Harvesting and analyzing data about your sales process helps you to understand where you’re succeeding and the bottlenecks slowing you down.
One of the best ways to combine your data is to form sales forecasts, which help you understand if you’re seeing a period of growth or falling short of your expectations. The rest of the company also relies on revenue forecasts to know how to budget their own operations.
One metric that can feed into your sales forecasting is sales volume variance. By working out your sales volume variance, you can delve deeper into your revenue data, extracting important insights about how external factors influence the sales of your product and also see where your product sits in the market versus its competitors.
So, what is sales volume variance and how can you utilize it to understand your products, sales and revenue?
Sales volume variance, also known as sales quantity variance, is a measure of the change of sales over a period of time in regard to how it affects profit or contribution.
This is done by taking the expected sales from your sales forecast and comparing it to the actual sales volume, or actual number of units sold, made during that time.
By working out the exact number of sales by which you have either exceeded or fallen short of your budgeted sales projections, you can scrutinize your sales performance for a set period or identify trends by comparing your sales volume variance over a longer period of time.
Sales volume variance is used to determine one of three things:
Your total sales variance: the variance between your estimated and actual sales revenue.
Your standard profit variance (also known as absorption costing): the variance between your estimated and actual net profits.
Your standard contribution variance (also know as marginal costing): the variance between your estimated and actual contribution costs (i.e. cost of production).
Your sales mix variance, meanwhile, also takes each different product's profitability into account, finding out if each contributed to an unfavorable or favorable sales volume variance. Sales mix variance takes into account the actual quantity of every product sold, their budgeted price and budgeted profit.
Measuring your sales volume variance is a chance to reflect upon your sales forecast. Whether you managed to exceed your forecast (known as a favorable variance) or fell short (known as adverse variance), simply knowing your variance will help isolate the parts of your sales forecast that need refining to project more accurate numbers in the future.
If you’ve exceeded your forecast’s expectations, it could mean there’s a bigger demand for your product than you thought, or that new sales activities within your team have had beneficial effects. Research on competitor products could show there’s room to increase the price of your product while still remaining more affordable than the competition.
An unfavorable variance might mean you need to reassess your sales reps’ approach and work out why your team hasn’t been reaching your projected sales targets. It could also reveal that your product is overpriced against the competition, or that there’s even a lack of market interest in the product.
Calculating your sales volume variance can even provide insights to parts of the company outside of sales.
If your standard contribution variance is unfavorable, it could be a sign that your company is spending too much on parts and may need new suppliers for your product, or that a rethink of your manufacturing logistics could make your product more profitable. Perhaps one product always exceeds expectations, but another isn’t resonating with your customers.
The first step is to subtract your predicted sales in your sales forecast from your actual sales during the time period. This will leave you with either a positive number (indicating a favorable sales variance) or a negative number (indicating an adverse variance). This number can then be multiplied by a key figure that directly relates to the type of variance you’re interested in working out.
If you’re not already making sales forecasts, you should be. Forecasts are an invaluable tool for your business. All departments depend on accurate sales forecasts to budget for the coming period and the process of putting together a forecast involves pulling from a range of useful sales data.
Let’s look at the different sales variance formulae and when to use each one.
1. Total Sales method
(Actual units sold - projected units sold) x price per unit
This method of calculating sales volume variance is most useful to the sales team, as it ignores factors such as production costs and profit margin, focusing solely on the difference between the expected and actual revenue brought in by the sales team.
2. Absorption Costing/Standard Profit Method
(Units sold - projected sales) x standard profit per unit
This method focuses less on overall sales team performance, increasing the scope to look at product viability in the market, cost of suppliers, product pricing, budgeting strategy and other factors that impact the profit margin of a product.
Your sales team may make a favorable sales volume variance when it comes to revenue, but even so your company may not be making enough profit on each item to reach a favorable standard profit variance.
Therefore it’s important to separate out the different aspects of what attributes to your company’s final profit to understand where changes need to be made.
3. Marginal Costing/Standard Contribution Method
(Units sold - projected sales) x standard contribution per unit
Marginal costing variance also broadens the focus from just sales performance. Using this formula, you can determine whether the running costs of your company—production, logistics, staff overheads etc—are viable, or whether changes can be made to improve the efficiency of these costs.
There are many factors that affect sales quantity variance, both internal and external. Here are some of the most common.
Changes to the sales process: Perhaps the most obvious factor, changing the way you sell is bound to have an impact on whether you meet your quotas, how much you sell and your sales variance.
