Executive summary: why is FinOps a board level priority in the Media industry?
As audience expectations rise and every millisecond of startup time influences engagement, cloud performance and cost efficiency have become inseparable.
With media companies shifting workloads from traditional data centres to public cloud and hybrid cloud environments, understanding cloud economics is now mission-critical.
Our recent cloud financial management assessment for a global, enterprise-size media client - with an average annual cloud spend of about USD 10 million - demonstrated how disciplined financial accountability can transform cloud operations into a genuine competitive advantage.
By analysing 12–24 months of billing and usage data, mapping consumption to business functions, and assessing tagging maturity across cloud environments, we identified both immediate and long-term optimisation opportunities.
Key takeaways of the assessment
- Thanks to our service, the client saved up to 20% of their yearly cloud spend.
- In the first year alone, they could achieve savings of 10–20%.
- These funds can either be kept as savings or reallocated, for example, to investments in data and AI.
In general, possible optimisations of such an audit could include:
- Removal of wasteful resources, saving 23.4% of overall AWS spend.
- Rightsizing of resources, reducing compute costs on AWS by 33%.
- Upgrading resources, achieving 12.4% cost savings and improved efficiency.
- Scheduling of non-production workloads, cutting 63% of computing costs in non-production environments.
- Storage clean-up and usage optimisation, saving 64.5% in development/test environments and 41.3% in production.
- Commitment discounts, reducing overall AWS costs by 54%.
£1B+ in bookings for the UK’s largest independent broadcaster with a new ad management platform
From cost cutting to cost-to-value alignment
Cloud financial management in media is not about slashing budgets – it’s about aligning spend with business value. Every dollar should directly support quality of experience (QoE), service reliability, and roadmap velocity.
Advertising yield, subscriber growth, and live-stream concurrency all depend on QoE metrics such as startup time and rebuffer ratio. Through data-driven FinOps, our client achieved tangible savings without compromising performance, turning cloud efficiency into a strategic lever for growth.
Broader industry changes further highlight the need for effective cloud financial management. Vendor service retirements are forcing organisations to re-evaluate platform dependencies, while multi-region expansion strategies are increasing both cost complexity and governance demands.
Key takeaway:
FinOps ≠ “cost cutting.”
It’s cost-to-value alignment with guardrails that protect QoE, business agility, and roadmap velocity.
Learn more about Cloud Cost Optimisation:
What is a 'media workload' (and where the money goes)?
Every media experience – from streaming a live concert to watching a news clip – relies on a multi-stage pipeline that processes, protects, and delivers content seamlessly to audiences worldwide.
Typical workflow stages include:
- Ingest – live feeds, raw files, or user-generated content enter the system. Requires high bandwidth and elastic compute to handle spikes such as sports events or premieres.
- Transcoding & packaging – content is encoded into multiple formats and bitrates for optimal playback across devices. This compute-intensive stage is a major contributor to public cloud costs and benefits from autoscaling, intelligent job scheduling, and spot/preemptible instances.
- Storage & replication – assets are organised by access frequency (hot, warm, cold) and lifecycle policies. Without management, hot storage costs can balloon and unused replicas increase backup and egress fees.
- Digital Rights Management (DRM) – protects content and ensures licensing compliance. While its direct cost is smaller, DRM depends on encryption, key rotation, and high availability.
- Telemetry & Data/AI Pipelines – playback generates analytics that feed recommendation engines, ad targeting, and audience insights. These workloads scale with audience size and require rigorous financial accountability to control costs across the media cloud.
Mapping the cost drivers
Each of these stages carries distinct cost pressures and optimisation levers:
- Compute: Encoding, rendering, and packaging consume CPU/GPU and benefit from autoscaling and spot/preemptible instances.
- Storage: Tiering (hot/warm/cold/deep archive) and lifecycle policies control retention costs without limiting access.
- CDN & Egress: Optimising cache efficiency, multi-CDN contracts, and real-user-metric routing unlock major savings.
- Observability: Logs, metrics, and traces provide insight but can quietly add cost; retention policies and compression are essential.
- Data & AI: Analytics and recommendation workloads require clear cost attribution for ROI and governance.
Over-provisioned transcode nodes and under-tagged CDN traffic mask true unit economics. Correcting these inefficiencies could deliver a 10–20% reduction in cloud spend in the first year while establishing governance for sustainable cost control.
With these cost drivers mapped and controlled, the next step was to ensure that optimisations were not locked into a single vendor or region. This led to a broader focus on cloud-agnostic design.
Spot aware job schedulers for background tasks
Media encoding is an example of naturally parallel and fault-tolerant, ideal for spot or preemptible instances offering up to 90% savings.
Implemented operational strategies included:
- Checkpointed, segmented transcodes with automatic fallback to On-Demand.
- Mixed instance strategies for cost and risk management.
- Preemption budgets and SLA-aware max-time-to-complete policies.
These strategies maintain service reliability while drastically reducing transient compute costs.
Once compute workloads were stabilised and optimised, attention shifted to long-term storage and lifecycle management — another area where automation and tiering unlock significant efficiencies.
Archive tiering & lifecycle policies
After addressing compute and pipeline efficiencies, the next layer of optimisation lies in how content is stored and retained over time. Automated tiering ensures that storage costs align with content value and rights, without compromising accessibility or compliance.
- Hot, Warm, Cold, and Deep Archive tiers organised by popularity and age.
- Compliance safeguards including legal hold, immutability, and checksum/fixity validation.
- Predictive pre-fetching to prepare for seasonal or event-driven spikes in demand.
This approach lowers overall storage TCO while preserving editorial agility and ensuring full compliance with media-specific governance and retention policies.
The Media FinOps operating model
Together, these initiatives form the foundation of a mature Media FinOps operating model – one that focuses on managing “the cost of quality” rather than simply reducing spend.
Using a structured assessment methodology, organisations can continuously align financial accountability with technical performance:
- Comprehensive review: usage, tagging, and storage management.
- Quick wins: rightsizing, scheduling, and licensing optimisation.
- Targeted projects: network re-architecture and Kubernetes tuning.
- Continuous roadmap: forecasting, anomaly detection, and unit-cost visibility.
Results:
- Up to 20% annual cloud spend reduction on the overall budget.
- Stronger visibility and financial accountability across teams.
- Confidence that every cloud investment directly supports performance, growth, and innovation.
Executive takeaway:
Ultimately, media FinOps ensures that every dollar invested in cloud infrastructure delivers measurable audience and business value.
Driving revenue and shaping the future of Media with technology
Contact us to see how we can help you transform your media business.
FAQ
Can we save money without hurting quality?
Absolutely. Effective cloud cost management enables significant cost reduction without compromising Quality of Experience. The biggest early wins often come from idle storage, underutilised compute, and CDN inefficiencies within your cloud services.
Start by tuning cache strategies and introducing shielding to reduce redundant egress and replication. From there, pilot Spot or pre-emptible instances for workloads like parallel video encodes – using checkpointing and fallback to avoid service disruption.
How fast can we see ROI?
Most organisations begin to see measurable cloud cost reduction within one to two quarters after embedding visibility and accountability into their operational rhythm.
When you connect unit economics, automation, and QoE tracking, early pilots quickly produce results – freeing up your cloud budget for innovation, performance upgrades, or audience engagement initiatives.
