What advice would you give to CTOs newly managing machine learning (ML) and data science teams?
CEO, MSSP - High Assurance Cybersecurity SOC in Services (non-Government), 1,001 - 5,000 employees
Give them the latitude to experiment, fail, and rebuild... that the is premise of ML and AI. But most importantly, keep the objective and end-state in focus while innovating. Director of IT in Software, 201 - 500 employees
Pay particular attention to the data formate/readiness. If your data is not clean/ready for ML, your results will not be valuable. They say Garbage in, garbage out. CIO in Services (non-Government), 201 - 500 employees
Put together a lab for them to build and break everything; the more they can play with it, and the more they can experiment, the better it is for their understanding of the technical side of the project. I'm a firm believer that all new projects should be implemented way ahead of roll-out, by putting it all together in a learning lab environment. I'm a "learn it by doing it and breaking it" kind of guy, and a lot of my engineers and techs are the same.Content you might like
Yes, we’ve done this successfully10%
Yes, but it’s still in early stages67%
Not yet, but I plan to17%
No, but I’d like to6%
No, and I don’t plan to0%
63 PARTICIPANTS
CTO in Software, 201 - 500 employees
Without a doubt - Technical Debt! It's a ball and chain that creates an ever increasing drag on any organization, stifles innovation, and prevents transformation.Community User in Software, 11 - 50 employees
organized a virtual escape room via https://www.puzzlebreak.us/ - even though his team lost it was a fun subtitue for just a "virtual happy hour"
Yes, we schedule these as separate meetings37%
No, we discuss them at the same time during scheduled performance reviews51%
No, but we’re working to implement a process for both discussions10%
Not sure2%
Other (I’ll comment below)0%
115 PARTICIPANTS
If you make them leave you might lose a valuable R&D researcher. And for every 10 applicants that I get on paper, nine of them are not a good fit. On paper, they've got the right academic background, qualifications and sometimes even a bit of industry experience, but only 1 in 10 will be a valuable addition to the company. So if you keep cycling though your staff, you'll soon be left with the people that are not that valuable to your company. And those people are not going to leave because they're not the ones that are being headhunted.