Valérie Bécaert of ServiceNow spends her work days navigating long-term research priorities and customer or product engineering groups, “weaving scientific change into the company’s texture,” she says.
Has a Ph.D. in chemical engineering and a professional focus on sustainability, data science, and AI research, he brings together diverse teams through brainstorming workshops, hackathons, proof of concept experiments, and pilot projects.
Bécaert, a senior director of research and scientific programs at the company’s Advanced Technology Group, spoke with Workflow about how he helps translate research innovations into production software.
The following interview has been edited and abridged for clarity.
Q
How does a company invest in research for markets, products, or use cases that don’t already exist?
A
Changing for the future requires a lot of creativity and intuition. There are three buckets in which you can invest. You can be market -based: thinking about what markets might look like in the future. You can be product -based: thinking about how you want the customer experience to evolve with a product. And you can be technology-based: thinking about what new technologies might emerge in the future and positioning yourself ahead of discovery. One constant is that within your organizations you must develop a culture of change.
[Read also: Resilience in the era of collaboration]
In my team, we are primarily based on technology. We are investing in our ability to see what technologies will emerge in five years. Once you know which bucket you are, you can understand what your team needs to succeed. My small team is heavily invested in collaboration, as we need to work together well to stay ahead of new technologies developed in academia and the scientific community and to evaluate how they fit into the ServiceNow product roadmap. I am involved in core and applied research on ElementAI, acquired by ServiceNow in January 2021, and we are reviewing use cases in business units on how we can use this new capacity. Some examples include our natural language processing, machine learning, and computer vision research, which are currently being re-platformed to produce customer-focused AI tools for the Now Platform.
Q
What are the major challenges in encouraging change in a large organization?
A
A lot of people talk about breaking loops so that teams can communicate cross-functionally, and I believe that is more important than anything. But leaders often mistakenly believe that in order to break the loopholes, they must create a consistent culture throughout the organization. Instead, teams should develop different behaviors, skills, and cultures based on their needs. In the research team, for example, I’m working to create a curiosity -driven culture where creativity and risk -taking are embraced, but you wouldn’t expect a team to have the same culture that needs to make concrete deliverables next week.
Q
How can you overcome those divisions?
A
Creating cross-cultural teams is about building connections and creating a general culture that is open to new ideas and unconventional perspectives. I think this is especially important because new technologies like artificial intelligence and machine learning are becoming more prevalent in the workplace.
Change isn’t always comfortable or easy, but it can be more comfortable and easier for organizations with leaders talking to employees about what’s in store. They need to be clear that what we do now is probably not what we will do 10 years from now. If people understand that narrative, they can come with change.
Disclaimer
ServiceNow Inc. this content was published to 24 February 2022 and is solely responsible for the information contained herein. Shared Public, unedited and unchanged, on February 25, 2022 21:15:45 UTC.
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Trends in technical analysis SERVICENOW INC.
Momentary | Mid-Term | Long -term | |
Trends | Neutral | Neutral | Neutral |
Evolution of Income Statement
Sell Buy |
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The meaning of consensus | BUY |
Number of Analysts | 35 |
Final Closing Price |
573.95 $ |
Average target price |
$ 697.73 |
Spread / Average and Target | 21.6% |
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