It is seems that there is a universal requirement these days that all new blog posts, articles and learned discussions on the topic of the media industry have to start by saying that the broadcast industry has changed beyond all recognition:
Well, I don’t think it has.
In the old days of just a handful of television channels and linear workflows, we received a tape, we checked it for quality, we standards converted it if necessary, and we played it to air. Today, we ingest content, run it through QC, transcode it and prepare it for delivery. Sounds pretty much the same to me.
So what has changed? Well, we just do a lot more of it. First, we need multiple transcodings because of all the different platforms we have to serve. Second, there are more producers creating more programs, and more archives releasing more historical content.
If you want a sensation of how much content there is in the world today, consider this: YouTube receives more than 100 hours of content uploads every minute.
Back to the conventional media business, which is trying to do what it always did, but with many times the throughput. How can it possibly cope?
As we all know, the answer lies in automation. Machines are good at repetitive tasks, and if we leave them to it then we can apply the human touch to things that really need it: Sophisticated judgements on quality issues. Pushing special projects through ahead of their natural priority. One-off workflows.
What we are talking about is process automation, of the sort that would be very familiar to engineers building, say, an automobile plant. Parts come in at one end, are assembled into the various versions of the car, checked for build quality, then loaded onto transporters at the other end.
In the media industry, the primary business requirement is that all these new markets and additional content are served in the most cost-effective way possible. After all, there is no point in doing any of it if you cannot make a profit. So there has to be a business level to the process automation. You have to know that the system is working to maximum efficiency, and that the content that comes off the end of the production line is fit for purpose, and right first time.
Which leads to the question of where you put this business intelligence. Some advocate embodying it all in a centralized asset management and workflow system, where all the detail is available in one place. Others argue that you are better to choose the devices and systems to do the work, let them each look after their own logic, and manage them as a system through watch folders and analytic reporting.
Both have their advantages. Centralizing the business logic eliminates the need for additional bespoke software, but it makes the asset management system extremely complex and very hard to replace. Dispersed logic makes changes and updates faster, but needs a lot of detailed understanding by key staff and can be hard to scale.
For me, the solution is a bit of both. Use the central asset management to issue high level commands, and receive top-level reports. Then build logic into each device to interpret those high level commands.
So the central instruction might be “transcode this piece of content for the iTunes Store”. The processor would interpret that with a list of actions including checking the format of the existing content and its quality status, transcoding and transwrapping, reformatting the captions and other access services, and filling the destination metadata schema. It would report back not only overall success, but the time and resources used, to help engineering managers determine if there are bottlenecks in the process.
This sort of system can be implemented today, using intelligent processing like the AmberFin iCR as the ingest/transcode/quality/delivery engine. Like the robots on the car production line it can be reconfigured at a moment’s notice to carry out a different task, and can be left to carry out its tasks day after day without the need for manual intervention, unless it is something that requires the human touch.
Media production and delivery can be industrialised without threatening creativity or quality. It puts the business management where it needs to be. And it ensures that enterprises can really benefit from efficiencies of scale through workflows that are tailored to precise business needs.
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