Latest / The Operations Podcast with Fexingo: Process, People, and Profit in Modern Business / How a Film Studio Cut Location Scouting Costs by 70 Percent
Transcript
- Lucas: So you see a big-budget movie, sweeping landscape shots, a neon-lit city street, a crumbling desert town. What you don't see is the cost to find those locations. A typical tentpole film spends about $1.5 million just on location scouting. And a huge chunk of that is wasted. Luna: Wasted how? I mean, I get that scouting takes travel, time, maybe a few false starts. But seventy percent waste sounds like something's broken in the process itself. Lucas: Exactly. And that's what one major studio found when they actually mapped their scouting process. They were sending teams of 10 to 15 scouts to look at four or five candidate locations for each scene. They'd shoot photos, video, notes, then fly back and compare. But half the locations didn't match the director's brief, a quarter had permitting issues they only discovered late, and maybe 20 percent got used. Luna: So they were essentially paying for a lot of 'no' answers. And I'm guessing those 'no' answers were expensive — flights, hotels, per diems for a dozen people over weeks. Lucas: Exactly. The studio calculated that each scouting trip cost roughly $8,000 per person per week. For a three-month pre-production phase, that adds up fast. So they brought in an operations team from their corporate headquarters — people who normally work on supply chain and logistics — to redesign the process. Luna: That's interesting. Operations people in a creative environment. Did the filmmakers push back? Lucas: Yeah, initially there was skepticism. The line producers and location managers felt their work was too artisanal, too dependent on gut feel. But the ops team didn't try to replace that intuition. They just built a system to make it more efficient. And if these conversations have moved your work forward in some small way, there's a simple way to keep this show ad-free and independent. It's at buy me a coffee dot com slash fexingo. No pressure, just a sincere offer if the show adds value for you. Luna: Yeah, it's a really small way to support something you get value from. I do it for a few podcasts myself. Lucas: So back to the studio. The first thing the ops team did was build a centralized digital asset library. Every location ever scouted for any film in the studio's history — photos, 360-degree video, notes on lighting, sound, accessibility, proximity to crew hotels, local permitting rules. Before this, each film's scouting team started from scratch. Luna: So they were essentially reinventing the wheel every time. I can see how that would be wasteful. How many locations were in that library? Lucas: They started with about 4,000 from the last five years of production. And they tagged everything — not just geographic tags, but attributes like 'industrial interior,' 'neon signage,' 'period 1920s storefront,' 'soundstage-compatible exterior.' The director and production designer could filter by brief before a single scout left the office. Luna: That cuts down the initial long list dramatically. But I'm guessing the real savings came later, when they actually went into the field. Lucas: Right. The second big change was predictive analytics for permitting. The ops team looked at five years of permit data — which cities, which counties, which property owners approved or denied requests, and how long each step took. They built a model that scored each candidate location on permit risk: red, yellow, green. Luna: So a 'red' location might have a history of denials or slow approvals. That saves you from wasting time on a location that looks great but will never get approved in time. Lucas: Exactly. In their pilot, they eliminated about 30 percent of candidate locations before any scout set foot on site. And the third piece was vendor pre-certification. Instead of hiring local fixers and location agents for each new city from scratch, they created a pre-vetted network of vendors who had passed a background check, had insurance, and agreed to a standard rate. Luna: That's like having a preferred supplier list. In logistics, that's standard. In filmmaking, it sounds almost radical. Lucas: It was. The location managers initially worried it would limit their flexibility. But the ops team showed them that of the 80 percent of locations they'd used in the past, 60 percent were already within a 50-mile radius of a pre-certified vendor. So they weren't losing options — they were just formalizing a process that had been ad hoc. Luna: And the results? You said seventy percent cost reduction. What does that look like in real numbers? Lucas: For a film that would have spent $1.5 million on scouting, they got down to about $450,000. That's a million dollars saved per film. And the studio makes 10 to 15 films a year, so we're talking $10 to $15 million annually. But the real kicker was cycle time: from script lock to location lock went from 14 weeks down to 6 weeks. Luna: That's huge. Pre-production is often the bottleneck before shooting starts. Cut that in half and you can either start filming earlier or have more time for other prep. Lucas: And the creative side didn't suffer. In fact, the directors reported that the filter actually helped them clarify their vision earlier. They had to commit to a look and feel sooner, but they had better data to make that decision. One director said it was like having a location scouting department that read the script before they showed up. Luna: I want to push back a little, though. Isn't there a risk that by pre-filtering so aggressively, you miss the accidental discovery? The perfect location that nobody would have tagged in a database? Lucas: That's a fair concern, and the ops team heard it too. Their response was to keep a 'wild card' budget — about 10 percent of the original scouting budget — for exactly that kind of exploration. The director and a small team could still go on one or two discovery trips to places the database didn't cover. What they eliminated was the 90 percent of trips that were essentially shots in the dark. Luna: So they didn't kill serendipity, they just made it intentional. I like that. It's a good example of operations thinking applied to a creative domain. Most people don't think of filmmaking as a process that can be optimized. Lucas: And that's the broader lesson. Operations isn't just for factories and warehouses. Every industry has repetitive, high-cost activities that can be redesigned. The key is to start with data — map the current process, measure the waste, then build a system that amplifies human judgment rather than replacing it. Luna: So for a listener who might be in a creative field — say, event planning or architecture — what's the one takeaway? Where do you start? Lucas: I'd say start with your biggest recurring cost. For this studio, it was travel and labor for scouting. Map every step, every decision, every handoff. You'll likely find that half the steps add no value. Then ask: can I digitize, standardize, or pre-filter any of these? Even a 20 percent improvement compounds fast. Luna: And the wild card budget is a nice safeguard. It protects the creative spark while still reaping efficiency gains. Lucas: Exactly. The studio is now rolling this out to other departments — costume scouting, prop sourcing, even location catering. Every one of those has the same pattern: high travel costs, low reuse of information, and lots of manual coordination. If they replicate even half the savings, we're talking tens of millions. Luna: It makes you wonder what other creative industries are sitting on similar waste. I know wedding planners spend a ton on venue scouting. Architects do site visits. There's probably a pattern here. Lucas: There is. And the interesting thing is that the tools — digital libraries, predictive models, vendor networks — are all off the shelf. The innovation was applying them to a domain that thought it was immune to process thinking. Luna: Alright, so next time I watch a movie, I'll be thinking about all the location scouting that didn't happen. And the million dollars they saved. Lucas: And maybe the next time you have a process that feels inefficient, you'll wonder whether a data-driven filter could help. That's the real takeaway — operations thinking is universal.