It is important to recognize and track changes that occur in any business. But it is also crucial to understand the reasons for those changes.
When it comes to revenue, many businesses focus on the immediate facts of those changes – their scale and where they arose, for instance. They don’t, however, focus on the factors that underlay those changes, or conduct the advanced PVM analysis that can support better management of their business.
Why is PVM Analysis Important?
You may know the broad reasons why revenue margin changes across different segments of your business. PVM analysis, conducted properly, can drive down into the salient details that contribute to those changes, so you are able to better visualize their cumulative effects on your EBITDA.
As Tim J. Smith explains,
An appropriately defined profit bridge will connect the profits of one period to another with clear measurements of the impact of changes in business variables between those time periods. It will provide understandable and recognizable facts for ease of communication and decision-making. While alone, a profit bridge cannot definitively state what actions to take, combined with other measurements and business intelligence, it can lead to better decision-making. Moreover, it apparently has interest to investors as some companies communicate their profit bridge to investors in quarterly and annual reports.
As we explain it in our own resource, “A Practical Guide to Price/Volume/Mix Analysis”:
The main purpose of PVM analysis is to provide a high-level overview view into the past, and to break down the change in revenue or margins into some key components or categories. The categories are used to highlight and help explain how much of the overall change in revenue or margins was caused by, e.g. the implemented Price changes, versus changes in total costs, versus the impact from change in Volumes, versus changes in currency fluctuations or other effects, comparing two different time periods.
Decomposing PVM Into Discrete Mix Effects
Often, PVM analysis will unveil decisions that were being made “beneath the surface” in situations where an organization did not have a process in place for solving margin challenges. For example? In many companies, margin and pricing decisions were made at beginning of the year and were stuck with throughout the year, for better or (too often!) worse.
So any shift toward having huge templates/product line reviews inserted into a sales motion can have a big difference in margin. This spotlights the impact finance and pricing can have on the rest of the organization.
PVM analysis provides a long list of insightful applications for these analytics. It can enable businesses to tailor models to stakeholders and specific areas of interest. Pinpointing the sources and causes of change provides the sort of actionable insights you can apply in making intelligent adjustments to your product and brand strategy.
As we point out in our Practical Guide,
A ‘one-size-fits-all’ PVM Model is not enough to support the specific business needs of different stakeholder groups or regions, and to provide them with the required level of granularity and insights to easily pinpoint potential problem areas.
Where can a customized and thorough PVM analysis deliver that level of granularity?
The ‘Cost Effect’:
- Un-boxing the black box of ‘Total Costs’: Imagine a scenario where product costs went down but overall ‘costs’ have increased and the Cost Effect on aggregated level shows a negative margin impact.
- Decomposing the Cost Effect ‘container’ and breaking it into further categories, directly linked to specific waterfall adjustments, makes the PVM model more insightful and actionable.
The Interaction Between Volume and Mix:
- In general, the volume effect represents the effect of revenue/margin change due to changes in volume with an assumption of unchanged prices/margins across the comparison periods.
- Change in volume has an impact on the portfolio mix when aggregated up to a higher level on your business hierarchies.
- When a PVM model does not include a Mix effect, the Volume effect is decomposed further into a computed/’adjusted’ Volume effects with discrete Mix effects.
- Mix effect = change in relative contributions occurs at all levels in your business hierarchy when aggregating on different level.
The Exchange Rate Effect:
- Decomposing the Exchange rate Effect, somewhat of a ‘blackbox’, into the different currencies or group of currencies enables more strategic volume re-allocation in some industries or businesses, to benefit from regional currency fluctuations.
- You can attain a higher level of granularity by unboxing the ‘Mix’ into different Mix Effects helps to identify trends and to better understand the drivers for revenue/margin variation.
New-/Non-repeat Business Effect:
- Comparing and assessing price levels or volumes in one period versus another on a very granular level, e.g., on the customer + product level, typically only makes sense if there is a purchase for that customer + product in both time periods.
- It enables you to put the focus on the business that is comparable and as a result the decomposition into the distinct categories, and their impact on change in Revenue/Margin, becomes much more relevant.
- In a model without separation of New/Non-Repeat Business, related Revenue/Margin goes into the Volume Effect, or if decomposed further, also into the Mix-Effect. The Volume and Mix effect values are skewed, as they are carrying related Revenue/Margin delta coming from ‘non-match’ business transactions.
Impact of Changes in List Price on Revenue:
- Understanding the impact of the various Price adjustments and the interaction between List Price change versus other On- and/or Off Invoice adjustments and their impact on Gross or Net Revenue helps to refine your pricing strategy and protect both, your top and bottom line.
- By selecting different price points from the Waterfall, e.g. using List Price as the reference to calculate the Price Effect and the Invoice Price as the anchors for “Margin” provide full visibility on the impact of List Price changes.
The Importance of Employing the Right Data
A quick Google search can turn up many examples of how to take a DIY approach to causality analysis and modeling. But a truly thorough PVM analysis will go far deeper than off-the-shelf approaches, allowing a company to really empower that old adage, “manage what you measure.” Because now, the PVM analysis user has far more granular insights s/he can manage against.
To tell the necessary stories, though, you need a crazy amount of data.
For instance: You may see stagnant revenue and declining gross margins, but outside of the broad numbers, any “insights” are strictly anecdotal. And, therefore, possibly misleading. If you add data, you can decompose PVM into discrete aspects to tell that story. Having the right data, obtained from viable sources, correctly transformed and extracted for use in calculations, is key if you want to decompose ‘Total Costs’ into specific price adjustments or cost elements for a more granular breakdown in your PVM model.
Depending on the purpose of your PVM analysis and model, it might make sense to add filters to your dataset. These can ensure analysis outputs and suggested actions derived from meaningful and solid data, focused on just the subset of data that ‘qualifies’ for this specific analysis. This leads to suggested actions that will be precise and effective.
Often, the pain in the analysis involves the struggles you go through to get the data you need to tell an accurate story. But it’s worth it, since revealing that story allows you to make the exact changes necessary to increase gross margins.
Vendavo Offers Solutions + Insights
With solutions like Vendavo’s Margin Bridge Analyzer, you can accurately measure and monitor the business impacts of complex variances in prices, volumes, product mix, and other dynamic market factors.
To learn even more, please consult the new download we’ve quoted from liberally in this post: “A Practical Guide to Price/Volume/Mix Analysis.” And/or watch our recent expert webcast, “How Strategic CFOs Leverage Margin Bridge Analysis.”