Earlier this year, business leaders and data science strategy executives joined forces at the All Things Insights MADS Continued Gathering to plot a new course for their respective companies. Looking back and looking ahead, these data science experts examined their analytics strategies in the context of the current economic environment. All Things Insights would like to thank them for their participation: Michelle Ballen, Head of Analytics, Future; Kate Carruthers, Head of Business Intelligence, UNSW AI Institute; June Dershweitz, Board Member, Digital Analytics Association; Anu Sundaram, VP, Business Analytics, Rue Guilt Groupe; and Sunny Zhu, ESG Data Analytics & Operations, Indeed.
Below are some key takeaways from the MADS Continued Gathering:
The Data Planning Mindset
“Q4 for us was really about testing and trying new things, trying different marketing tactics, and just setting ourselves up with all the insights and learnings that we could possibly gather. So that going into Q1, we knew we were putting our best foot forward. At the time it was really focused on growth learning.”
—Michelle Ballen, Head of Analytics, Future
“Once we close our peak holiday season, the analytics and the data science teams are ensuring that all the testing that we did, and all that we gave our customers, actually paid off. And then finally at the end of the quarter, we ensure that there is quantitative closure. That’s a new word I’m coining on what worked and what did not. And that actually informs us for holiday in 2023.”
—Anu Sundaram, VP, Business Analytics, Rue Guilt Groupe
“The strategic planning part is the end of the year for a lot of insights and the project communication. What is being achieved? What is high visibility? And the second area is, it’s insights crunching time, so many questions need to be answered. And the third area is about reflection, so usually Q4 is there’s no big change on the data perspective. It’s a perfect quarter to reflect about data governance, data infrastructure, how we can get strong and more efficient for the new year.”
—Sunny Zhu, ESG Data Analytics & Operations, Indeed
Preparing for What’s Ahead
“This year, from what I’m hearing, is that it’s about doing more with less. It’s about improving the efficiency of our team and finding ways that we can become even more competitive and deliver even if we aren’t able to hire people. Automation becomes increasingly important in that kind of a structure. Another thing that’s really important is proving the value of analytics, making sure that everything that’s on your roadmap for the year is something that actually matters. How can the work of the analytics team help the business understand what they should be doing more of, what they should be doing less of, what they should keep and what they should cut.”
—June Dershweitz, Board Member, Digital Analytics Association
“Optimization can be around resourcing. Let’s focus on doing less, but focus on the most important things we want to achieve. We are focused on the cost perspective, but data teams specifically focus on is there any new tools or there’s any way we can optimize our current data stack so we can optimize any cost related to the data and analytics team. Because a lot of the goal is to transform the data team to be a cost center, to be a revenue generator. That’s definitely increasing the value for the team.”
—Sunny Zhu, ESG Data Analytics & Operations, Indeed
“It comes back to the analytics teams to help business stakeholders kind of prioritize and ensure that their efficiency goals are met. And while doing that, also ensuring that as an analytics or a data science team, you are able to provide the most value to the business stakeholders. I would say it is a big lens on prioritization.”
—Anu Sundaram, VP, Business Analytics, Rue Guilt Groupe
“We’ve got a huge focus on data protection now. We’re doing all sorts of cost optimization. So we’ve always had to be very cost conscious. But now increasingly, we’re really focused on protecting our data, understanding our data. So data governance is increasingly important.”
—Kate Carruthers, Head of Business Intelligence, UNSW AI Institute
Final Takeaways
“I think we need to be looking at our data architectures and streamlining them. One of our big lessons learned from all of our ML experiments was that our data warehouse was not doing us any favors. We are migrating to a data lake house with the view of migrating to a data measure architecture, and that’s going to mean that we are positioned to leverage the very keen interest that people have in AI.”
—Kate Carruthers, Head of Business Intelligence, UNSW AI Institute
“Definitely focus on aligning data strategy to business strategy. Every company wants to say data is our strategic asset, but it’s really important to start now to align that strategy with business strategy for both short-term and long-term needs.”
—Sunny Zhu, ESG Data Analytics & Operations, Indeed
“Make sure that everything that is getting worked on and done and delivered has a focus on commercial viability and demonstratable value of results. But at the same time making sure to keep an eye open for innovation along with that delivery of practical results.”
—June Dershweitz, Board Member, Digital Analytics Association
“My piece of advice is to become best friends with your finance team. Getting close to them and looping them in, in a strategic fashion too, on those working groups around experimentation and growth. They have a great perspective and we’ve definitely benefited a lot from getting close to them.”
—Michelle Ballen, Head of Analytics, Future
“I think having that open mindset of the customer’s changing, the macroeconomic factors are changing, and how we change our business accordingly, as well as the data and analytics strategy and priorities. One thing I want to double down on is just being super close to understanding how all of your initiatives impact your profitability because that is also keeping a very close tab with budgeting and forecasting, because you might be planning for something else in the forecast that changes over time.”
—Anu Sundaram, VP, Business Analytics, Rue Guilt Groupe
