Unravelling the complexity: Understanding revenue recognition

In our previous article, “Driving growth and strategy: The importance of revenue recognition in media“, we discussed why accurately recognising revenue is crucial in today's complex media landscape. We also explored how modern and easy-to-use solutions can help you navigate the chaos. Revenue recognition impacts most media companies, so it needs to be planned into the business strategy early on to maximise future success. If a company does not have a clear understanding of their financial situation, it's difficult to plan and adapt to meet demands effectively.

In this article, we'll break down the complexities of revenue recognition in the media space and explore how modern technology can help your business make informed decisions that drive it forward.

Putting revenue recognition at the core of your decision-making 

When it comes to revenue recognition, many companies find this area problematic and need to approach it with careful consideration. Often, this critical process is handled manually at the back end, for example in finance systems, rather than integrated into the order management systems (OMS). As a result, it lacks agility and real-time data insights. To truly make this process agile and empower the sales team with data-informed decisions, you need to seamlessly incorporate revenue recognition into your OMS with real-time data.

When implementing any new OMS, you need to prioritise revenue recognition in the solution design. Poor decision-making at this stage can have detrimental effects on various areas of your business, leading to inaccurate data-driven decisions and unfavourable outcomes. By placing revenue recognition at the heart of your OMS implementation, every decision will be based on accurate and timely information.

Accurate and flexible calculation of revenue recognition 

The term revenue recognition means understanding how orders and order lines are calculated to provide precise values for data-driven decision-making. What makes it interesting is that not every business calculates revenue in the same way. That's why the OMS needs to align with the unique requirements of your business.

At its core, revenue recognition allows you to accurately show and calculate revenue based on when orders are received. For example, in the case of a print order for a magazine set to be released in June, the revenue should be attributed to June’s figures. However, things become more complex when dealing with digital orders that span multiple months. In such cases, the revenue should be apportioned across those months based on the duration it appears in each month.

Let's say a digital order starts on 1 June and ends on 10 July. The revenue for June should account for 30 days, and the revenue for July should reflect the remaining 10 days.

But even that's not the whole picture. For some customers, revenue recognition must go a step further and apportion values from the order to ensure accurate internal accounting.

Below is an example of how the revenue calculations can be executed when a production charge is involved, along with a free of charge (FOC) item. In this scenario, it is necessary to apportion the production charge to the other booked products, excluding the FOC item, based on the relative cost of each line.

Calculating transaction price  The production charge allocated to deliverables based on the relative price of each deliverable. Production is not a deliverable for this organisation. The customer 20% discount is apportioned to deliverable values one through four. These values must then be stored against the order in the correct period for accurate revenue recognition.

Calculating the invoice order value  Booked value is the standard price for a deliverable. Order value is calculated net of discounted or FOC items. FOC items should be displayed as that to the customer. 

This example highlights how revenue recognition can be used to calculate values for orders.

Revenue recognition is a complex subject, so you need a comprehensive understanding of all the associated rules from the very start of an OMS project. This way, the OMS solution can be tailored precisely to meet the specific requirements of the customer.

Implementing revenue recognition into an existing OMS presents a unique set of challenges, particularly when dealing with historical data. To provide an accurate year-on-year picture, it's essential to account for historical data to calculate the correct revenue recognition figures.

For media companies and digital bookings, there is an additional layer of complexity when it comes to calculating orders. If the price has been agreed upon upfront and is contractual, the calculation is relatively straightforward. However, when the price is based on unknown factors like actuals (what the order delivered during the period), it becomes significantly more difficult.

In the example below, we see the original digital order that was initially scheduled to run from 1 June to 10 July. However, the actual start and end dates differed, as did the delivered amounts. As a result, the OMS needs to consider not only the contracted value but also the value that actually occurred.

Data-driven intelligence 

With the data captured by the OMS, it’s now possible to make data-driven decisions. This wealth of information captured in analytics allows you to paint a clear picture and respond strategically to the data presented. In the example below, we can see a visual representation of how the figures for the example order have been calculated for revenue recognition.

This data-driven approach is key not only for reporting purposes but also for seamless invoicing. Having a clear view of what is being billed in each financial period should be standard practice and should be readily available.

But the real power lies in the ability to gain an overview and make proactive, data-driven decisions. Are you on track to meet your pipeline goals and targets? Being able to react proactively and influence these factors empowers businesses to be more agile than ever before. Gone are the days when finance departments and systems dictated these decisions, often when it was too late in the operation!

Bring experience and expertise to the table

In conclusion, it's clear that revenue recognition is far from a simple subject, with numerous nuances and complexities to consider. Getting it right and equipping your business with the necessary tools to comprehend the data and respond to it is strategically vital for achieving lasting success. 

At Credera, we understand the intricacies of revenue recognition in the media industry. Our team brings a wealth of experience and expertise to the table, ready to guide you through the complexities and help you navigate this critical aspect of your business. To learn more about how we can help you gain a competitive advantage in the dynamic media industry, please reach out to us today.

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