A lot of virtual ink has been spilled in recent years promoting the idea that using public, cloud-based tools to replace or augment data centers can save companies considerable amounts of time and money. The case for these benefits is by now well established. What is less often pointed out, however, are the many ways in which the cloud can help you increase revenue by boosting productivity, lowering the barriers to entry for new business opportunities, reducing risk, and freeing up resources for more lucrative pursuits. The increase in overall content monetization from switching to the cloud is significant. We’re not talking incremental improvements; we’re talking several orders of magnitude bigger.

We recently spent some time comparing our costs for video encoding and post-production services to those of some of our more prominent server-based competitors – companies who require you to install dedicated hardware and software-based systems.

Our model is based entirely on publically available rate charts and hardware performance benchmarks. We determine how much content different size business could process in a given period of time with a single encoding box and reasonable time requirements, and scaled up the costs based on encoding volumes.

Keep in mind, however, that the cost of building and maintaining a data center includes much more than just the continued capital investment in software and hardware. There are significant operational expenditures as well. Such setups also require an extensive IT support staff and facilities investments to build, host, and maintain the infrastructure. The value of this infrastructure depreciates rapidly. Hardware and software becomes obsolete, requiring expensive upgrades. Companies have to build a system capable of meeting their peak requirements – even if that means that the system sits idle most of the time.

Aren’t convinced? Let’s take a look at the numbers.

We started with what we took to be the typical processing requirements of a very large content producer: encoding approximately 1,500 video files a month, with an average length of 22 minutes each, into a range of mobile, broadcast, and broadband formats. We also assumed that the output files would include a mix of clips and full length files in both HD and SD.

Over a five year period, we predicted that the cumulative video processing costs for a typical in-house data center would exceed $25 million. Processing the same amount of content using Panvidea would cost that producer slightly more than $8 million. That’s nearly a 70% decrease in total costs.

And the numbers are similar for smaller implementations. We also modeled a “medium” size company (750 files per month) and a “small” company (100 files per month, clips only). The five year Panvidea costs for these scenarios were 65% and 55% less respectively.

The chart below tells the story in more detail.

For anyone familiar with the economics of the cloud, these kinds of numbers aren’t all that surprising. What may be surprising to some people, however, is the scale of the potential boost in productivity and revenue.

To estimate the productivity increase, we switched the terms of the equations. Rather than trying to calculate how much money a company could save by switching to Panvidea, we decided to calculate how much more content they could process with Panvidea if they spent the same amount of money they would have spent on an old fashioned, server-based system. The results were jaw dropping.

Assuming the same large processing requirements cited above, a company could increase their media processing output from 1.8 million content hours to over 7 million content hours. This represents a productivity boost of almost 300%. The increase for a medium sized company was just slightly less at about 280%.

The biggest surprise, however, came when we looked at the small company scenario. In that case, the potential productivity boost for switching to Panvidea was over 980%!

We chose to represent this increased productivity in terms of increased output based on the assumption that the demand for content these days is great enough that most companies are being held back by high opportunity costs rather than lack of demand. But even if that isn’t the case, the Panvidea approach gives media companies many reasons to rejoice because they can channel those freed up resources into the business of generating demand for their content without the fear and risk associated with the crushing overhead of maintaining a data center.

One might say that building even a small data center is an expensive proposition and it probably wouldn’t make sense for a small content company to make this kind of an investment. But the fact is that many companies do just this, in the hopes that the investment will pay off over time as their company grows. Even if they decide not to build their own data center, they are probably paying a hosting company which has these costs built in.

But here’s the catch. It doesn’t pay off. And it will never pay off, because costs in the old model scale incrementally with capacity. But not with Panvidea.

When you manage your own data center, or pay a hosting company to do it for you, it is extremely difficult to achieve any economies of scale or profit from an increasing number of licensing and distribution deals. Companies are literally forced to walk away from potentially lucrative content deals when the costs of fulfillment threaten to exceed the potential revenue or when the delays caused by overloaded operational queues result in missed opportunities.

Panvidea lets content companies get out of the IT business. By freeing up staff and resources, customers can focus on the core creative and business activities that contribute to their unique competitive advantage. On-demand solutions also enable much shorter deployment times – potentially minutes as opposed to a phased implementation that could take months.  Upgrades follow the same assumptions.

In summary, content producers who choose to build server-based infrastructures are faced with:

• Spiraling ownership costs
• Resources wasting time juggling codecs, wrangling metadata, maintaining infrastructure
• Inability to grow or to profit from economies of scale
• Inability to fully monetize new or long tail content
• Persistent threat of obsolescence and lack of future-proofing
• No means to keep pace with online and mobile innovation
• Deals left on the table and profits forfeited

Cloud-based encoding and video processing services allow companies to:

• Significantly reduce up-front and ongoing costs
• Gain increased transparency and predictability of costs over time
• Shift software expenditures from a capex to an opex model
• Take advantage of the economies of scale enabled by multi-tenancy
• Pay only for the capacity that they use
• Spend 50% – 70% less than comparable on-premise solutions
• Increase productivity (and potential revenue) by as much as 300% on average, but potentially much, much more