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The workday ends and office lights dim, but Cornell’s systems continue sending data where it needs to go. Files move between university and vendor systems, internal data flows behind the scenes, and time sensitive processes—such as financial transactions and system jobs—often wrap up in the wee hours of the morning, when the people who rely on that work are fast asleep.
Cornell’s digital night shift, the Production Control team, keeps those systems, processes, and data moving.
Using automation, Production Control designs workflows that run reliably on a schedule or in a specific order—without requiring someone to be logged in. The team monitors these processes around the clock, investigates issues if something doesn’t run as expected, and steps in to get things back on track, ensuring work is completed and ready when departments need it. This continuity helps minimize human error and allows units to focus their time and resources elsewhere.
Once upon a time, Production Control relied on three shifts of employees to keep data flowing around the clock. As technology evolved, the team introduced automation to provide new options for 24/7 execution and monitoring of business activities. Automating work that once depended on manual, time intensive processes allowed the team to significantly expand its scope.
The move to Tidal Automation Software in 2011 marked a turning point. As scheduling and monitoring became automated for systems like Kuali Financial Systems and PeopleSoft, the team was able to shift its focus—supporting file exchanges with vendors, moving data between campus systems, and managing multi step workflows that once required manual intervention.
“Automation let us move past just running jobs,” said Amber Aiken, Manager of Production Control Operations. “Now we’re actively supporting our customers—watching workflows, jumping in when something breaks, and helping departments trust that their data will be there when they need it.”
Explore Automation for Legacy and Fragile Processes
For many departments, the warning signs are subtle. A process works—until it doesn’t. Someone logs in manually “just for now.” A spreadsheet gets emailed one more time. A task depends on one person remembering to do it every day. These are often the moments when people think, “I wish we could automate this.”
Do any of these scenarios feel familiar?
- You log into a vendor website every day to download or upload a file—often manually and often hoping you don’t forget.
- You regularly send data to an outside vendor for processing using a setup that “works as long as nothing changes.”
- You run PeopleSoft jobs by hand or wish you could connect several steps into one reliable workflow.
- One person knows how a process works, and if they were out—or left Cornell—no one is quite sure what would happen next.
Situations like these are common, and they often signal that a process has simply outgrown its original design. Production Control partners with departments to automate and stabilize these workflows, reducing risk and improving reliability. Even as future reviews through efforts such as Resilient Cornell and CEMI take shape, automating fragile or manual processes today can help smooth transitions if changes are needed down the road.
Collaborating with the Production Control team can free up resources in units that still rely on manual or legacy solutions.
As Aiken put it, “We work to automate repetitive tasks so departments can use their time and resources more effectively.”
By using clear documentation and proven approaches, the team ensures processes run smoothly and securely. Aiken is confident in the team’s reputation as a partner that departments have trusted to reliably handle their critical data.
“Team member names and tasks may have transitioned over the last fifty years, but at the end of the day, what we do hasn’t really changed,” Aiken added.
“We still show up every day to support our customers—finding better ways to run their processes so they can focus their energy elsewhere, and so together we can support Cornell’s mission.”
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