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M&E Journal: Smart Content Will Simplify the Digital Supply Chain

By Uri Kogan, Vice President, Product Marketing, Nuxeo

Everyone in the M&E content ecosystem knows the Holy Grail of content value generation is in serving the right content in the right format through the right channels to the right people.

On the other hand, they also know that moving all of it at speed through the digital supply chain is getting harder and growing even more critical to the financial success of media enterprises.

The early and incumbent existing media systems managing various loose or disconnected production content, WIP, marketing, archive, and distribution have been built, rebuilt, customized, upgraded and re-customized — and everyone knows they aren’t keeping pace.

The old technology simply wasn’t designed with today’s challenges in mind. As these systems consume ever larger shares of technology and operations budgets, it’s becoming increasingly difficult to maintain them while simultaneously addressing ongoing and imminent digital disruption.

As if solving the existing system conundrum isn’t trouble enough, the business goals and revenue targets aren’t shrinking and the business will do what it must to achieve them. To address these issues and realize the vision of transformation, organizations must get off this Sisyphean path and change their approach to content: they need smart content, in smart systems.

In this piece, I’ll describe what it means for content to know itself. I’ll outline principles to consider in building a smart system for content to operate in, including cloud, AI, and smart storage. I’ll identify considerations for how to transition from the current state of outdated infrastructure, to a smart system that leverages a system of systems approach, as well as how this approach can lead to better monetization and growth.

Content that knows itself

There’s been a customer-experience revolution in business over the last five years focused on developing a fuller 360-degree view of customers to provide them more relevant content and offers. Just as that perspective massively increases the value of each customer, with a 360-degree view of your content — context provided by rich metadata that enables people to search for, effectively use, and route it — you can massively increase the value of your content.

Take a TV show file. How do you find it? At a minimum, it’s in a folder structure that you can dig through, from show to season to episode. But what happens when it’s pulled into another system or put in the wrong folder, and someone searches for it without knowing that 09272016s1e1DenHD.mov means season one, episode one, with Danish subtitles, in HD, as first aired on Sept. 27, 2016? Naming conventions aren’t very helpful to those who don’t know the convention! So, people resort to opening many files, hunting for the right one. Not very smart!

Now, if you attach a transcript and your system is capable of full-text indexing, you’ll know exactly what the video is about and what’s being said. Episode numbers associated with the video, information on cast and crew, and details such as episode length and chapter timestamps will elevate its discovery, usefulness and ability to be referenced.

Things get more intricate when you add in usage rights. Smart content comes with information that indicates where and when it can be shown, on which channels, details on product placement, and more. Content that knows itself ensures its handlers know how it should and can be used, reducing the risk of misuse and the huge penalties that follow.

With smart content, there’s far less need to resort to tribal knowledge. It’s fine to ask Gary in post and Sally in sales where something is — until they change jobs or leave. And with smart content, there’s far less effort required to manage the verification of available rights.

Leveraging smart content

Having smart content is just the tip of the iceberg. In order to make the most of it, having a system that can interpret the metadata while keeping up with complexity and scale is critical. The level of richness associated with content can get unwieldy very quickly, and being able to distinguish the details of the files and rights management is the only way to effectively leverage it.

For example, a smart video file — including metadata describing not only the actors, directors, and products in it, but also rich details like what countries the directors or actors made the most money in previously — enables a smart system to help you make informed business decisions.

Additionally, a smart system enables you to quickly remake, reuse, and re-purpose content, a process that, when done manually, can be extremely time-consuming. This comes in handy when certain geographies have restrictions on nudity and/or violence, and you need to release multiple versions of the video. With a smart system, you can pinpoint a scene that you want to edit or swap out with other existing content, expediting and simplifying the content supply chain.

The content supply chain often requires collaboration across regions and teams, and a smart system will facilitate this. In other words, if multiple users are working with a video file to localize it for specific regions, a smart system will provide you with a unified platform that allows you to share feedback within the same system, maintaining version control, and grant access based on where the content is in the supply chain, accelerating the process without compromising security.

Considerations for building a smart system

Working with content across departments and teams requires a system that is flexible, enabling you to access it instantly from anywhere in the world. And given the huge amounts of information being worked on, a smart system must be cloud-native, connected to content delivery networks (CDNs) that accelerate file distribution, and edge caching to limit bandwidth use and expense for files being reused on the same network.

