At These 6 Chicago Tech Companies, Data Is King. Here's Why.

by Alton Zenon III
August 22, 2019

The way many companies in the Chicago tech scene leverage data to achieve success may surprise you. We asked six of them — utilizing data to do everything from recommending cars to solving internal hiccups — about how their use of data created a recent win for their business and how it’s used to measure overall success.

 

Avant team working at a whiteboard

Avant uses big data and machine learning to offer personal loans to consumers. Doing so requires copious amounts of information and Director of Data Management Robert Adler said it’s very important that their data be accurate. His team has a number of checks in place to ensure their figures are correct, bug-free and turned around quickly. 

 

What’s a recent project that data played a vital part in, and what was the tangible impact of that data?

As a lending-as-a-service platform, the data that we provide is perhaps our most valuable asset. It informs our partners about the types of customers coming to the website, the products that are issued to these individuals and the performance of these products.

We recently developed a new data processing platform to compile and send data files to our partners in a more timely and accurate fashion. The new platform has improved the quality of the data sent externally, which has given us a sense of confidence that data definitions are consistent across deliverables, leading to a much more governed and stable data environment.

The data management team measures success by the consistency of the data produced from our systems.”

 

How does your team leverage data to measure and drive success? 

The data management team measures success by the consistency of the data produced from our systems. We measure the accuracy of data points utilizing a suite of data quality checks, which produce a pass rate that can fluctuate based on the state of the system. We also measure the coverage rate of data points by ensuring that the correct checks exist for all key data elements across data deliverables. These metrics influence prioritization for the correction of existing data bugs and development of new data quality suites, allowing us to meet accuracy and timeliness in service-level agreement requirements for data deliveries.

 

GoHealth team outside their office

GoHealth’s Vice President of Advanced Analytics Jeff Gutierrez said his team is hard at work using data to take the stress out of finding health insurance — and that’s no small feat. Here’s how his team’s efforts are creating success for the entire business. 

 

What’s a recent project that data played a vital part in, and what was the tangible impact of that data?

We recently deployed a near real-time projection of the supply of health insurance agents, and of the consumer demand that GoHealth should generate. It uses historical and recent data about phone calls, agent attendance, and digital advertising in predicting how well our plan is tracking reality, and the actions that need to be taken in response to various conditions. Thanks to the data engineering and machine learning work that we have done, we are able to get multiple departments to work together in achieving the overall company execution plan. 

We are able to get multiple departments to work together in achieving the overall company execution plan.”

 

How does your team leverage data to measure and drive success? 

We use our predicted consumer-lifetime-value-per-opportunity to gauge how well our scoring models are performing in near real-time basis. Based on this metric, our marketing and business operations teams are able to make timely business decisions that affect advertising and call routing that have direct impact on the company’s bottom line. The metric also informs the business analytics team on how effective our model feature engineering is between production releases.

 

PEAK6 team working in their office

When working with people’s money, a company’s data needs to be kept very up to date and well-organized. Data Team Lead Paul Whalen and his crew of engineers at investment firm PEAK6 are on a mission to modernize the company’s critical data, helping employees throughout the business do their jobs more efficiently.

 

What’s a recent project that data played a vital part in, and what was the tangible impact of that data?

At PEAK6, the availability of data is critical to the success of every piece of software and business function. It is largely the data development team’s responsibility to ensure that data sourced from external vendors is available promptly and accurately for any internal consumer. This team is currently in the process of modernizing how we ingest data, moving from one-a-day batch jobs based on the MS SQL server toward a real-time data streaming pipeline heavily reliant on Apache Kafka. We made this decision for a few reasons: it enables real-time processing using general purpose programming languages, but more importantly, it decouples the source and processing of data from its resting state and end users. This is critical because the access patterns of different users for the same type of data can vary greatly, and storage techniques for a certain type of data might need to be different for  different usages of the data.

We’ve enhanced internal Python and Java libraries used by a wide variety of users to actually expose tracking data about their usage.”

 

How does your team leverage data to measure and drive success? 

Since the data dev team is the provider of such a wide variety of data, it’s up to every other team — from traders to analytics to operations — to make good use of it. But because there is such a wide variety of data at PEAK6, it can be hard to track which specific data points are being used productively and should therefore be maintained or enhanced by the data dev team, and a few efforts have emerged to tackle this challenge. We’ve enhanced internal Python and Java libraries used by a wide variety of users to actually expose tracking data about their usage — both how much a certain function or data point is used, and the actual flow of the data — so we can track what raw data was used as an input for a more complicated calculation.

 

KAR team working in themed conference room

We buy cars from car dealerships based on a number of personal needs, but how do those same dealers decide which cars they should buy? Data Science Manager Jeremy Mobley and his team at KAR work to make these choices easier for dealers by recommending vehicles to them based on data sourced from emails, clicks and eventually, dollar signs. 