Underperforming/overperforming reps: If you’ve been collecting sales data then identifying drops or improvements in your reps’ performance is simple. You can then take action to tackle bad sales practices or encourage successful techniques, respectively.
Pricing: Setting a selling price point for your product that doesn’t reflect its value, or prevents it from competing in the market, could impact your sales volume variance. It’s important to take into account the standard profit variance too, as increasing the standard price may mean fewer sales overall, but could lead to an increase in profits.
Planned alterations to the supply chain: Your company may wish to switch suppliers, perhaps to reduce costs or improve quality. Changing the cost and/or the quality of your product will have an effect on customer perception and experience, leading to a change in sales volume variance metrics.
Increasing or reducing the output of your products: Changes to product quantity can either reduce or increase your manufacturing costs, affecting your standard contribution variance.
Seasonal effects: Customer demand for your product may change depending on the weather, the time of the financial year or whether it’s coming up to a holiday. It’s important to take into account how the time of the year plays a part in your sales volume variance so you can more accurately predict future revenue and sales.
Changes to competitor pricing: If a competitor decides to raise their prices their customers may switch to you as the better value option (taking advantage of this with targeted marketing and offers is always a good idea). If your competitor lowers prices, you might find your own sales variance adversely affected.
Unplanned alterations to the supply chain: If a supplier lets you down last minute, you may find your standard profit variance adversely affected by having to find a new supplier at short notice, even if your sales volume variance is favorable.
Change in market interest in your product: Waning or growing interest in your product may show itself over time.
Calculating your sales volume variance helps establish the accuracy of your sales forecast: a significant variance from your prediction shows that there are more severe internal and external factors affecting the sales of your product.
The key is to understand what your sales volume variance is highlighting, as well as your team’s sales process, your staff’s performance and effects on the market coming from outside your team. With this data, you should be able to hone in on which factors are affecting your sales and take action to address adverse variances or encourage favorable ones.
Now we’ve covered sales volume variance, let’s look at how to create your sales forecasts with sales data.
What is sales data?
Sales data points provide you with insights into your sales process and activities, especially when compared to your KPIs.
It’s important to determine which metrics will be the most useful to you and your team. Your sales methods and organization size will affect the ideal metrics for you to track.
Check out our comprehensive guide to sales data here to learn more about the myriad benefits your business could see.
How does sales data contribute to the sales forecast?
By looking at your sales data, you’ll be able to determine a percentage chance of how likely a lead is to convert to a won deal.
You can work this out by seeing how many leads enter your sales funnel and how many convert to customers at the end of it.
By dividing 100 by the number of leads and then multiplying by the number of new customers, you can work out the chance of each new lead becoming a successful deal. You can then predict how many deals your team will win based on how many new leads you acquire.
This is the beginning of your sales forecast.
Over time, as you continue to make sales forecasts, you’ll begin to build up historical data you can draw from to refine your forecast. You can also take into account seasonal changes, for example, that will lead to more accurate forecasts in future.
Where do you find sales data?
If your team is used to documenting all your processes manually in a spreadsheet, then collecting sales data can be time consuming and disruptive.
However, you can eliminate this problem entirely when using CRM software.
CRM Software with strong automation and integration features, such as Pipedrive, saves sales teams time. CRMs help to automatically log sales data, shifting you and your team’s focus to making use of the data.
With your CRM in place, finding your sales data is as simple as turning to the insights tab.
Pipedrive enables you to customize your insight dashboards with the KPIs and sales data that best visualizes your progress and process. Managers can create a dashboard that displays overall sales alongside aspects of the sales process they are in the process of refining. Sales reps, meanwhile, want to keep a dashboard of their personal metrics.
Get started with your sales dashboard templates by downloading our free templates.
With an understanding of how to calculate your sales volume variance, you should be in a position to know if it’s something your team/organization should be considering.
Sales volume variance is an excellent way to feed sales results back into your larger data collection efforts. When used in conjunction with your sales forecast, it’s a great indicator for general progress and for isolating the factors that have been affecting your sales adversely or favorably.
If you already have the data in place to make accurate sales forecasts, then working out your sales volume variance should be your next step, as you have all the information you need to gain further powerful insights.
But if you’re new to the idea of collecting sales data and sales forecasts, then we recommend starting there and building that into a strong foundation first. Sales data provides insight into your sales process and performance, especially when coupled with a CRM’s insights dashboards.
Once you have a system in place to analyze your sales data, it’s time to start thinking about sales volume variance.
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