While growing up in India, Maneesha Bhalla received simple advice from her parents that hit home. “One of the things that they instilled in me and my sister was to make sure that we are independent thinkers, and to never be afraid to take the path less traveled,” Bhalla says.
After Bhalla graduated from Pune University with a degree in chemical engineering, she started working as a data analyst and consultant, climbing the career ladder with brands like UBS and Target. But a decade later, recalling her parents’ advice, she took a leap of faith by moving to the US, where she was hired by Office Depot as senior manager of customer analytics.
After serving in data leadership roles and building high-performing analytics teams at Office Depot and Royal Caribbean, she took on a hands-on role at Nearly Natural where she built its data lake and set up its BI platform.
“I am still a data nerd at heart and I love learning about the latest tools and tricks in the ever-changing landscape of data technology,” she says.
Bhalla is now the vice president of enterprise data analytics and AI for Designer Brands Inc. (DBI), a retail conglomerate that owns DSW and the Shoe Company. “My main goal is to make DBI a data-driven organization by shaping and executing the data strategy for the enterprise,” Bhalla says.
She established a “center of excellence” that is focused on building and executing on the road map for data analytics strategy for DBI and addresses a wide range of data initiatives. She leads teams dedicated to the company’s enterprise data engineering, business intelligence, enterprise AI, and cloud data engineering.
Bhalla acknowledges that behind the scenes, her role entails more than you’ll find in her job description. For one thing, she has to make sure that data analytics is at the front and center of decision making and move the needle on analytics from being post-hoc to predictive and prescriptive.
“It’s not enough to know ‘Why did something happen?’” she says. “We need to have the right data and analytics available to answer, ‘What’s going to happen next and what levers can I pull to change that?’—and that information needs to be available at executives’ fingertips.”
It’s the biggest challenge she faces, Bhalla says. “In any analytic element or data leadership role [the challenge] is never the technology. It’s never the tool. It’s never the data platform. It’s changing the mindset and habits of decision makers to make data-driven decisions.”
Because DBI’s operational efficiency hinges on how Bhalla organizes its information, her impact is difficult to quantify. Her first order of business upon arriving at the firm was to centralize source master data and build a semantic data layer in cloud that connected data from customers, products, and its supply chain.
This is the first step toward the larger vision of real-time analytics. Her team took on the task of designing the cloud data lake of the future by architecting the workflows in cloud, leveraging latest cloud native technologies, stitching the data at logical layer, and exposing this data for business consumption through MicroStrategy and Tableau.
“From there, it’s about modernization of our infrastructure, modernization of our data stack, to make sure that there’s focus on things like continuous data governance,” she says. Making sure that the company’s virtual intelligence continues to advance is essential, Bhalla explains. “We don’t just look at hindsight, but provide foresight through AI and ML [machine learning].”
By developing a reliable and accessible data infrastructure, Bhalla also set her teams up to tackle projects across other DBI departments. For example, her AI machine learning team is building a product recommendation engine for an email marketing team. While it’s not finished, early testing shows significant lift in revenue and click-through rate (CTR).
“We were able to test two new models against the current incumbent model that was in production,” Bhalla says. “The models that my team built far outperformed the current models we are working towards implementing that in production.”
Meanwhile, Bhalla says, machine learning only scratches the surface of what data-driven trends will thrive in the future. “Augmented reality (AR) coupled with machine learning and AI is disrupting the retail landscape in a big way. Inspiring our customers to interact with our brands via an immersive and interactive experience through AR, while recommending styles we think they will buy, is going to transform the landscape of personalization for any retailer.”
The challenge now is not obtaining the data, but knowing what data is important. While you can get all the computational power and the right platforms and tools in place, Bhalla explains, the key challenge is understanding what data to look at to drive business decisions.
“Having robust and real-time data architecture to have a 360 view of the customer, enable efficient inventory decisions, and build the brands our customers love is going to set us apart in future,” she notes. In her role shaping DBI’s data strategy for the future, that’s what Bhalla will be focused on.