her perspective on what SAP needs to do to support women's careers in the tech industry and what she experienced during her journey in a job where she combines technical, product management, and leadership skills!
My current job at SAP is the perfect match for everyone who wants to combine technical skills and interests with product management and leadership. I am a Chief Product Owner. My team is responsible for improving machine learning (ML) services' development process and developer experience by providing products, tools, processes, and best practices. My main task is coordinating all activities, which means aligning the strategy, new requirements, and priorities with the product manager, maintaining backlog, planning accordingly, and being accountable for the deliveries. The required skills are widely diversified. Understanding the ML development process and technologies used in this area and market trends is essential. Secondly, a knowledge of software engineering (tools and processes) is necessary as well. And finally, the leadership qualities. For me, it is a perfect mixture of different tasks that never get boring.
Honestly, I didn't look actively for a job in the AI area. Like very often in life, you must grab the opportunity that comes along your way. After being a developer for ten years, I got a chance to work on a product that provides operations analytics for IT and be responsible for a prediction component. As a mathematician, I was well prepared to read and understand scientific papers, but data science is much more than that. I lacked practical skills in using the tools and methods. So, in 2016, I decided to apply for a fellowship in a newly created ML organization (Bernd Leukert, Member of the SAP Executive Board at that time, himself announced this fellowship program, so it was clear that this would be the next important innovation area SAP would invest in). I was lucky to get one of these highly coveted fellow positions and joined the team where I am still working since then. Initially, I wanted to improve my data science skills but what I found in my new team matches my skills and interests much more. The idea was to build a platform for data scientists and software engineers who can easily and in a standardized way productize, reuse, and operate ML use cases. This was a perfect match to connect my experience in Life Cycle Management (I previously worked eight years in the LM area), software engineering, and data science. Our mission was not to solve a concrete ML problem but to help data scientists to bring their solutions into production. So, I grabbed the opportunity with both hands and became a product owner in the Walldorf team very soon, and since 2020 got the responsibility as Chief Product Officer (CPO) for the whole AI Workbench team.
I want to pick two emerging AI trends that are tremendously important for SAP and related to what my team is responsible for. The first one is "low code, no code AI". The idea of "low code no code platforms" is hopefully self-explaining. With such platforms, companies want to make application development easier (and, with that, reduce costs) and more scalable. The developers don't have to write code at all or just less code, and the platform will automate the rest. In the past, AI development was a privilege for a few specialists with a deep knowledge of ML frameworks. Productization and management of such ML scenarios was a tedious manual effort. Our content package concept should help lower the barrier to successfully starting with AI development by using prepackaged AI solutions to adjust to your needs.
And the second trend I would like to point out is MLOps. One of AI adoption's main problems is that only a few ML projects make it from the experimentation phase into production. And if so, it will take, on average, nine months (according to Gartner). Operationalization is the magic word to accelerate AI adoption and growth.
The first step is always the hardest, people say. I am very proud of how we successfully managed all the challenges and pressure as a newly created team. It all started with that small group of around ten people in 2016. What happened in the following years was breathtaking. Our first product ML Foundation was announced at TechEd 2016 by Bernd Leukert, and we had only half a year to deliver the first increment of the product, which was planned to be launched on SAPPHIRE 2017. We tripled our team size and delivered our first services this time. This startup-like environment was new to me, and I was very enthusiastic and inspired by it. In general, there was great excitement and interest around the AI topic internally as well as on the customer side. We got much visibility at several events and provided many enablement sessions worldwide. What a fantastic but also challenging time! And to all my team members: I am so proud and happy to be part of this team!
