The countdown to Vena Nation week continues! This interview features Rishi Grover, our Co-founder and Chief Technology Officer, for a preview of his keynote talk, The Future of Data Transformation. Read on to discover what data transformation is all about—and don’t forget to register for Vena Nation Week 2021 today!
What does the term “data transformation” mean to you?
Rishi Grover: Data transformation is the process of optimizing your analytics strategy so you can rely on cross-functional business data to make strategic decisions. Every individual company is on their own journey to becoming more data-oriented—and having confidence in your data-driven business decisions is the ultimate goal for everyone.
Data transformation happens in stages. You need to identify what your most important data is, figure out where it lives and then get your data to a “utopia” state where you can actually extract insights from it. My session during Vena Nation week will be about helping business leaders understand, “Okay, this is where we are today with data transformation, this is where we want to be and this is the path we need to take to get there.”
What do you think are the most important steps on the road to data transformation?
RG: Good question. I’ll start by talking about an approach companies shouldn’t take, which is looking at all their disparate data sources and trying to fix everything all at once. It becomes a psychological hurdle in that scenario—because even the most advanced companies might not know where to start.
A much safer strategy involves identifying your ideal end state and then rolling out a phased approach with realistic steps to getting there. First you have to look at the KPIs you want to measure. Then you need to figure out the data you need to represent those metrics. Once you have access to the focused data you’re looking for, the next steps are validating it, optimizing it and getting it into the hands of the people who need it most.
The phased approach is so important because every business has different priorities. Once you’ve got your most important KPIs figured out, then you can start to add more sub-level data points into the mix and tell a more comprehensive story about how your business is performing.
Why do you think finance leaders are in the best position to spearhead data transformation initiatives?
RG: The office of finance is the only department connected to every other function within a company. Finance leaders know better than anyone what metrics and KPIs run a business. CFOs are close with everyone—especially operations leaders—because they look at the business as a whole when making decisions about dollars and cents.
How do you think machine learning will advance data transformation in finance?
RG: It’s a pretty complex topic, but the core idea is the ability to take a huge data set and have a machine run through it to identify trends, anomalies and correlations. It gives you a granular level of insight in a short amount of time, which is helpful when your business has a lot of data to sift through.
This can really help finance professionals when they’re doing a lot of forecasting, because you can put training patterns in place to help make predictions about future outcomes. Your end users don’t even need to know what the underlying technology is—because at the end of the day, they just care about getting the information they need to run the business.
A big part of my session will be demystifying machine learning for the audience. Some businesses might not even need machine learning to get to that “utopia” state I mentioned earlier. You just need to make sure your data is reliable and that your users have a seamless experience when they’re working to extract insights from it.
What are some strategies finance leaders can employ to make communicating the story behind their data a little bit easier?
RG: In my opinion, it’s all about transparency through business intelligence. You need to ensure the people who need financial or operational data can get it without having to email the director of finance.
That’s where business intelligence solutions come into play here. Just look at Power BI, for example. Tools like that are so affordable now, which means everyone across your organization can have easy-to-read dashboards that tell a story. So when you marry business intelligence with a proper data transformation strategy, everyone has a chance to collaborate with reliable data they actually understand.
When companies are further along with data transformation, what do you think will change about how they interact with their data day-to-day?
RG: I think strategic analytics efforts will become proactive rather than reactive. Here’s what I mean by that: Instead of logging into a system and looking for insights yourself, the system will actually alert you about meaningful information on its own. What you see will be based on everything you’ve looked at historically, which is really cool to think about—especially when you can trust the data. For me, that’s going to be the fundamental shift over the next five to 10 years.
What’s the number one thing you think the audience will get out of this session?
RG: The most important thing I want the audience to take away from this is that data transformation isn’t just a “trend.” It’s not something you should be thinking about tomorrow or later next year. It’s happening right now—and companies need to be ready for that.
This session will provide a roadmap for how to get ready. I’ll walk through some actionable steps your business can take today so you can prioritize what to focus on as you embark on your data transformation journey.