 

What’s a recent project that data played a vital part in, and what was the tangible impact of that data?

Data is critical to everything we do. My team’s primary focus is on recommending vehicles to used car dealers. We combine data from a variety of sources, clean it up, and optimize it to build a model for making the best recommendations possible. The data comes from dealers’ past vehicle purchase history, their retail listings, recent market trends and dealers’ past interactions with specific types of vehicles.

We use machine learning to combine all these data points together to identify and recommend the most relevant vehicles for each dealer. We push these recommendations out through a variety of channels — from tailored emails to our inside sales teams to the used vehicle marketplaces powered by our company’s platforms. And we’re constantly looking for a new way to get the best information in front of dealers to help them make smarter buying decisions.

We have a data-driven business process that analyzes the potential impact of different products we’re considering building.”

 

How does your team leverage data to measure and drive success? 

We measure the product’s effectiveness with a variety of metrics, many of which are pretty standard, like email opens and click rates. One of the more interesting metrics we look at is purchase efficiency — how many vehicle pages a dealer views before a bid or purchase — to better understand how effective the recommendations are at influencing dealer behavior. The eventual metric we’re driving toward is sales — opening an email is good, a click is even better, but if they’re buying the car we’re actually recommending, that’s the best.

Beyond that, we have a data-driven business process that analyzes the potential impact of different products we’re considering building. This helps us determine where we spend our time and resources, the products we develop and the features we invest in. Data helps us determine where we can have the most impact.

 

Payformance team at a beach outing

Director of Analytics Matt Beatty and his team at Payformance recently ran a project that saw hundreds of millions of data points digested and analyzed in a few hours — all to benefit the hospital care that mothers received surrounding the birth of their new babies.

 

What’s a recent project that data played a vital part in, and what was the tangible impact of that data?

In a recent project with a large, state Medicaid agency, we used baby delivery data to show the variation in practice patterns between hospitals adjusted for the risk and age of the mother. In a few hours, we used two-and-a-half years of complete state Medicaid claims — over 300 million claims for over 2 million members — to create an analysis that looked at the variation of C-section rates by facilities, adjusted for risk. This would have taken days or weeks in the past. It allowed us to quickly respond to an ad hoc report request from a client and allowed them to show that even for low-risk moms, there is significant variation and opportunity to improve the quality of care across the state.

We are looking at metrics that quantify waste and measure quality in healthcare, like Potentially Avoidable Complications.”

 

How does your team leverage data to measure and drive success? 

Data is always a vital part of every project we do. Making use of data from healthcare claims can be fraught with challenges. We are looking at metrics that quantify waste and measure quality in healthcare, like Potentially Avoidable Complications. These inform us of the opportunities for savings through waste reduction and improvement in quality for a specific care continuum at the provider level.

 

SpotMe team doing a weird dance

After facing some project-based challenges, live event engagement platform SpotMe decided to launch a strategy to dive deeper into how it can better resolve and prevent similar, future issues. Ivan Probst, vice president of professional services, said understanding what went wrong and why, as well as getting feedback from clients, will improve the company’s work moving forward.

 

What’s a recent project that data played a vital part in, and what was the tangible impact of that data?

Inspired by aviation and other industries where mistakes can have a life-or-death impact, we wanted to create a space for our team to share and discuss problems that affect our customers. As a result, we implemented our own incident management system, called the Collective Breakthrough. The CB initiative is a reporting system used to describe an incident that may occur during a project. Once reported, it automatically alerts the account and line managers, who take over to solve the challenge at hand. At a later stage, we do an in-depth post-mortem, identifying the root causes of the problem. Finally, we discuss if anything can be changed that would prevent the incident from happening again, and leverage common use cases for dedicated training sessions. 

Thus far, we have collected a handful of reports, which have successfully helped encourage accountability – one of our core values. This has also helped spread trust quickly throughout the organization – a key enabler for a fast-growing and ever-evolving company like ours. 

Customer feedback has had a significant impact on our company, leading to product releases, organizational changes and improved internal procedures.”

 

How does your team leverage data to measure and drive success? 

We strongly believe in genuine customer feedback, and will take every opportunity to capture and leverage it to improve our product and company performance. Our main quality performance barometer is the Net Promoter Score. It informs us on the satisfaction of our services, the quality of our product and the impact our solution had on achieving our customers’ goals. For any score that is not satisfactory, we lead both an internal and customer investigation to understand where we felt short. Based on the results, relevant teams assign time to adjust and correct course, keeping our customers informed in the process. 

Positive feedback also contributes to our success, helping us position ourselves as a leader in our market. Additionally, customer feedback has had a significant impact on our company, leading to product releases, organizational changes and improved internal procedures. We strongly believe we owe our NPS of 70 not only to our team, but also to our customers’ trust and their candid feedback.

 

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