Web-based solution for media asset management (MAM), workflow automation, and project planning provides a single platform through which providers can effectively manage and scale all elements that contribute to the production workflow.
Building a iTunes, Netflix, and UltraViolet ready environment.
Rising consumption of content across online and mobile platforms, as well as on conventional broadcast services, is pushing many media companies into the business of multiplatform content creation and delivery. Karl Mehring, senior product manager MRM at Snell examines how new multiplatform delivery presents content providers with a host of new challenges.
Traditional workflows weren’t created to support the preparation of content for delivery to multiple distribution outlets, or “TV Everywhere.” Multiplatform delivery demands management of a much higher volume of media and metadata, as well as more extensive processing of media so that outputs conform with the specifications or profiles required by different consumption platforms, such at iTunes, Netflix, and UltraViolet.
When building new file-based workflows to accommodate new multiscreen offerings, media companies are running into a variety of issues that can compromise both operational efficiency and the quality of content being consumed. Issues common today include bulky or erratic media processing workloads, duplication of processes across workflows, inefficient or ineffective quality control, management and correction of audio loudness and language, and inefficient repurposing of media for services such as VoD.
Issues in File-Based Workflows
While the concept of workflow is straightforward, a linear and sequential approach to processing and other tasks is insufficiently sophisticated for the management of multiplatform content creation and delivery. In practice, key manual and automated processes ranging from QC to closed-captions validation to transcoding typically are interdependent and often reference one another, or link back on themselves throughout the content life cycle. By necessity, content enters and exits the workflow at various points and follows one of numerous possible paths in between. This circumstance can give rise to issues, both large and small, that threaten the efficacy of the file-based workflows used for multiplatform content delivery.
Problems leading to erratic media processing workloads, for example, can begin right at ingest. Media acquired from a third-party may somehow be incomplete, missing an element such as an audio track. When incoming content is checked manually for such errors, time is wasted as an operator waits for files to arrive. When many files arrive simultaneously and require checking by that same operator, a bottleneck is created.
Issues extend into automated processing tasks, as well. Because many facilities build in processes and devices organically to meet emerging requirements, they often work with multiple systems and variants of those systems, each of which must be handled differently. These systems may be QC stations and devices, loudness monitoring and control systems, or conversion systems. When these systems are treated as discrete units within the workflow, it becomes difficult and time-consuming to alter, refine, or extend that workflow and its capabilities.
Duplication of processing tasks is another common problem in multiplatform content creation and delivery workflows. It is not unusual for a facility to ingest one source file multiple times, QC each resulting file, transcode that content, add elements such as branding, and then output multiple versions for different target platforms or devices. In some cases, and especially in the repackaging of content for VoD services, there are as many separate workflows running in parallel as there are intended outputs.
By bringing all such tasks and workflow elements under the umbrella of workflow automation, the media company can optimise processing and device utilisation, keeping content constantly churning through to distribution. Even greater efficiency is realized when the file-based workflow, guided by workflow automation, uses conditional logic to ensure that downstream operations are determined by the results of upstream operations and/or by the metadata associated with a piece of content.
Automating the File-Based Workflow
To address problems common in file-based workflows, solutions such as Snell’s Momentum Workflow Manager extend the reach of workflow automation beyond master control and into the realm of production. This Web-based solution for media asset management (MAM), workflow automation, and project planning provides a single platform through which providers can effectively manage and scale all elements that contribute to the production workflow.
In handling media assets and metadata, human resources, and technical resources including suites, devices, and applications, the workflow automation solution makes it easier and less-costly for content providers to get the most value out of their media assets. It does so not only by eliminating processing inefficiencies and bottlenecks, but also by managing intertwined systems and processes more intelligently. For example, in managing a group of devices (such as transcoders), the solution can employ load-balancing or a similar technique to allocate tasks to the appropriate devices and, in turn, optimise resource use.
The workflow automation system manages these elements and their interoperation while presenting the operator with an array of workflow functions (or references) that can be called upon and leveraged as and when needed throughout the overall workflow. Through this approach, functions such as QC, loudness monitoring, and transcoding can be smoothly integrated into any part of the workflow, which in turn supports timely and efficient project editing, consolidation, quality control, and transcoding so that finished outputs can be delivered on time and in accordance with the requisite profile.
With simple control over workflow processes, administrators can be more effective and agile in allocating available resources and in orchestrating end-to-end processes. As the media company’s operations change or grow, this model also simplifies refinement or extension of the workflow. Users can create and manage file-based workflows themselves, rather than pay for upgrades over time. With this flexibility, media companies can not only optimise their operations, but also reduce their cost of ownership. For this reason, workflow automation can be a powerful enabler of the transition to a file-based workflow.
Automated Workflows Illustrated
The sampling of potential workflow issues identified earlier demonstrates pitfalls that may occur across multiple applications. The examples that follow illustrate how workflow automation resolves such issues and streamlines multiplatform content creation and delivery.
Quality Control and Loudness Correction
Workflow automation can manage various resources and present them as an available function within the file-based workflow, and file-based quality control and loudness correction are one such function (Diagram 1). Content sent for QC may be material recently ingested onto video servers under the control of the workflow automation system or content from a third-party system that requires review. In either case, the material passes through automated evaluation according to the appropriate parameters indicated by the file type or by its metadata. If content fails this test, it is routed for manual review.
When the workflow requires manual tasks such as QC or editing, the automation interface allows them to be assigned to an individual or to a specific group of operators. The system then can present users with clear “to do” lists and track not only who carries out an operation, but also when and how long it took to complete that operation. In this case, the workflow automation system builds a job list for human QC and prompts the user to trigger the next step with either an “OK” or “fail” result.
An “OK” result either for automated QC or the subsequent manual QC sends content on for loudness correction. Failure of both automated and manual review sends content for re-ingest, after which it re-enters the QC process at the beginning. If content fails either the initial QC or the loudness evaluation, an email immediately notified administrators either of a failure or any corrections made to content. The output of this process is sent on to the next step of the workflow, which might be archiving, transcoding for multiplatform distribution, or playout via broadcast services.
Repackaging Content for VoD
In workflows designed to prepare content for VoD services [Diagram 2], the workflow automation system can automatically restore content from archives and concurrently perform a variety of tasks — including branding, captioning, ad insertion, transcoding, colour correction, Nielsen C3 — according to the target platforms for that content. Information about the type and format of content, as well as the specifications of the target platform, enable the workflow automation system to determine and trigger the correct processing tasks prior to output. Automation of this single-input, many-output workflow yields the dramatic efficiency gains promised by file-based operations.As it guides workflows and workflow processes, Snell’s Momentum system captures operational performance data that can be leveraged for more comprehensive business analysis, more accurate capacity planning, and greater optimisation of resources.These measurable results can tell a media company if it has the resources and capacity to grow, and the workflow automation allows the business to adapt its workflows accordingly.
To meet the many new demands of offering TV Everywhere, media companies must have the flexibility to scale their operations their businesses. Effective and efficient workflow management is a critical means by which such companies can achieve this flexibility in orchestrating, managing, and controlling sophisticated content production processes required for multiplatform content delivery with measurable success