by Thor Olavsrud

Real-time analytics: 4 success stories

May 07, 2020
AnalyticsData ScienceDigital Transformation

These five companies are using real-time analytics to improve agility, respond to customers as needs change, optimize pricing, and identify inefficiencies affecting their bottom line.

data analytics / risk assessment / tracking data or trends
Credit: ipopba / Getty Images

For companies seeking value from data as it flows into data systems, real-time analytics is the way to go. This emerging discipline blends technology and processes to help enterprises improve internal workflows or to provide insight into customer activities and marketplace trends as they unfold.

Real-time analytics strategies provide business agility, whether they are outfitted to help your organization respond to customers as their needs change, optimize pricing as market conditions fluctuate, or identify inefficiencies in business processes that affect your bottom line.

Companies are increasingly turning to real-time analytics for competitive edge, in particular to streaming analytics, which analyzes data in-flight. Grand View Research forecasts the global streaming analytics market will grow at a compound annual growth rate of 29 percent through 2025, starting from $6.32 billion in 2018, as businesses invest to improve their performance and operations.

Here are four examples of how organizations are using real-time analytics today.

Real-time data helps Bayer reshape business strategy

Bayer Crop Science has created “virtual factories” to provide dynamic digital representations of the equipment and processes of its nine North American corn seed manufacturing sites. The project, dubbed “Shaping Business Strategy and Future Operations Through Virtual Factory,” has created a dynamic representation of the equipment, process and product flow characteristics, bill of materials, and operating rules for each of the nine sites.

As the company’s commercial team introduces new seed treatment offerings or new pricing strategies, the business can use the virtual factories to assess each site’s readiness to adapt its operations to deliver those new strategies, says Naveen Singla, the Data Science Center of Excellence lead at Bayer Crop Science.

“Now we can reimagine our business processes. We can reimagine our decisions through the application of these machine learning algorithms or simulations,” Singla says, adding that the company can now answer complex business questions regarding the SKU mix, equipment capability, process order design, and network optimization.

Singla’s advice: Know the business. Singla credits the time Shrikant Jarugumilli, head of decision science – connected virtual systems at Bayer Crop Science, and his team spent at manufacturing sites to learn the ins and outs of their seed manufacturing operations. “Having our data scientists understand the domain of the business has been so critical,” Singla says.

Penn Medicine uses real-time data to shorten ICU stays

Many patients in hospital intensive care units (ICUs) depend on ventilators for survival. Getting critically ill patients breathing on their own is an essential step towards getting them safely out of the ICU and freeing beds for other patients. Penn Medicine is using real-time analytics to help it more efficiently identify when patients are ready to come off ventilation.

In 2016, Penn Medicine (consisting of the Raymond and Ruth Perelman School of Medicine at the University of Pennsylvania and the University of Pennsylvania Health System) started developing a dashboard that leverages its electronic health record (EHR) vendor’s real-time data streams to alert respiratory and nursing staff when interventions are needed and when patients may be ready to be weaned from ventilators.

Implementing the application — dubbed ABC, for Awakening and Breathing Coordination — required Penn Medicine to bring together its Penn Center for Health Care Innovation with the information services (IS) and data science departments. The innovation center and IS built the dashboard based on clinical decision support rules engines and alerts created by Penn Medicine’s clinical experts and programmed by the data science department.

“This was the first project that really drove the deep collaboration with these three departments,” says Michael Draugelis, chief data scientist at Penn Medicine. “That project, that interaction, has adjusted the way that we work. We’re organizationally shifting in how we manage our projects.”

In 2019, Penn Medicine said ABC had reduced the time ICU patients spent on a mechanical ventilator by more than 24 hours.

Draugelis’s advice: Focus on the data, not vendors. One of the biggest delays in the project stemmed from Penn Medicine’s decision to change its electronic health record (EHR) vendor months into the pilot. But the organization focused on how it could use data and ultimately gained valuable experience that helped create a better application. “Building our first deployment on our first EHR definitely drove the requirements in terms of how we wanted to interface with our new EHR and that process generalized our interfaces with those two different systems,” Draugelis says. “It made it more robust and helped us have a more foundational build with our current system.”

Land O’ Lakes optimizes sales and marketing with real-time analytics

Land O’ Lakes Data to Value program brings AI techniques to bear on the company’s sales and marketing efforts. The project leverages data analytics tools and disparate data sources to provide visibility into the company’s profitability, sales call success factors, and commodity markets.

The program includes propensity modeling to identify which dairy sales prospects have the highest propensity to buy at the highest volumes, while commodity forecasting helps the company’s risk management team drive decisions around hedging, inventory strategy, and spending.

“Due to the efforts and output of this project, we have greater confidence than ever that our salespeople are equipped with the right products at the right prices for the right customers,” says Jeremy Dumond, director of business intelligence at Land O’ Lakes.

As of 2019, Data to Value had helped Land O’ Lakes improve its success rate on sales calls by more than 40 percent.

Dumond’s advice: Find partners in the business. Dumond says the project’s biggest challenge was selling the improvement potential of the model to the internal sales organization. Seeking sponsorship from business leadership with the credibility to get the sales organization on board was essential. “Building a marketplace-backed project plan, in partnership with trusted business leaders and a commitment from the top of the organization, are foundational to success,” Dumond says.

Jackson Health System taps data flows to improve care

Jackson Health System (JHS), a nonprofit academic medical system in Miami, Fla., and one of the largest public health systems in the U.S., is utilizing real-time analytics via its Overwatch data integration program to help it cut costs and ease pressures on its emergency departments (EDs).

JHS’s Population Health team came to the JHS IT team in 2017 with a problem: It needed to identify ‘high utilizers’ of its ED. High utilizers are patients, typically underfunded, who use the ED for primary care, generally because they aren’t aware of other options. The Population Health team needed a way to identify these patients when they visited JHS facilities, so they could engage them and enroll them in a funded program that would provide appropriate and ongoing care that wouldn’t tax emergency services.

“We had all this information flowing through this engine and we delivered it to these individual systems, but we didn’t take advantage of the fact that we have it all sitting in this engine in transit and in real-time,” says George Rosello, associate director of enterprise application integration at JHS.

Overwatch leverages the data already flowing through the JHS integration engine, providing real-time alerts via text and email to appropriate case managers when ED high utilizers enter one of the JHS EDs, providing information about the patient, what service line they’re in, where they’re currently located, and what’s currently being done with them.

“It’s allowed us, as a community safety-net hospital, to do our mission statement, which is to get those patients to appropriate care, get them to the right charity care, and get them the help they need,” Rosello says. “We had patients that were just coming in, getting stabilized, and leaving. Now they’re getting persistent care that’s addressing the root cause of their problems and they’re healthier for it.”

Rosello’s advice: Know how you will measure success. “When you have a project, especially projects that take a while, the end goal of the project ends up being finishing the project,” Rosello says. “But that’s not what it started as. Not losing sight of the end goal is a challenge and something I would advise anyone to keep an eye on. What’s the real success factor of your project?”