In my 18 years at SAP, there were a lot of memorable moments. My most incredible memories are all about the community and people. It's about intense workshops with my team where we discuss the way forward. It's about the customer events where you can see and feel the positive impact of our products on their business. It's about fun with my colleagues inside and outside the office. It's about all the great Christmas-, Summer-, special Release-parties, annual works outings etc. This great community is pushing my motivation again and again. It might sound like a corny advertisement, but this is how I feel about the big SAP family 😊
I was lucky to feel encouraged and empowered by my managers. I know this is not always the case for women. I recognized it many years ago when I did a training about gender awareness. It was an eye-opener for me. In this training, we discussed the typically female and male characteristics (nota bene: we all are individuals and can have any of these characteristics independent of the physical gender 😉) and how it impacts our careers. And I learned how many women feel not valued and overseen. It helped me to reflect on how I act in certain situations and how my (mostly male) colleagues could perceive it. It doesn’t mean I changed my behavior to fit into the “male business world” because this is unnecessary and not desired! On the contrary, if we strive for balance in the teams, we all should learn to esteem diverse personal qualities and recognize their value for the team. The key, in my opinion, is awareness about ourselves and empathy to others.
What can SAP do to support women’s careers in the tech industry? In general, I think SAP is on the right way. I believe it must start much earlier: in the families, schools, and further professional education. Society should prioritize this topic so that women don’t get the impression from the beginning that they are inferior to men regarding technical understanding. And SAP should continue to talk about it, to spread awareness and, with that, create a mindset of equality and balance.
At this point, I would like to emphasize that, especially in our AI organization, I experienced a very strong focus on diversity (both gender and ethnicity), and I love it! If you didn’t experience working with such a highly diverse team, you don’t know what you missed. I perceive such teams as very balanced, with a pleasant working atmosphere and the best performances. This is the way to go! 😊
Thank you very much for sharing these exciting insights, Helene! We highly appreciate getting to know the perspective of another female colleague in the tech area and are sure to have answered many questions that women may ask themselves when planning their careers. You can learn more in our previous interviews with Jana Würth and Haodan Yang, who also gave us inspiring insights into their work at SAP AI!
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Read along to learn about her perspective on what SAP needs to do to support women's careers in the tech industry and what she experienced during her journey in a job where she combines technical, product management, and leadership skills!
Can you describe your daily job at SAP?
My current job at SAP is the perfect match for everyone who wants to combine technical skills and interests with product management and leadership. I am a Chief Product Owner. My team is responsible for improving machine learning (ML) services' development process and developer experience by providing products, tools, processes, and best practices. My main task is coordinating all activities, which means aligning the strategy, new requirements, and priorities with the product manager, maintaining backlog, planning accordingly, and being accountable for the deliveries. The required skills are widely diversified. Understanding the ML development process and technologies used in this area and market trends is essential. Secondly, a knowledge of software engineering (tools and processes) is necessary as well. And finally, the leadership qualities. For me, it is a perfect mixture of different tasks that never get boring.
How did you enter the field of artificial intelligence (AI)? What initially sparked your interest in this topic?
Honestly, I didn't look actively for a job in the AI area. Like very often in life, you must grab the opportunity that comes along your way. After being a developer for ten years, I got a chance to work on a product that provides operations analytics for IT and be responsible for a prediction component. As a mathematician, I was well prepared to read and understand scientific papers, but data science is much more than that. I lacked practical skills in using the tools and methods. So, in 2016, I decided to apply for a fellowship in a newly created ML organization (Bernd Leukert, Member of the SAP Executive Board at that time, himself announced this fellowship program, so it was clear that this would be the next important innovation area SAP would invest in). I was lucky to get one of these highly coveted fellow positions and joined the team where I am still working since then. Initially, I wanted to improve my data science skills but what I found in my new team matches my skills and interests much more. The idea was to build a platform for data scientists and software engineers who can easily and in a standardized way productize, reuse, and operate ML use cases. This was a perfect match to connect my experience in Life Cycle Management (I previously worked eight years in the LM area), software engineering, and data science. Our mission was not to solve a concrete ML problem but to help data scientists to bring their solutions into production. So, I grabbed the opportunity with both hands and became a product owner in the Walldorf team very soon, and since 2020 got the responsibility as Chief Product Officer (CPO) for the whole AI Workbench team.
What are the most important trends you already see emerging in AI? What are its future possibilities?
