Music industry uses big data to track royalties

By Russ Banham The music industry has changed dramatically in the last couple decades, except for one domain — how television, film, video game and other producers of creative content license music tracks. Now, thanks to data analytics, APM Music believes that it has found a way to improve the system by enabling customers, who include major entertainment studios, to access musical tracks more easily from the Los Angeles-based company’s huge library. The system also keeps closer track of payments. APM’s previous system involved producers manually filling out a cue sheet listing the title of a track, the performer and the duration of the piece. The cue sheet was delivered to the American Society of Composers, Authors and Publishers (ASCAP), a professional society representing composers and musicians. Based on the data, ASCAP ensured the producer paid APM Music, which in turn pays the composer (APM licenses music). With APM’s more than 400,000 music tracks available to producers, this antiquated process made it difficult to account for the proper income. “The problem is that the cue sheets are not always filled out correctly,” explains Barry Massarsky, president of Massarsky Consulting, a New York-based music industry economist. “This creates the risk of lost royalties for both the licensing company and the performer.” Since APM Music has many tracks routinely playing at any given time in the background of movies, TV episodes and video games, the lost royalties can add up to a lot of money. “We’re a bit like Wal-Mart — a penny business,” says Adam Taylor, APM Music president and vice chairman. “We’re licensing a Rolls Royce product at Chevy rates, based on what the client needs.” Major clients for APM Music’s tracks include the producers of “Mad Men,” “Boardwalk Empire” and “Dexter” — thanks to its large collection of early ‘60s music, ‘20s music and Cuban music, respectively. “We’ve got 20 different versions of Auld Lang Syne that companies can choose to use, which compounds the complexity,” Taylor says. “To make sure money doesn’t slip through the cracks, we needed a better way of accessing and measuring data.” Read the full article here:

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