By Narayanan Rajan, VP Global Channel Partner Sales, MediaKind
In 2018 Deloitte published a long view study titled “The future of the TV and video landscape by 2030”, where it posited four potential scenarios for an end state to a video marketplace that was very much in a state of flux. They included:
In the intervening three years, none of the uncertainty surrounding these scenarios has significantly changed. The likelihood the industry landscape will end up in some hybrid state somewhere between these four scenarios has made predicting the future even more complicated, creating immense difficulties for business leaders trying to make investment bets in our industry.
Key questions like “What does my audience want to consume?”, “How do they want to consume it?” and “How do I monetize the consumption?” have required long view decisions in the content and technology chain that can often be expensive to unwind if the winds of change shift too rapidly. Adding to these questions, the granularization of audience demands for content consumption creates a downright turbulent perspective. While there is no single inoculation for these fundamental issues, there are two potential avenues to mitigate some of the business uncertainties for the traditional video segments insofar as they still purely exist.
The first is to build more capability at the edge of the traditional primary distribution chain to incorporate new services and functionalities closer to a target audience group. Edge computing has been a buzzword for applications demanding hyper-low latency, like IoT, gaming, and AR, to name a few, but is also relevant in any context where the audience needs may be uncertain over the business term of the technology investment.
The second is to have a fundamentally modularized approach to the software architecture that supports the primary distribution chain through microservices or containerization and is deployable through Kubernetes orchestration. That allows the business to migrate or add functionality to the edge, spin it up or down, as the needs of the business dictate. Examples might include targeted advertising services, manifest manipulation, transcoding, prepositioning, and splicing local alternate content. At the content origination point, it may be employing machine learning for content up-conversion.
In his MediaKind blog “Personalizing Media: Trends and Opportunities in TV Advertising,” Christophe Kind discusses exactly the kind of challenges facing the industry around targeted advertising that could benefit from the ability to deliver more functionality to the edge. This particular use case requires combining both manifest manipulation and splicing, especially in an increasingly ABR world.
While the big OTT players are starting to incorporate content lineup available with 4K and HDR, it is fair to say that content availability in the broadcast domain has been largely constrained to Tier 1 sports.
However, content owners are looking at the potential ability to up-convert from HD to UHD for their archival content to increase the value of the audience experience. Tony Jones provides an excellent overview of this technology in his MediaKind white paper “Increasing the value of existing content: Machine learning for HD to UHD up-conversion.” The ability to easily manage the transition from HD to UHD services across the distribution chain all the way to the edge with a containerized approach could go a long way to mitigating some of the uncertainty around the timing of infrastructure investments, while still giving the audience the desired experience.
For national and regional broadcasters and providers, this level of flexibility is even more critical. Their value proposition in the face of established and global content distribution behemoths is the ability to react quickly and effectively through their understanding of local audience needs and appetites. Consideration of technology investments at the edge of the content distribution chain must incorporate the certainty of an uncertain landscape so that investment dollars afford the maximum adaptability in a rapidly evolving future. MediaKind’s approach to our technology evolution has been particularly sensitive to address these uncertainties.
After all, as viewers adapt the way they consume content, broadcasters across the value chain need to change with them. While we may be no clearer about the TV and video landscape by 2030, we are starting to see a move towards a form of grand unification. There is a commonality that everyone across the media value chain is trying to achieve; irrespective of the side of the market you are starting from or the delivery mechanism, there are opportunities to succeed.
Whether it’s providing technologies or solutions to increase reach, engagement, improve monetization, provide agility, move to the cloud – or simply to reduce costs – MediaKind has a laser focus on providing certainty to our customers and partners. We ensure they have the best tools they need to meet the challenges they face today and throughout the decade ahead.