Data-Driven Work Cultures: Ishaan Nerurkar of LeapYear On How To Effectively Leverage Data To Take Your Company To The Next Level
An Interview With Pierre Brunelle
Monetize data — Monetization of data, or more generally deriving commercial value from data, should be the default approach going forward. Leadership must acquire solutions and strategies to generate insights and analytics that unlock revenue and improve business outcomes, driving innovation and competitiveness.
As part of our series about “How To Effectively Leverage Data To Take Your Company To The Next Level”, I had the pleasure of interviewingIshaan Nerurkar.
Ishaan Nerurkar is the founder & CEO of LeapYear. LeapYear has raised over $50M in financing, and enables the world’s largest financial institutions, healthcare organizations, and government agencies to safely access and share highly sensitive datasets.
Before founding LeapYear, Ishaan led a consulting firm that partnered with government agencies, corporations, and universities to apply cutting-edge research to data strategy. Prior to that, Ishaan worked on a Department of Defense initiative as a researcher through MIT.
Thank you so much for joining us in this interview series. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?
I started my career wanting to be a professional researcher — in particular I enjoyed applying new mathematical techniques to solving real-world problems. For example, I worked on a range of problems from designing new algorithms to predict epileptic seizures from brain EEG data for medical researchers to using network science to detect anomalies in cell phone data for the government. In order to broaden the range of problems I could work on, I started my own consulting firm, and worked with government agencies, Fortune 500s, and nonprofits on making better decisions from their data. Across all of these initiatives, I saw that organizations were either underutilizing data due to privacy concerns or putting their customers and partners at risk by sharing sensitive information. I founded LeapYear to solve this problem at scale, with cutting-edge research at the intersection of cryptography and machine learning.
Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lessons or ‘take aways’ you learned from that?
In the very early days of LeapYear I had the opportunity to present to a senior executive of a large healthcare company. At the time, we had a few prototypes which showed how our algorithms could allow predictive models to build on medical data without exposing any patient information. We had also put together an analysis of how their current methods of anonymization — based on statistical de-identification and data masking — were compromising patient privacy. In a one-hour presentation, I covered the product, underlying algorithms, roadmap, and the results on their datasets, which we believed were impressive. At the end of the presentation, the executive asked only one question: Is your product most similar to PowerPoint, Word, or Excel?
At a loss for words, I answered “Excel”, but needless to say the meeting was not as productive as I had hoped. I learned from this experience the importance of explaining what we do in very simple terms, and not assuming that the audience has any understanding of the problem being solved, let alone the intricacies of the solution.
Is there a particular book, podcast, or film that made a significant impact on you? Can you share a story or explain why it resonated with you so much?
I really enjoy reading science fiction. Great science fiction authors invent a new world, usually shaped by a technological development or scientific breakthrough which does not exist today. Within this world, they have to think through how the lives of individual characters are shaped by the scientific breakthrough at a significant level of detail — everything from their daily lives to their hopes and ambitions. This has some small but interesting parallels to inventing a fundamentally new technology — you need to be able to imagine broadly how the existence of this technology will shape a business or industry, and also carefully think through details of how it affects individual users of your product.
Some examples of science fiction which I like: Three Body Problem series by Liu Cixin, Macroscope by Piers Anthony, and many of Ted Chiang’s short stories.
Are you working on any new, exciting projects now? How do you think that might help people?
One project that comes to mind is our work with consumer credit card data. This type of transaction data is highly sensitive and personal to each card owner. In addition, the merchants represented in the data sets are also concerned that information about their performance be protected. Think of the sensitivity of a market share analysis comparing one fast food hamburger chain to another. For these reasons, consumer credit card data is appropriately regulated and deliberately hard to use. But these use restrictions leave value trapped in the data. For the last six months we have worked with a top five card issuing bank to liberate the value from their massive cards data set, solving a 20-year-old problem of ‘how do we use this data and be compliant and respectful of privacy?’ By liberating this data, our customer will see downstream improvement in overall market risk, liquidity and cost metrics.
Thank you for all that. Let’s now turn to the main focus of our discussion about empowering organizations to be more “data-driven.” My work centers on the value of data visualization and data collaboration at all levels of an organization. So I’m particularly interested in this topic. For the benefit of our readers, can you help explain what exactly it means to be data-driven? On a practical level, what does it look like to use data to make decisions?
I believe we are in the third — and most interesting — phase, that of becoming data-driven. The first phase was about understanding that data is a new and powerful resource to drive outcomes for businesses of all types. The second phase was defined by the development of tools and capabilities to collect data. Now we are entering the third phase where the use and collaboration of data will bloom into competitive advantage and positive outcomes. But using data at scale for critical purposes is challenging. Most organizations face restrictions on how they can use much of their data because it is sensitive in some way. These challenges come from regulations, data silos, and client or customer expectations. In order to be truly data-driven, companies will have to solve the challenge of actually using all the data they collect. Once they overcome this last critical barrier, companies will incorporate data into all facets of their work, from customer acquisition and retention to deriving new and valuable products for the market.
Which companies can most benefit from tools that empower data collaboration?
