Before in-plants can take full advantage of artificial intelligence (AI), they need to rethink the metrics they track. Traditional measures such as pages printed, jobs completed, and monthly volume show how busy a shop is, but reveal little about its efficiency or profitability. This is one of the key points Consultant Howie Fenton makes in his latest blog post, "Why Metrics Are the Key to AI Improvements in Operations."
“AI will not improve print production unless it has the right data," Fenton writes. "And the right data starts with better metrics.”
Fenton urges printers to focus on actionable metrics that reveal where production problems occur. These include queue time, rework rates, on-time delivery, equipment uptime, and estimated-versus-actual production time. Such measurements can uncover bottlenecks, wasted labor, unnecessary rework, and jobs that cost more to produce than expected. Workflow software such as RSA's WebCRD, QDirect, and ReadyPrint can help create more consistent processes and provide the job-level data needed to identify these problems.
Ultimately, Fenton argues, preparing for AI requires more than investing in new technology. In-plants must first develop better measurement practices and understand how jobs move through production. With accurate, detailed data, future AI tools will be better equipped to predict problems, recommend improvements, and help shops increase productivity and profitability.
Read Fenton's full blog post here.
Preparing for AI Starts With Better Data
Before in-plants can take full advantage of artificial intelligence (AI), they need to rethink the metrics they track. Traditional measures such as pages printed, jobs completed, and monthly volume show how busy a shop is, but reveal little about its efficiency or profitability. This is one of the key points Consultant Howie Fenton makes in his latest blog post, "Why Metrics Are the Key to AI Improvements in Operations."
“AI will not improve print production unless it has the right data," Fenton writes. "And the right data starts with better metrics.”
Fenton urges printers to focus on actionable metrics that reveal where production problems occur. These include queue time, rework rates, on-time delivery, equipment uptime, and estimated-versus-actual production time. Such measurements can uncover bottlenecks, wasted labor, unnecessary rework, and jobs that cost more to produce than expected. Workflow software such as RSA's WebCRD, QDirect, and ReadyPrint can help create more consistent processes and provide the job-level data needed to identify these problems.
Ultimately, Fenton argues, preparing for AI requires more than investing in new technology. In-plants must first develop better measurement practices and understand how jobs move through production. With accurate, detailed data, future AI tools will be better equipped to predict problems, recommend improvements, and help shops increase productivity and profitability.
Read Fenton's full blog post here.
Bob has served as editor of In-plant Impressions since October of 1994. Prior to that he served for three years as managing editor of Printing Impressions, a commercial printing publication. Mr. Neubauer is very active in the U.S. in-plant industry. He attends all the major in-plant conferences and has visited 200 in-plant operations around the world. He has given presentations to numerous in-plant groups in the U.S., Canada and Australia, including the Association of College and University Printers and the In-plant Printing and Mailing Association. He also coordinates the annual In-Print contest, co-sponsored by IPMA and In-plant Impressions.