In 2021 Off the Fence asked Blue Lucy to help them come up with a solution for converting their broadcast catalogue for OTT delivery without adding staff or requiring a significant investment in new technology. The automated solution that Blue Lucy delivered allows the content company to save hundreds of man-hours and deliver on a scale they were never able to before - with almost no human intervention. And as the demand for VOD assets increases, it continues to prove its worth.
Off the Fence is a longstanding BLAM customer. The content company first worked with Blue Lucy to migrate their media management and fulfilment operation to an in-house model using BLAM in 2019. Since then, the OtF team has been iteratively working with Blue Lucy to automate delivery processes in a way that integrates their existing technology with cloud capabilities. In 2021 director of technical operations, Sukhan Bains faced a new challenge: while their huge cloud-based content library consisted almost entirely of broadcast masters, the demand for VOD and OTT content was growing. For VOD deliveries the broadcast masters require editing into a specific structure, as Bains explains, The biggest issue was cost of creation for these VOD / OTT assets. When you archive assets in the cloud every step you take whether it's download, upload etc adds time and money to the equation.
A problem of scale Initially, Bains' team was able to keep on top of demand by manually creating the VOD and OTT deliverables from the broadcast masters. The source broadcast masters were restored from the library, downloaded and edited on site, before being rendered and uploaded back into AWS for BLAM to pick and manage the delivery. But, in addition to the costly egress fees that this process involved, Off the Fence's operations team quickly ran into capacity issues. As well as the time spent downloading, rendering and uploading media in its round trip to the cloud, editing the content was a time-consuming, albeit straightforward, task. Bains' team had to manually seek within each programme and mark cut points to remove broadcast elements like colour bars, slates and ad breaks as well as select the appropriate audio tracks so that only the active programme would be delivered. They also faced technical constraints, We're quite a small organisation and internet bandwidth is valuable - we can't just brick the network any time we want to upload assets, says Bains. With few solutions available at the time, and none that met OtF's cost and efficiency requirements, Bains asked Blue Lucy to collaborate with his team to automate the process in BLAM.
Going from a manual workflow to managing by exception Analysis of the material highlighted one crucial factor working to their advantage: all of OtF's content has black and silent frames between the slate and the active programme, in the ad breaks and at the end of the programme - at all the points where cuts are needed to select only the active programme. So, the teams began by exploring ways to automatically detect and create cut points where black frames and silence happen at the same time. The solution they devised relied on refining the tuning parameters of BLAM's existing technology integrations to create a black and silence detection microservice that works in combination with (and enriches) the existing QC data. When a new order for VOD content comes in through Off the Fence's rights management system, BLAM triggers the relevant automated workorder. First, the black and silence detection microservice detects where the cuts should be and creates an EDL for the proposed edits, then the EDL is automatically sent to Bains' team for verification using a timeline view in the platform. Once approved, the EDL is rendered using AWS MediaConvert before delivery. The BLAM platform manages the automatic scaling of the microservice instances to avoid bottlenecks during peak demand periods. Bains describes it as a crazy improvement saying, At the end of year Christmas rush we did around 1500 hours of deliveries through BLAM and a huge percentage of those were to VOD platforms. We just shoved them through the workflow, with a few hands-on-deck to do the approvals, and all of a sudden, this single-transcode and single-thread workflow was now autoscaling so there was pretty much no limit to how many files we could handle at the same time. I don't think we'd have been able to deliver half as many assets without it.
Ongoing benefits The obvious (and possibly most important) benefit of automating the conversion of broadcast content for OTT and VOD delivery is scalability. Bains estimates that their throughput increased by five times from one month to the next - with almost no human intervention. But, almost four years later, their decision to continue to use a trusted automated workflow, rather than exploring newer AI-enabled options, is driven by multiple factors: as it's entirely cloud-based, the workflow doesn't result in any additional egress costs and uses standard off-the-shelf Blue Lucy microservices. Off the Fence convert their catalogue based on customer demand and can choose to save already edited assets or to delete the edited files to reduce storage costs, retaining the EDL for re-rendering should new orders come in.
The implementation of this workflow has been a huge help for us in a struggling industry where we're trying to pivot to benefit from new areas. Leveraging BLAM to do the heavy lifting has removed some of the biggest hurdles for our OTT workflow,' says Bains.
Get in touch to find out how Blue Lucy can help you save time and money across your content supply chain.
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In 2021 Off the Fence asked Blue Lucy to help them come up with a solution for converting their broadcast catalogue for OTT delivery without adding staff or requiring a significant investment in new technology. The automated solution that Blue Lucy delivered allows the content company to save hundreds of man-hours and deliver on a scale they were never able to before - with almost no human intervention. And as the demand for VOD assets increases, it continues to prove its worth. 