Financial firms, healthcare organizations, and retail and consumer companies are good examples. Ultimately, we are talking about virtually any company that has collected data they can use to their advantage.
We’d love to hear about your experiences using data to drive decisions. In your experience, how has data analytics and data collaboration helped improve operations, processes, and customer experiences? We’d love to hear some stories if possible.
In addition to the credit card example detailed above, we find organizations are constantly striving to improve their outcomes with data. Two more examples are included here:
In the equity capital markets, banks help their clients execute stock trades. The pattern of trades executed by each client is considered confidential, because it is based on information or strategies which are proprietary to the client. The bank must protect the confidentiality of this information in order to retain client trust. Partnering with LeapYear has allowed our banking clients to improve client confidentiality protections, expand execution options and improve top line performance for the bank. These improvements come from a more optimal usage of the sensitive data the bank already possessed.
A second example comes from healthcare. In this example, a healthcare company is focused on combining both healthcare data (such as medical records) and consumer spending data (such as credit card transactions). The challenge here is two-fold: First, how do you protect the sensitive contents of each data set separately, and then how do you protect the combination of these data assets? In this case, LeapYear enables the compliant private joint analysis of this data, powering better health outcomes and recommendations for patients.
Has the shift towards becoming more data-driven been challenging for some teams or organizations from your vantage point? What are the challenges? How can organizations solve these challenges?
There are many challenges to overcome. Some are organizational and others are in the practical use of data. Many companies do quite well when using the “easier” data sets available to them. An example of this would be a single business team using publicly available information (like weather) to provide better service to customers (for example, having umbrellas at the front desk of a hotel). However, the challenges are different when the data under consideration is sensitive and potentially must cross internal firewalls or regulated boundaries. Teams historically fall back to very conservative approaches to data use in these scenarios, leaving value trapped in their data. Organizations need an optimal approach to liberate their data with technology solutions. Adopting these approaches will take leadership from executives to demand maximum value from data and intra-organizational collaboration with data, compliance and IT to rapidly adopt and scale the solutions.
Ok. Thank you. Here is the primary question of our discussion. Based on your experience and success, what are “Five Ways a Company Can Effectively Leverage Data to Take It To The Next Level”? Please share a story or an example for each.
- Reinforce customer trust — Protect confidentiality and personal data privacy (“the right to be private and remain private”). Next-level data use and collaboration will achieve both incredibly high value and protect the underlying people and institutions in data sets.
- Liberate data — Get data flowing across teams and organizations. Implement technical solutions that achieve maximum data use while still respecting necessary data privacy protections.
- Monetize data — Monetization of data, or more generally deriving commercial value from data, should be the default approach going forward. Leadership must acquire solutions and strategies to generate insights and analytics that unlock revenue and improve business outcomes, driving innovation and competitiveness.
- Be compliant — Leadership must ensure that the use of data abides by all regulatory and legal guidelines and requirements. However, it must also understand that the use and sharing of data will come under more scrutiny and perhaps more restrictive legislation in the future. Market advantage will go to companies who build future-proofed approaches to share and protect data.
- Collaborate transparently — Companies should adopt data collaboration approaches which rely on transparent methods to achieve value with privacy and compliance.
The name of this series is “Data-Driven Work Cultures”. Changing a culture is hard. What would you suggest is needed to change a work culture to become more Data Driven?
Due to privacy and security concerns, many businesses are apprehensive about liberating data. But the imperative to leverage this data cannot be overstated. Companies may think they can slowly ease into using data effectively. In reality it is a binary choice. Companies will either step boldly into a future that creates market advantage through data, or they will lose market share to firms that do. With our software, responsible analysis and sharing of sensitive data securely are possible through advances in cryptographic techniques like differential privacy. Companies need to know that with modern technological innovations, it is indeed possible to capture value from data while respecting economic, moral, and social concerns, as well as considering ethical obligations (to improve industry, government, and public safety). Most companies believe their current strategy is sufficient to address the emerging data and privacy landscape. But time and again we’ve helped our customers recognize there is a massive amount of value still to be captured.
The future of work has recently become very fluid. Based on your experience, how do you think the needs for data will evolve and change over the next five years?
Regardless of the format the future of work takes (in-office, hybrid, remote), the world is being driven by three secular trends that relate to data. 1) An ever-increasing need to collect data. 2) An ever-increasing need to use that data to build competitive products and services. 3) An ever-increasing need to respect and improve privacy for individuals and enterprises. The combination of these three factors will demand that executives evolve their organizational competencies and technologies. LeapYear believes in a world that can be both data driven and respectful of privacy, and we intend to help organizations of all types meet these trends head on and succeed.
Does your organization have any exciting goals for the near future? What challenges will you need to tackle to reach them? How do you think data analytics can best help you?
There is a competitive advantage for companies that leverage LeapYear’s expertise. Many companies are at a stalemate. For those, this is their last option at making more money. For others who are new to the space, they need us to address their issues with data; making sure it is shared safely and securely. We facilitate the broader use of data, utilizing every last drop.
How can our readers further follow your work?
Thank you so much for sharing these important insights. We wish you continued success and good health!