I want to pick two emerging AI trends that are tremendously important for SAP and related to what my team is responsible for. The first one is "low code, no code AI". The idea of "low code no code platforms" is hopefully self-explaining. With such platforms, companies want to make application development easier (and, with that, reduce costs) and more scalable. The developers don't have to write code at all or just less code, and the platform will automate the rest. In the past, AI development was a privilege for a few specialists with a deep knowledge of ML frameworks. Productization and management of such ML scenarios was a tedious manual effort. Our content package concept should help lower the barrier to successfully starting with AI development by using prepackaged AI solutions to adjust to your needs.
And the second trend I would like to point out is MLOps. One of AI adoption's main problems is that only a few ML projects make it from the experimentation phase into production. And if so, it will take, on average, nine months (according to Gartner). Operationalization is the magic word to accelerate AI adoption and growth.
What's the accomplishment you are most proud of?
The first step is always the hardest, people say. I am very proud of how we successfully managed all the challenges and pressure as a newly created team. It all started with that small group of around ten people in 2016. What happened in the following years was breathtaking. Our first product ML Foundation was announced at TechEd 2016 by Bernd Leukert, and we had only half a year to deliver the first increment of the product, which was planned to be launched on SAPPHIRE 2017. We tripled our team size and delivered our first services this time. This startup-like environment was new to me, and I was very enthusiastic and inspired by it. In general, there was great excitement and interest around the AI topic internally as well as on the customer side. We got much visibility at several events and provided many enablement sessions worldwide. What a fantastic but also challenging time! And to all my team members: I am so proud and happy to be part of this team!
Any great memories working at SAP that you'd like to share with us?
In my 18 years at SAP, there were a lot of memorable moments. My most incredible memories are all about the community and people. It's about intense workshops with my team where we discuss the way forward. It's about the customer events where you can see and feel the positive impact of our products on their business. It's about fun with my colleagues inside and outside the office. It's about all the great Christmas-, Summer-, special Release-parties, annual works outings etc. This great community is pushing my motivation again and again. It might sound like a corny advertisement, but this is how I feel about the big SAP family 😊
Wow, your significant role in driving major innovations is empowering! What have you experienced along this journey in terms of diversity? What do you believe SAP needs to (continue to) focus on to support women's careers in the tech industry?
I was lucky to feel encouraged and empowered by my managers. I know this is not always the case for women. I recognized it many years ago when I did a training about gender awareness. It was an eye-opener for me. In this training, we discussed the typically female and male characteristics (nota bene: we all are individuals and can have any of these characteristics independent of the physical gender 😉) and how it impacts our careers. And I learned how many women feel not valued and overseen. It helped me to reflect on how I act in certain situations and how my (mostly male) colleagues could perceive it. It doesn’t mean I changed my behavior to fit into the “male business world” because this is unnecessary and not desired! On the contrary, if we strive for balance in the teams, we all should learn to esteem diverse personal qualities and recognize their value for the team. The key, in my opinion, is awareness about ourselves and empathy to others.
What can SAP do to support women’s careers in the tech industry? In general, I think SAP is on the right way. I believe it must start much earlier: in the families, schools, and further professional education. Society should prioritize this topic so that women don’t get the impression from the beginning that they are inferior to men regarding technical understanding. And SAP should continue to talk about it, to spread awareness and, with that, create a mindset of equality and balance.
At this point, I would like to emphasize that, especially in our AI organization, I experienced a very strong focus on diversity (both gender and ethnicity), and I love it! If you didn’t experience working with such a highly diverse team, you don’t know what you missed. I perceive such teams as very balanced, with a pleasant working atmosphere and the best performances. This is the way to go! 😊
Thank you very much for sharing these exciting insights, Helene! We highly appreciate getting to know the perspective of another female colleague in the tech area and are sure to have answered many questions that women may ask themselves when planning their careers. You can learn more in our previous interviews with Jana Würth and Haodan Yang, who also gave us inspiring insights into their work at SAP AI!
Follow to not miss our upcoming interviews:
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