News & Views

From the engine room to the cockpit

How the digital content supply chain empowers talent in the media industry

Today’s digital content supply chain is driven by a continuous data loop from strategy and planning to execution and back. In the middle, there is human talent, freed from repetitive and error-prone tasks, liberated from physical barriers to collaborate tightly across functions, departments and territories, empowered to manage by exception and assisted by augmented intelligence to make sense of augmented complexity.

See the content planners and schedulers. With great experience and deep knowledge, they craft plans and schedules in a way that attracts and retains viewers and gets the most value out of the content. With apparent ease, they negotiate the obstacles of complex rights and regulations, quotas, and editorial guidelines to stay on target and within the company strategy and mission. Together with the people involved in media asset management, they juggle multiple formats and versions of video, audio and subtitle files. They insert trailers and secondary events in all the right places in airtight playlists. And together with Airtime Sales, they ensure advertisers get the best bang for their money. 

Dealing with increasing complexity

The amounts of content that go through a company’s content supply chain are massive.

One MEDIAGENIX client schedules 30,000 trailers a year; another client localizes 16,000 hours of content a year.

Whether media companies are dealing high-value content in primetime or the umpteenth repeat for a small audience, it can take them the same number of manipulations. 

Blockbusters, vintage series and movies, game shows and soaps, old content or new, there is a different approach for every piece of content. Management has defined the strategy months in advance, and the information is passed down the line from the strategic planners to the long-term planners, and from the long-term planners to the short-term schedulers and VOD curators. Data is re-entered over and over again in the process.

Rights have to be managed with great precision. The purchasing department and content coordinators register a wide range of information about deals, agreements and contracts, and already capture granular data about underlying rights, such as copyrights. As the content progresses through the supply chain the data is enriched. Data from third parties often needs to be entered into the system manually.

In the meantime, the Finance people manage multicurrency costs, amortizations and payment schedules. They calculate revenues and the revenue shares for rights holders and suppliers and provide accurate reports for management reviews, stock trend analysis, and end-of-year closures. They need to know the value of the schedules and the inventory at all times.

At the end of the content’s life cycle, sales officers need to know which rights are available for selling where based on the latest data. They need to gather insights into the content and keep track of all license agreements and holdbacks with potential buyers. And after the sale, the schedulers need to know immediately which rights are no longer available for scheduling. 

The work is massive, and the need for data sharing and communication humongous. We are talking hundreds of emails and Excels a month. And that is just internal communication.

For example, one MEDIAGENIX client sends a 100,000-line Excel to the compliance authority every four months to show that quotas have been met. Another client processes almost ten million consumption records a month to calculate royalties. 

Rethinking the processes

Now that the increasing cost of content and the dispersed viewer market push media companies to deliver content on multiple platforms — and, as the case may be, to various territories — complexity is skyrocketing.

Media companies need to rethink their processes. The lean supply chain model in the manufacturing industry teaches us to take an end-to-end process view and see the organization as one system. That requires an automation approach, a specific data framework, and AI analysis of key data.

Actionable intelligence needs to flow along the two axes of the content supply chain: from upstream, where people are acquiring or producing content to downstream, where you can see how successful the content actually was; and from the strategic plane, where you know the strategic objectives to the operational and execution planes where you can see how everything is panning out. 

Simplified collaborative workflows

When information flows freely, all people across de departments and levels of the organization have access to the real-time data they need to optimize their contribution to the value chain. They can work in perfect sync as communication across departments and collaboration across functions and territories is greatly facilitated. 

For planning and scheduling, this can mean, for instance, that managers have ready access to visualizations of the content and platform strategy over long periods. They can define, view, inspect and manipulate the strategic long-term schedule directly in the central system with apps that do not require any knowledge of intricate scheduling functionality. That way, their work can immediately be refined by the long-term planners, then by the short-term schedulers and eventually — in the case of linear schedules — by Continuity: no rework, no re-entry of data, no mistakes. 

Plug-in web apps can also greatly facilitate collaborative metadata enrichment across departments and partners and leverage automated metadata ingestion from various internet platforms. They can give quick and easy views on the schedules in safe read-only mode or conjure up focused views on genres, departments, target groups and cost grades, eliminating hours a week spent on manually extracting the data. 

Automation and orchestration

Data flows that are truly bidirectional close the loop between the organization’s strategic, operational, and execution levels and open the door to data-driven automation and orchestration of unified content, rights and planning workflows across linear channels and VOD platforms. 

In daily life, people will start the day with a list of your current and upcoming tasks and the information they need to complete them. System administrators have a dashboard to monitor the progress of the processes and take action as soon as the workflow stops because a task has failed.

Based on best practices, automation and orchestration substantially improve workflows in VOD distribution, subtitling, contract verification or whichever domain of the content supply chain. A workflow orchestrator integrated into the scheduling system can, for instance, also manage a touchless flow to get Soundmouse to track music usage in on productions and promotional material and report it to the collecting societies with detailed scheduling data. For the average broadcaster, that already eliminates hours of drudgery a year.

People in Finance get access to tools that easily process millions of consumption records a month with hundreds of revenue split models to get the revenue shares right. Sales officers can benefit from automatically updated information on availabilities to sell content online without the hassle of constantly updating the offers. And all departments can make diverse calculations and draw up reports from their own screens, assisted by best-of-breed BI tools.

Augmented intelligence

It is clear that data-driven automation frees people from repetitive work. They discover that new, best-practice-based processes really improve their daily work and give them more time and possibilities to create value.

But to tackle today’s augmented complexity, people also need augmented intelligence.

Starting from existing schedules, a human-in-the-loop-type of AI algorithm can automatically build linear schedules in seconds built on parameters the schedulers have set, such as cost, the rights expiration date, or predicted ratings. This can be used for off-peak hours or to quickly create a kind of skeleton schedule for the primetime hours. That way, schedulers can focus on the important decisions they have to make.

Machine learning algorithms can forecast ratings for the different target groups based on content and context metadata, such as historical and competitor schedules, content metadata, or the weather. These predicted ratings allow schedulers to improve their schedules and optimize revenues from ad sales.

Augmented intelligence helps determine how scheduled content is performing and how content in stock might perform. That greatly helps with budget simulations. It also helps to decide what content should be acquired to complement existing content. Also, if you know how well the content you want to acquire or produce will perform, you know how much money you want to invest in that content.

All this can converge in a web-based BI tool that helps managers optimize the content life cycle across channels and platforms based on real-time, actionable data on content needs, content performance, and predicted performance. But facilitation and enablement should apply to all levels of the organization and all functions along the content supply chain. This is not only about drastically reducing the number of mails and Excels going back and forth. Everybody should feel they have a cockpit view of the organization, the value chain, and their important role in that exciting whole.

The resulting empowerment of the entire organization will create the agility to secure and extend the competitive market position. Without this empowerment, the operational costs of managing multiple platforms and business models will quickly spiral out of control.

Visiting IBC in Amsterdam? Book a meeting at MEDIAGENIX booth 1.C25 and make it pay for everyone in your company.

In the meantime, discover our new WHATS’ON HIVE collaborative web apps:

Photo by Dragoș Grigore on Unsplash

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