CollisionCast: Repair-planning with Data-Driven Repair Recommendations

Learn how data-driven repair recommendations can assist with increasingly complex repairs.
May 10, 2024

How shops approach repair planning is often not optimal for where collision repair is headed, with added repair cost and complexity. Although much of repair planning is currently focused on identification through the pre-scan, it needs to move to data-driven repair recommendations, says Sam Poradish, director of automotive intelligence at asTech, one of the sponsors of our inaugural Best Repair Planner/Estimator of the Year Award.

About the Author

Jay Sicht

Editor-in-Chief, FenderBender and ABRN

Jay Sicht is editor-in-chief of FenderBender and ABRN. He has worked in the automotive aftermarket for more than 29 years, including in a number of sales and technical support roles in paint/parts distribution and service/repair. He has a bachelor's degree in journalism from the University of Central Missouri with a minor in aviation, and as a writer and editor, he has covered all segments of the automotive aftermarket for more than 20 of those years, including formerly serving as editor-in-chief of Motor Age and Aftermarket Business World. Connect with him on LinkedIn.

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