Case study

Meet the Studio: LAIKA

Year Founded: 2005
Original Feature Films: 5
Shotgun Users: ~ 300
Favorite Shotgun Features: API

Scheduling Time Saved

By Michael Nowakowski, Pipeline Technical Director, LAIKA

Stop-motion animation studio LAIKA is the creative force behind some of the most inventive feature films of the last 15 years. Merging the old-world craft of puppetry with advanced CG technology and visual effects, the studio aims to tell big, bold stories in its own distinct aesthetic. Based in the Pacific Northwest, near Portland, Oregon, LAIKA has received an Academy Award nomination for every original film it has created to date, including Coraline, ParaNorman, The Box Trolls, Kubo and the Two Strings, and Missing Link, and was awarded a Scientific and Technical Oscar for its innovation in 3D printing in 2016.

The challenge

LAIKA’s craft-based approach to filmmaking is inherently complex, and each project is a massive undertaking. Stop-motion animation requires the creation of thousands of sets, props, puppets, and costumes that must both express the creative language of the film and be able to be rigged and animated in painstaking frame-by-frame detail. Perhaps even more daunting, work must be coordinated between our fabrication groups to ensure all our assets fit into the same world, and are delivered to the appropriate stages in time for their moment in the spotlight. A schedule is an essential part of enabling this intricate filmmaking machine. It helps us allocate resources for our production, and ensure we're hiring an appropriate number of people with the right skills. The schedule also provides prioritization for our work, so we know what is due when and who should be working on what, allowing us to work as efficiently as possible, and it’s an important communication tool.

As our films have grown in complexity and scale, maintaining an accurate schedule and leveling resource has become more of a challenge since much of this process has been done by hand and informed by gut instinct. Without effective tools to evaluate and adjust the schedule to accommodate changes, crafts people often ended up overworked and assets delivered late, which slowed the pace of shooting and made it harder for downstream departments, like rigging, camera, animation, and visual effects, to meet their deadlines. We needed to develop a new scheduling system that could be used studio-wide and enable faster iteration as well as better resource leveling and visualization.

The solution

We were already heavily invested in production tracking, reporting and distributing schedule information with Shotgun, so we decided to follow a progressive enhancement strategy, and build a new, browser-based workflow on top of it to meet our needs. Using a Gantt tool for data modeling, Shotgun for day-to-day task management, and a new program initially called Consilium (recently acquired by Autodesk) that leverages machine learning for resource balance and leveling, our upgraded workflow allows users to quickly iterate on a complex fabrication schedule. Accurate and easily shareable schedules can be generated in minutes and adjusted on-the-fly to account for different variables, such as project timeline and artist headcount, transforming a previously time-consuming and error-prone process.

Since Shotgun is already central to how we work, we kept a familiar UI so Shotgun users can continue to work as they always have, but with access to custom tools when they need extra features, like auto scheduling and leveling.

The features

At LAIKA, scheduling starts with a bidding process, during which departments estimate the work necessary to create each asset by breaking them down into a list of tasks with durations, resource assignments, and dependencies on other tasks. These tasks lists are then brought into our production database and leveled to ensure that each task is completed in time for other departments to complete their work, each asset is delivered in time for its scene shoot date, and that no group or person within each department is overloaded with tasks. Balancing these goals is an incredibly difficult and time-consuming job that takes years of experience to master, especially given the complexity of a physical production schedule. LAIKA's current project consists of 12,000 tasks spread across 300 physical assets, and balancing the workloads of 60 people with 15 different skill sets.

With our previous scheduling solution, we ran into major limitations. Initial bidding often took weeks, data could easily get out of sync when doing updates, and hand-leveling such an enormous dataset is laborious. Every push or pull in the order of tasks to benefit one group tends to come at the expense every other group. Perhaps even worse, a hand-adjusted schedule can be quickly made obsolete from daily changes in the shooting schedule, R&D timeline, or to the story itself. In improving the process, we also wanted to be smart about our development and not re-invent our entire workflow.

Since Shotgun is already central to how we work, we kept a familiar UI so Shotgun users can continue to work as they always have, but with access to custom tools when they need extra features, like auto scheduling and leveling. We also found Consilium, a new solution that leverages machine learning for resource balance and leveling. The technology (since acquired by the Shotgun team at Autodesk) enables a user to create different scheduling scenarios, where they specify parameters for how many tasks should be assigned to a resource in as little as a few seconds. Once the user has entered their targets and pressed schedule, its scheduling engine searches for a way to adjust task start dates for the schedule while still satisfying all constraints and dependencies, so that each resource is as close as possible to its target curve. When we started overhauling our workflow, Consilium was a standalone program, but now its powerful machine learning abilities are being integrated directly with Shotgun as a Generative Scheduling feature.

The first time we successfully got a schedule from Consilium back into Shotgun was a big ‘aha moment.’ Instead of having to manually level out 12,000 tasks, we were able to just press a button and get a schedule round trip back to Shotgun. And with Consilium functionality being built directly into Shotgun, I’d imagine even greater gains will be realized in the near future.

Consilium’s machine learning technology is being used in production at LAIKA for managing tasks in several departments, most notably as the means for scheduling the Puppets department. Whereas a human-leveled schedule takes weeks to build, with machine learning, we are able to generate scenarios in less than a minute and receive more efficient results. For example, provided the same data and 3.5-year time frame to shoot a film, a human-leveled schedule projected that 334 assets would be needed while using machine learning to level the schedule projected 251 assets. Considering each asset is physically created by hand, that’s a significant difference. With machine learning, we can also easily adjust the parameters for schedules for other scenarios, discovering that shaving a year of the project timeline would require the creation of 308 assets and reducing the timeline by six months would require the creation of 270 assets, all in a matter of minutes.

Our new scheduling workflow has made a big impact at LAIKA. Changes are now significantly easier to accommodate, and there is increased confidence in the scheduling process. Filmmaking at LAIKA happens over a very long time frame, with each film taking several years to complete, so we won’t have a full sense of the time or cost savings for a while, but the results so far have been quite promising. Users are able to turn around new bids and resource lists faster than ever before.

The first time we successfully got a schedule from Consilium back into Shotgun was a big ‘aha moment.’ Instead of having to manually level out 12,000 tasks, we were able to just press a button and get a schedule round trip back to Shotgun.