- What got you interested in product/project management?
When I moved back to Pittsburgh, I took a job as a relationship manager for a small tech startup called SnapRetail. The company made email and social media marketing software for independent retailers. It was my job to work with the vendors (think Vera Bradley and Yankee Candle) so that they could add their content to our platform.
The startup world is tough, and my department was eliminated with those of us in it being moved to sales. I was … uninterested. So, I presented a two-week plan to my CEO and asked him to lay me off after I had completed that work. He looked at me quizzically but said he’d think about it. As I was leaving his office, our VP of Engineering, a woman named Tara, pulled me aside and said that she loved my work and that she’d like to hire me to be the development team’s project manager. (I had previously led a few dev programs having to do with my job functions.) I found my place in project management.
- Can you help us understand the distinctions between product, project and program management?
This is a tough one and really depends upon where you work. I’ll give a high-level overview, but there is quite a lot of crossover in responsibility if you work at a smaller company. Product management is what you want your technology to do. A PM does competitive analysis, talks to customers and positions the company for correct market fit. They’re responsible for the “what” and the “why” and work more cross-functionally with marketing, sales, engineering and UI/UX.
A project manager, on the other hand, owns the “how.” They translate the product requirements into actionable items for the development team to work on and keep a close eye on progress. They can create or modify processes for better visibility or tracking, and often manage budgets as well.
Program management, which is what I do now, is kind of like project management, but with multiple teams/projects and dependencies. A program manager can and should have a higher-level view of the company’s goals and strategies to avoid rework or the duplication of efforts.
- What carries over from your writing/journalism background into this world?
So much of what I learned at John Carroll, particularly in my journalism and writing classes, is how to ask questions, synthesize information and then share it with the rest of the world. We learned to read, write and think — independently. I didn’t just learn to regurgitate a previous author’s ideas; I was taught to use them as a baseline for my own. And I think that the drawing out of information, the searching for clarity, is what has made me successful in my career.
Technology needs people who don’t know everything and who aren’t masters of a particular domain because it’s those folks who look at problems differently and involve others. The non-tech techies are English majors, MBAs and sculptors: our views aren’t myopic because we’ve entered the field not knowing what we don’t know.
- What would you tell current students about thriving in the world of tech and tech startups?
I love this question! Be prepared to work, to pivot from product to product, to rarely have the same day twice in a row. Learn to be comfortable with the nebulous world of inventors and idea people or become one. Keep excellent notes, because you’re never too good or high-up to be a note taker. The keeper of good notes today becomes the person others go to tomorrow — when they look for the go-to person for project status or consensus or next steps.
Startups can also be uncomfortable if you’re brave enough to work for one with an uncertain future. If you believe in what your company is doing, then it’ll be worth it. It also may be worth pointing out that technology companies are doing so much more than selling things and building self-driving cars. They’re trying to solve big, complex, messy problems. If you’re interested in that, then go for it.
- What do you glean from your experience with self-driving automotive and other technologies regarding the future of work — and the interaction between machine learning and human talent?
We have a long way to go before robots are doing the hard things for us. Right now, for example, machine learning models are being trained by human input: we have to give the algorithms correctly labeled data for them to continue to improve in their decision-making. For example, traffic lights look and behave differently from city-to-city, country-to-country. So, in order for us to have a universally working autonomous vehicle, the car needs to understand the wide and diverse sets of traffic lights and their behaviors.
Right now, I see human talent and computers improving the world in tandem and there isn’t yet a clear “leader.” It’s scary to think that one day everything will be automated, but the future of work is broad and limitless. There will always be someone out there who is working to discover something new. And, in that regard, there will always be a need for people to do it.