Accedo – The Cost of Hidden Operational Inefficiencies

Fredrik Andersson, SVP Business Development, Accedo

Most streaming services were built for growth rather than efficiency, hardwired to acquire subscribers as fast as possible. However, as the industry has matured and macroeconomic challenges have added pressure, those same video services have shifted towards running leaner, more efficient operations better able to sustain profitability over time.

While most OTT businesses have inevitably scrutinized their customer acquisition costs, churn rates and monetization strategies, that alone is not enough. Operational inefficiencies have snuck in over time through delayed innovation, technical debt, overprovisioned infrastructure that has somehow become the permanent baseline, and engineering effort spent on maintenance instead of new features and improvements. These inefficiencies have compounded over time, quietly absorbing resources that could otherwise be directed towards innovating, improving user experience and creating new revenue opportunities. The real challenge comes because these operational efficiencies are hard to see, and even harder to address. Yet without remediation, they are steadily inflating costs and ultimately degrading the viewer experience.

When Inefficiencies Are Hard To Pin Down

 Some operational inefficiencies can be difficult to identify, particularly when they creep in slowly over time, and all too often, by the time they’re realized, they’ve already had a big impact. Perhaps an engineering team is spending longer than usual resolving incidents, or maybe new releases are pushed back by several months because it seems sensible to do so at the time. None of these decisions seems particularly significant by themselves, but when considered together, a new picture begins to form.

Engineering capacity provides one of the clearest examples. It’s not unusual for a substantial proportion of effort to be devoted to maintaining existing services, resolving operational issues and managing technical debt rather than innovating and building new capabilities. In this scenario, engineering teams are running at full capacity, but product development has slowed down considerably. From the outside, investment appears unchanged but when you look a little deeper it becomes clear that far less of it is creating new value for viewers.

Technical debt compounds this effect. Every workaround introduced to meet a deadline or support a new device becomes another dependency that must eventually be maintained. As platforms expand across more devices, territories, business models and emerging ad tech, those dependencies become increasingly interconnected. Changes that once affected a single component start requiring coordination across multiple pipelines, increasing both complexity and delivery times.

While it may have seemed sensible in the past to deliberately design streaming services with overly generous capacity to guarantee resilience during periods of rapid subscriber growth, the same infrastructure has often remained in place long after usage patterns have changed. Individually, each of these issues doesn’t seem hugely serious but their cumulative effect is that operational costs increase while the service’s ability to respond quickly gradually declines.

Small Delays Become Larger Business Problems

 One of the less obvious consequences of hidden operational inefficiency is that it rarely remains confined to only one function. With engineering effort being swallowed up by maintenance and fixing underlying problems, features that improve personalization, discovery, UI and UX are often postponed. Product teams are therefore much more limited in what they can realistically deliver. Similarly, opportunities to trial new business models are delayed simply because there is insufficient engineering capacity to support them. These decisions have commercial consequences even when they are difficult to quantify precisely.

The viewer experience can also begin to change in subtle ways, in that improvements arrive less frequently, bugs remain unresolved for longer, and playback stops being optimized. The impact also extends beyond technology to people. As complexity and operational demands increase, retaining specialist engineering knowledge becomes more difficult. And, when valuable expertise leaves, making future improvements becomes even more time consuming and expensive.

Perhaps the greatest cost is lost opportunity. While one service is spending its engineering effort on maintaining increasingly complex systems, another is investing that same effort in developing and launching new capabilities, improving customer experience or expanding into new markets. It’s easy to see which one will fare better in the long run.

 

Addressing Inefficiencies Before They Become Embedded

 Although managing infrastructure, maintaining integrations and responding to routine operational issues are all essential functions, they’re rarely the capabilities that attract subscribers or increase engagement and retention. Video services need to instead create enough operational headroom that engineering teams can spend less time on maintenance and more time on work that supports long term growth. That begins with understanding where engineering effort is actually being spent. Services often measure delivery velocity and infrastructure costs independently, but examining how operational maintenance affects feature development often reveals a more complete picture.

Utilizing AI and automation, and working with managed service partners can enable internal teams to focus more on other areas such as improving quality of experience, and developing product capability. Also important to remember is that when tackling the hidden operational inefficiencies discussed here, while the primary goal is to reduce expenditure, the secondary goal is to increase flexibility. Streaming remains a fast-moving industry with constantly shifting sands, and it is the services that can adapt the quickest that are the ones best placed to respond to those shifts.