To understand how data analytics can transform meeting planning, forget about meetings and consider how UPS saved $320 million. The shipping company created an analytics system called Orion — short for On-Road Integrated Optimization and Navigation — to increase efficiency and decrease costs. Developed over a 10-year period, Orion uses algorithms and fleet telematics (a tracking system for its trucks) to provide drivers with the best delivery routes. Orion is so sophisticated that it minimizes left- hand turns: Turning left takes longer than right-hand turns and vehicles spend more time idling.
Thanks to Orion, UPS has reduced drivers’ trips by about 100 million miles annually. The company’s fuel consumption has dropped by about 10 million gallons a year, which cuts its carbon emissions by roughly 100,000 metric tons. A reduction of one mile per driver, per day, saves the company up to $50 million per year, according to UPS — proof that small changes, driven by complex algorithms, can have major benefits.
“UPS has information on how many footsteps a driver takes to deliver a package — they’re using pure mathematical-model analytics,” said Najaraj Reddi, director of information technology for the Catonsville, Maryland–based Institute for Operations Research and the Management Sciences (INFORMS), an international organization of 12,500 operations research and analytics professionals and students. “It makes them more efficient and it improves their customer service.”
Reddi is interested in UPS not simply because he’s a data geek, or because UPS is a member of INFORMS, or even because UPS won INFORMS’s most prestigious prize in 2016. It’s because systems like Orion represent huge possibilities and potential for associations and meeting organizers. That’s why Reddi and his colleagues are about to take their first steps — or a significant left turn — to bring sophisticated analytics to INFORMS.
PREDICTING BEHAVIOR
Shelley Renn, director of meetings for INFORMS, can already access plenty of data about the organization’s events. INFORMS tracks attendees’ Internet usage to determine the bandwidth it will need for future events, and relies on Tableau software for data visualization, among other processes. But Renn is eager for an analytics program that can help her make better decisions.
“I analyze our data every year before our planning process,” Renn said. “But it’s a manual process. I’m looking at it and saying, ‘This is what I see and this is how I might use it.’”
Reddi and Renn expect to implement a data-analytics system within the next three to five years. Because INFORMS focuses on analytics and predictive behavior, it will work with one of its members to develop the program. The goal is to dive more deeply into the organization’s data and provide Renn with more nite information, particularly on attendee behavior, from price points — “What can the market bear? Is our rate structure on target? Are we too high or are we too low?” — to the popularity of programs and event locations.
“There’s a pattern to how people attend our events,” Reddi said. “Demographically, certain people are coming from Germany, Japan, or other countries. But why are they coming from those places? What are their backgrounds, what are their age groups, and what do they get out of this meeting? We want to see the behavior patterns. And based on those patterns, we can recommend that they attend other events and show them the benefits.”
Renn also wants the system to improve efficiency at events. How many radios do they need? How much staffing is required based on the number of attendees and the time it takes to register? “The data may give us information that we didn’t think about, and lead us to another place,” Renn said.
“Sometimes you think you’re hitting the mark, but that data can tell you, ‘Uh-uh — you’re not hitting the mark.’”
EMBRACING THE POSSIBILITIES
Building a data-driven organization isn’t easy. It requires a significant financial investment and support from upper management. It means creating a comprehensive data infrastructure. And too often, data isn’t consolidated. “It’s all over the place,” Reddi said. Frequently, he notes, emphasizing analytics requires a culture change. But however difficult the process, the payoffs are immense — which brings us back to UPS, where analytics are a large part of the company’s identity, and where they will only become more powerfully predictive.
“Imagine a data architecture and an analytics system of the future that predicts a problem is going to exist and solves it before you even know something is wrong,” Jack Levis, UPS’s senior director of process management, said in an interview with NetworkWorld.com. “We’ll look like Sherlock Holmes. And that’s where I think we’ll be one day.”