Melville, NY - SPENCERMETRICS LLC announced its recent donation of the spencermetrics® connect®system to Arizona State University (ASU) Print and Imaging Lab. This is the fourth year of spencermetrics supporting ASU with productivity software donations intended to educate students on the impact of operational efficiency and to support the ASU in-plant print provider by offering Print Lab management with an analysis tool to increase their asset utilization and overall efficiency.
Spencermetrics' most recent donations of its automated connect system are running on ASU's Xerox® iGen® 4 and HP® Indigo® 5500 digital presses. With its unique multi-vendor capabilities, connect allows quantifiable operational metric analyses across multiple press platforms, providing comparisons of shifts, technologies, operators, and performance, all within one software system.
Spencermetrics connect software is the industry's quickest to deploy and easiest to install. According to Chris Halkovic, Digital Workflow and Web to Print Manager at ASU Print & Imaging Lab, "As an IT manager, setting up new software utilities is always a pain, but implementing the spencermetrics connect system was as simple as plugging the machine in and signing into the iPad app. We were up and running in just a few minutes." Data collection and analysis began immediately after installation. Halkovic added, “The ease-of-use of any system is very important, especially when integrating into an already-busy workflow. The spencermetrics connect system provides incredibly simple functionality for collecting data." connect has streamlined processes and has since eliminated the manual input of data from ASU’s operators.
The connect system provides actionable information, turning raw data into knowledge and facilitating timely decision-making. "The analytics provide data that our operations staff always wished for, but never had the time or resources to manually compile," stated Halkovic. "We’ll be using this information to see where we need to focus on training our press operators and to provide a better insight as to optimizing our equipment and labor resources for maximum efficiency."