Guest Blog - Women in Data & Analytics: Moe Kiss, Wine Gallery
To celebrate International Women's Day on March 8th, this week we will be bringing you a series of guest blogs from leading senior females in Data and Analytics. They will be discussing their success, career-defining moments and what advice they would give to another female looking to pursue a similar career. This is what Moe Kiss, Wine Gallery had to say.
Profile: With six years of analytics experience, Moe’s focus is on understanding customer behaviour through data & analytics. Moe is the Head of Analytics & Digital at the Wine Gallery - a personalized wine subscription service, and was previously the Analytics Manager at THE ICONIC.
Moe is an active organizer in the analytics community serving as President of the Digital Analytics Inc. where she helps run Analytics Wednesday, a monthly meetup, and MeasureCamp, a yearly free “unconference”. Moe also co-anchors The Digital Analytics Power Hour, the number one data & analytics podcast.
What are the key factors that you feel make you successful?
Build Relationships: I have strong relationships across the industry and I believe my success is largely dependent on these relationships. Knowing a peer in another company well enough to be able to shoot them a message and talk through a problem or ask for help is paramount. Often people who work in data & analytics are the single person at their company doing that job; a strong network who you can help and who can help you will only make you a stronger analyst. Likewise, I often find helping another analyst helps shed new light on a problem or solidifies knowledge in my mind. If you work in data & analytics my first stop would be the Measure Chat community - it is 6,000 analysts helping each other out. You can join here.
Give back: one of the best ways to keep learning is to get more involved in the community where you work. For example, I am part of a team that runs Analytics Wednesdays and MeasureCamp, a free “unconference” for data and analytics professionals (our next one will be in October 2019). Believe it or not, but volunteering helps validate my previous point on relationships and also ensures you stay ahead of the curve by listening to what is happening in the industry through meetups. You’ll also be the first to know about mentoring initiatives or new job opportunities.
Do things that scare you: I have spoken openly before, on my friend Lea Pica’s podcast, Present Beyond Measure, about my fear of public speaking. I worked incredibly hard to overcome that and while it still scares me, I now love it as a way to share my knowledge. When I moved careers I made the decision to become a “yes person”. By that, I mean say yes to every opportunity that lands on my lap, especially if it scares me! That’s when you tend to learn the most. For example, I said yes to be a co-host on a data & analytics podcast, The Digital Analytics Power Hour. While it was scary, it was also the best decision of my career. Subsequently, I’ve written a blog post on how I came to the decision.
Pomodoro: when I am struggling with lots of competing priorities and find myself getting distracted I use a technique called pomodoro. This is where you work in 25 minute blocks and have 5 minute breaks. I find this technique helps me smash through work and stay focused. I use the marinara pomodoro assistant to keep me honest. It also gives me data on how many blocks I’ve got through, which as an analyst, I love!
What's the most valuable piece of advice you have received in your career and how did it help you?
“Stay in the weeds as long as you can.”
I had the great honour of meeting the former President of the Human Rights Commission, Gillian Triggs. I asked her if she could go back in time and tell herself at 25 years old, one piece of advice what would it be. She said to stay in the weeds as long as you can! What I understood that from this, was that often in our 20s we are very eager to climb the corporate ladder but developing broad experience across many roles and industries is far more valuable once you do go into leadership. I often encourage people in the industry to take a few different roles before becoming a people manager for this reason. Her point is that it is quite difficult to go back and take a sidestep once you do start in leadership, so enjoy learning while you can.
What's the most challenging situation you have faced in your career and how did you overcome it?
Facing a career transition was a challenging situation for me personally. Leaving the federal government and moving into data & analytics was a big shift and I found it pretty tough. I tackled it by:
No idea is a bad idea - I read many books and tried different exercises. The most valuable I found was brainstorming what you are good at, what you can get paid for and what you like doing. We had a dinner party and invited people over to help with their ideas. After that I had a pretty good idea of what type of roles would meet all three criteria and got to work applying.
Ask for help
- Leaning on those who love you. My amazing husband, Jamie Behl, supported me by doing even more in our personal lives, which gave me time to attend interviews in Sydney, on top of my hectic existing role in Canberra. Asking for help is important when you are going through a big change.
- Use your network, which often means asking for introductions. We need to get better at this! My network may have helped me get an introduction which led to an interview but I still turned up and convinced the person on the other side of the table to give me that job and then proved myself in the role.
Be kind to yourself - come up with a few small rewards for tough days (get a massage, cook your favourite meal, go to bed early, smash out a run) and do your best to shut down that negative voice in your head that is saying you can’t do it. In order to do this, you need to do some soul searching on what are the types of activities and rewards you can give yourself which will help you feel recharged when you most need it (I recommend thinking about that before the challenging situation hits so you are ready to go).
Lastly, surround yourself with your cheerleaders - you know those awesome friends who think you are the best and skip catch ups with anyone that drains you. You need to save your energy for you during tough times.
How do you approach making a difficult decision?
I talk to my network and trusted advisors, and use their input to form a pro and con list. If there is any doubt, I will always lean towards a yes - especially if it scares me. However, weighing the cons helps me identify any genuine red flags, that should make it a no.
What do you believe will be the most in-demand skills over the next 10 years within data & analytics and why?
Data & analytics continues to become more and more technical with many roles now requiring three programming languages (SQL, R, Python). My advice to those who are new to the industry is to start learning now. If I could do my time over, I’d start with SQL and then go to Python - I love R but Python is a bit broader allowing you to do more throughout your career. I have a few other tips on my blog for newbies to the industry.
The most important question facing our industry though, is whose role is it to apply society’s values to our work? What I mean by this is, that as analysts & data scientists we are often making decisions about what variables to include in a model and how we should be treating those variables including the weights applied.
These decisions can impact who sees what ad, the search results shown, the words provided in autocomplete, the products displayed or the order in which they appear and so on. In some cases, this very choice by an analyst or data scientist can perpetuate inequality, possibly without the analyst even realising it. For example, an algorithm in which senior executive roles only being shown to a particular demographic. Or email autocomplete statements referring to leaders as a particular gender (e.g. “him” or “he”).
The challenge for our community is how we manage this. Government and private companies are not providing enough guidance. Ultimately, over the next decade we as an industry are going to need to decide how we manage these moral questions. It is not merely enough to input data into a model and let it figure itself out, if the outcome can lead to societal inequality. A big part of this is ensuring analysts & data scientists have deep enough subject matter expertise to see and call out these potential issues. The question that keeps me up at night is: as a data & analytics community, where do we want to stand on this issue and can our work generate a more inclusive society?
Join in on the conversation on Twitter for this years' International Women's Day using the hashtag #BalanceforBetter