Conferences, Clients, and ROWE

Bree Stanwyck

3 min read

Jul 8, 2012

Conferences, Clients, and ROWE


Highgroovers keep up with new trends by attending at least one conference per year. Besides bringing us up to date on what’s shiny, they help us network, learn about the bleeding edge of our field from academics, and gain new perspectives on what we do. But conferences aren’t necessarily vacations, and juggling a conference and a Results-Only Work Environment (ROWE) can be tricky. Read on to see how we handle conferences in a ROWE while keeping our clients happy.

Many of us choose conferences like RailsConf or RubyConf that relate directly to our work, but we also attend startup and business conferences like LessConf, Summer Con, and BarCampNYC.

This year, I chose to attend ICML 2012, an academic conference centered on machine learning. ICML offered a great chance to get in touch with machine learning academia and learn what’s new in big data processing and deep learning, among other things.

Thanks to our “unlimited within reason” vacation policy, conference days don’t have to count as working days. And even if we’re working during a conference, learning and interacting at the conference takes priority over work.

In my case, I chose to work while attending the conference. Doing so meant that I hade to figure out how to manage time spent doing work at a conference, and how to make sure clients know what to expect while I was attending it. Work done during a conference most likely consists of keeping up to date on any communication regarding the project and potentially responding to emergencies, such as production downtime on a project. By updating our availability well in advance and informing our clients at the same time, we eliminate most issues that can pop up when you attend conferences.

On the other hand, a conference can also be taken as vacation where no work gets done (this option works well, for example, on projects with only one assigned developer). Or there’s a full-on “working conference,” which is a tempting option, but it can get tricky when you’re dealing with a hotel’s shoddy WiFi and balancing work with conference time.

Our vacation policy gives some solid advice for ROWE conference-takers: “Don’t spend conference sessions trying to get other work done. That said, if you have huge swaths of down time while on a trip, that can be a pretty awesome time and place to get some work done.”

I am thankful that the client I am working with actively discouraged me from working too hard during conference days, allowing me to me focus on presentations and networking with the machine learning community. While I was at the conference, I tried to keep up with my client via chat, and they repeatedly told me to get back to the conference. I was surprised by this, but they know that attending conferences helps us to do better work for them in the future.

ICML 2012 helped me sharpen my skills in a number of ways. I was reminded of the importance of the cycle between business problems, machine learning research, and business solutions in a great talk and paper called Machine Learning That Matters. It also gave me a feel for what’s possible now, and what will be possible, with machine learning algorithms. Clients often ask us questions related to machine learning: They frequently have a pile of data and aren’t quite sure how to extract the info they need. ICML made me more aware of new ways to interpret ML problems so that I can help add business value in these cases.

Learning from the academics at ICML taught me about the ways the field is growing and changing, and made me think about how I can use this knowledge in my work. I may not have been working at full strength during the conference, but I was definitely increasing my knowledge base and learning new skills to use at Highgroove.

What about you? Have you been able to juggle work and attending a conference?

Juan Pablo Claude

Reviewer Big Nerd Ranch

During his tenure at BNR, Juan Pablo has taught bootcamps on macOS development, iOS development, Python, and Django. He has also participated in consulting projects in those areas. Juan Pablo is currently a Director of Technology focusing mainly on managing engineers and his interests include Machine Learning and Data Science.

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