Few industries are as fast paced and highly pressurised as the media industry. What was already a competitive field has become even more so, as the demand for content has increased in-line with the explosion of OTT services. To manage this high volume of throughput, content supply chains have become more complex, with multiple teams all contributing towards content preparation.
There is a lack of consistency and uniformity across the industry, and this results in the need to manage a wide variety of formats and metadata standards. This only serves to add to the already complex nature of the modern content supply chain. Naturally, when producing and preparing media assets in such a competitive environment, it is critical that the content’s value is maximised.
Managing Content at Scale
To keep up with demand, a typical media organisation will see large numbers of assets continually moving through its content supply chain to facilitate consumer demand. Content is being produced and managed at a scale never seen before. If content supply chains are not optimised, it is harder to monetise content and maximise its value. If media costs more to produce than it needs to, profit margins are quickly going to be affected and this will significantly impact the ability of a business to operate, particularly given the current global circumstances. As the volume of content being produced grows, this issue becomes magnified and bottlenecks can occur.
Media organisations are adapting their workflows to better manage content at scale and are doing this while maintaining their focus on quality. To process all this content, companies need to ensure workflows are streamlined, automated where it makes sense, and operating as efficiently as they can be. This applies to all stages of the media workflow and is particularly important with those stages that involve a lot of manual, labour intensive tasks, such as essential editing tasks around QC and compliance.
Optimisation Needs Time-based Metadata
Managing content at scale is impossible without leveraging time-based metadata. Scrubbing through literally thousands of hours of content to find errors or complete validation checks is impractical. Take advert markers for example: without time-based metadata, media operators would have the painstaking process of having to manually locate black frames for inserting advert markers. This may need to be done not just once, but multiple times and in different ways for versions of the same content, as media operators prepare it for distribution in regions that have differing ad requirements.
It’s easy to see why this process is such a drain on resources. But if time-based metadata is used to identify exactly where the black frames are, rather than operators spending time manually searching through content, they are guided straight to the correct position. Operators can then set a start and an end point for the content, find the optimum position for ad-breaks and move on to the next task. This is where time-based metadata can make a huge difference to the efficiency of a content supply chain.
The same applies when it comes to the QC and localisation process. Let’s say an operator has to remove frames showing restricted content such as firearms. Without time-based metadata, this could involve trawling through masses of content to find all problematic frames. In addition, if operators have to manually search each frame, there is always the possibility of overlooking the inclusion of a firearm, where it is not immediately obvious. An error of this nature would understandably have quite significant repercussions.
With time-based metadata, operators are guided to the frames where essential actions are required. This means they can quickly manage, edit, and remove errors or restricted content. Operators are empowered to work efficiently and focus their time and energy where it is needed most. By letting the metadata guide them, an operator’s workflow becomes more targeted. Individual actions are made more efficient and then multiplied across thousands of hours of content processing, so companies can optimise the monetisation of both archive content and acquisitions.
Simplifying essential editing
Media operators are under enormous pressure to perform the necessary actions around QC, compliance and localisation, quickly and efficiently. Failure to do so can create a backlog in the system which can be catastrophic for media businesses. Many of the tasks involved in essential edits are repetitive and time consuming. Let’s say a media operator is responsible for locating and removing errors such as bars, black frames, or slates and tones, from 100 hours of content for a particular show. What if an operator can access the content straight in the browser and easily locate, edit, and fix any errors? This is a much more efficient way of working than having to open and use more complex video editing solutions not designed specifically for essential edits.
The localisation element of the process can be optimised in the same way. Media operators need to be able to remove frames that show content which is prohibited in certain regions - such as violence, explicit content, or drugs. Being able to do this quickly and easily in a browser from anywhere, will speed up the supply chain and save costs.
Automation also has the power to speed up the editing process, and at the same time allows operators to apply their skills in other areas. Automating repetitive and onerous editing tasks wherever possible, will save operators huge amounts of time and help to optimise an asset’s value. Automation is not only a critical requirement when improving efficiency, it also plays an important role in minimising human error.
In this era of expansive content consumption, the value of media assets must be maximised. The complexity of content supply chain workflows has a huge impact on how organisations can effectively monetise a large volume of media. By radically simplifying the editing process that accompanies QC and compliance, actions can be performed quickly and efficiently.
Modern cloud-based, content processing allows media companies to optimise asset preparation and streamline workflows. This provides operators with much faster and more efficient methods for segmenting content and carrying out essential edits. By using both automation and time-based metadata effectively, media companies can monetise and truly maximise the value of their media assets.