Apex talks to Harini Sridharan, Head of Analytics and Data Management at MoneyGram. She is a growth-focused digital business leader, leveraging deep, multi-industry analytics and data strategy experience to build, scale, and lead global analytics teams in generating multimillion-dollar revenue growth and cost savings. Harini shares valuable insight into building out and integrating a strong data driven business strategy.
Q: What are the current trends impacting data?
A: On the offense side, you have Increased Digital Adoption and Personalization and on the defense side, you have Data Privacy.
Increased digital embrace by customers is driving digital transformations in companies and good data is key for such transformations to be successful. You will know more about your customers and personalize their journey to make it easier for them to shop around in the digital world if you have their journey and friction related data. Therefore, it is reasonable to expect digital adoption and personalization to further drive big data and machine learning needs.
On the defense/privacy end, collecting, storing, and using data in a responsible manner will be critical since customer expectations and data privacy regulations are changing worldwide. The regulations are challenging us to change the way we measure effectiveness of programs and channels and to use the collected data in a more responsible manner.
All these changes enhance the need for machine learning in order to showcase the right products and services, to algorithmically make decisions on approving customers for financial transactions, and to make marketing investments more effective.
Q: How do you balance the need to ensure that non-revenue generating data-driven transformation efforts receive the commitment and funding that are required to sustain these efforts?
A: The executive team supports data transformation efforts if you can articulate that those efforts will drive understanding about customers and lead to optimal decisions that would in turn drive up revenue and profitability. So, it is important to have a list of projects that can deliver value because of the data transformation effort.
As with any transformation, you need to show sustained progress to ensure that there is continued enthusiasm. It is important to start with small POCs and show quick effective wins. I would approach it like any new product development. Similar to a new product introduction in a market, you need to start with a critical area and find your strongest supporters and adopters who can use the product/service (in this case data service) and illustrate the value of your efforts. As you would for any transformation, you need to have milestones along the journey that show value improvements along the way. This will lead to sustained interest among executive sponsors and will keep the team’s morale high.
Q: Have you developed a business driven data strategy; is there support for it and is your organization becoming more data-driven? What steps are you taking to ensure all areas of the business are data driven?
A: Any data strategy should be built around a company’s business strategy. A number of companies are going through digital transformation these days. If digital transformation is a goal, then first we need to collect data in a way that addresses immediate needs. This includes everything that we can reasonably get about the type of customer we are trying to attract and retain. Also, it is important to understand the current factors impeding adoption by these customers, learn about the kind of channels that can bring the types of customers and so on. But on a longer-term basis, we also need to ensure that data strategy can support tomorrow’s business models which require faster machine-learning driven decisions and recommendation engine driven content among others.
It is easier to convince adoption when data strategy is built around supporting business growth and it will help your case if you can demonstrate it with a few proof-of-concept examples. Also, by now, most firms and boards see the value and there is significant investment across most industries in data.
Again, it is very important to find a few strong supporters and pilot use cases that visibly impact their teams. Once you have some strong wins and have started scaling it with a few more partners in the company, it is easier to convince partners who are holding out.
Q: What is the current state of Big Data and AI investment and do you sense the pace of Big Data and AI investment changing?
A: Customers are now getting used to split second AI driven decisions in many spheres of life and are starting to expect it more everywhere. What used to be customer delight and competitive advantage five years ago is table stakes today. To support this kind of instant decisioning, optimization, and ML driven pertinent content etc., requires a tremendous amount of data and ML capabilities. As such, investments are accelerating significantly and should continue to accelerate over time.
Q: How important is it to have a data driven culture? Have there been the obstacles to building a data culture and if so, then how have you resolved it?
A: To win in the digital space, first, companies need to be data driven as opposed to merely being data informed. That takes a huge cultural shift. Often the argument that we hear is innovation and data driven decision making don’t go hand in hand. Yet some of the most innovative firms are also the most data driven ones – Netflix, Amazon and so many more. Concepts like data driven innovation are catching up.
Secondly, you will see that a lot of successful digital firms test customer preferences before they invest. In a digital world with good data and technical infrastructure, customers’ likes, and dislikes can be quickly identified. Therefore, it is important not just to build products, but have a feedback circle in the form of A/B and multivariate testing as well. Surveys and user testing are important. In addition, before going live, it is also vital to test in small volumes before you invest or make a large change wherever possible. That again requires a culture change in decision making from being opinion based to one that is data driven. It makes it vital to hire personnel with a data driven mindset across functions and for the CDO or CAO to consistently make the case for having analytics at the table.
Q: Have you found new vendors for your organizations that are now needed in this time of COVID-19 and remote working?
A: Yes. With COVID-19, data needs as I mentioned have only accelerated as digital adoption has scaled. So organizations have greater data needs. Some of it has been through word-of-mouth recommendations and others have been through virtual events such as yours. Some of it has also been through vendor cold calls and demos.
Harini Sridharan – Head of Analytics and Data Management at MoneyGram
Harini is a growth-focused digital business leader, leveraging deep, multi-industry analytics and data strategy experience to build, scale, and lead global analytics teams in generating multimillion-dollar revenue growth and cost savings while improving customer engagement. She has worked across B2B and B2C companies in areas of product, customer, growth, business analytics, and data strategy. Her expertise includes ROI improvements for 9-digit media budgets as well as optimization and customization of US and international websites across multiple industries like e-tail, cloud infrastructure, and financial services
She is the Head of Analytics and Data Management at MoneyGram International and was previously with IBM, eBags, and Vistaprint in various roles. She is also a Senior Fellow at Wharton Customer Analytics.
Harini holds a Master of Business Administration (Honors) from the Wharton School; a Master of Engineering Management from Dartmouth College; and a Bachelor of Engineering degree.