Take a movie studio. They release movies in multiple languages, which includes revising and replacing subtitles and dubbing. Throughout the process, the movie must be passed between studios and the regions that are localizing it. And when they factor in the cost of storage, which includes back-catalogs and thousands of hours of footage in both SD and HD, the undertaking quickly gets out of hand.

By leveraging the cloud, teams can seamlessly collaborate, and they can pick and choose which files need to be stored in the cloud and which ones can be archived in different tiers of storage — a decision that could save them a lot of money. A smart system lets them use metadata, like release dates, download frequency, or other criteria to automatically select storage tiers to keep the most important content closest to users and the least critical in cold storage.

Additionally, a smart system must enable global find-ability without needing to centralize all the content at once. Existing silos of content have workflows and business applications built around them that are very painful to disrupt. Instead, a smart system should index content anywhere in the organization, consume multiple metadata models on the same content, and make it all easy to find and work with, whether through a user interface or other applications through modern APIs. This way, third-party system content can be a first-class citizen.

Furthermore, a smart system leverages artificial intelligence (AI) to assist people throughout the supply chain. AI can speed up the content supply chain by intelligently tagging footage along the way–an otherwise time-consuming task that must be done manually; and it can help with the creative process (e.g., when editing footage, the system can route a specific editing task to a colleague or partner that has expertise working on a similar project and has the availability to tackle it).

AI can help with risk and managing contractual rights, by identifying what is and isn’t allowed to be shown on a certain frame or scene based on contractual obligations, as well as helping identify consumer consumption characteristics scene-by-scene. For sales teams, AI can recommend additional content based on a customer’s purchase history. And AI can even be used to intelligently suggest where to store content based on what’s needed, where it’s needed, and when it’s needed.

Creating better monetization and growth

Smart content and systems enable you to use your content in an efficient way, to its fullest extent. This saves you time and money that would otherwise go into re-creating content, and it facilitates the content supply chain by making it easy to collaborate globally with your partners, while leveraging AI to automate time-consuming processes that would otherwise require manual labor.

In such an event-driven cloud workflow, logic can then be defined to process the subsequent event messages — e.g. proxy “object created” — to initiate follow-on actions. For example, a follow-on action might include a lookup in a business system to determine what formats the media is needed in to complete a delivery, along with the time the media is required, and hence the priority. The service could then insert a job in a transcoder queue that would then trigger another event when the transcode was complete, which in turn could trigger additional actions defined by logic operating on those event notifications.

And so on along a linear or branching, logic-defined and event-driven, media process chain. None of these actions require any knowledge of the physical infrastructure the logic executes on in the cloud, or awareness of prior events. Of course, chain-of-custody and overall status can still be determined by logging and viewing these events.

This approach affords several advantages. The mapping of jobs to available hardware could consider variable costs of compute in a way that is completely abstracted from the logic that decides what transcode is required and by when. This logic could be implemented by a transcoding service that provides this level of abstraction as a service, or it could utilize transcode software provisioned directly on top of cloud compute.

In the latter case, it could manage the capacity of the transcode farm based on availability of spot instances at given price points, and vary the spot instance price point up to and including the on-demand price, based on the backlog of high priority transcodes.

All previous phases of file-based media workflows — from early “file islands”, to tightly- coupled bespoke systems, and on through the loosely-coupled on-premises solutions of more recent years — have all suffered from a common problem. No matter how elegantly “abstracted” the solution might be architecturally, the reality was that physically there was always a lot of infrastructure (hardware and software) that needed to be built, tested, deployed and supported.

This took time and money, and frequently led to systems that did not lend themselves to expansion or major modification without another round of substantial investment of time and money.

Often it was simpler to scrap the previous build and just begin again as technology aged and changed, or as what was originally built no longer matched the business needs in terms of performance, cost, efficiency, reliability or functionality.

This long-established pattern of initiating large IT-driven media workflow projects only to see them become obsolete before they have even paid for themselves (or in some cases even worked as planned), has led many to have a justifiable skepticism of yet another new approach.

However, the marriage of event-driven workflows with the “Everything as a Service” offerings of the cloud perhaps finally offers a model for success — even for media, that most demanding of industries.

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