When Microsoft first released Excel in 1983, it changed the way businesses dealt with calculations and record-keeping. Suddenly, all sorts of data that had previously been difficult to handle were finally possible.
But, here’s the catch.
Almost 90% of all spreadsheets contain at least one error.
The ease of use and flexibility make excel spreadsheets the go-to answer for many use cases, including that of sales compensation calculations.
But, is that really the way to go?
Using Excel for calculating sales compensation is like Michael Scott attempting to lead a serious corporate meeting – it's full of awkward moments and ultimately results in a hilarious mess that leaves everyone wondering how on earth it could have gone so wrong.
But, despite all that, a significant number of SaaS companies use excel spreadsheets today to calculate and pay sales commissions (that often run into millions of dollars annually).
In this blog, we will look at some compelling reasons for you to think about replacing excel for sales commissions and the benefits that automating the entire process can get.
Let’s dive into 5 reasons why excel spreadsheets could be a nightmare for SaaS sales compensation management.
While excel spreadsheets are known to be easy to use and flexible to make changes to, sales processes at SaaS companies make it harder to track sales compensation for multiple reps across scattered spreadsheets.
Add to this, multiple levels of sales rep hierarchy and mid-term policy changes, bonuses, kickers, spiffs, etc. - it’s impossible to capture the level of detail needed for a complex sales commission plan to be facilitated via Excel.
With an increasing number of SaaS businesses striving to be ASC 606 compliant, sales commission accounting becomes all the more complex. Since ASC 606 needs companies to recognize revenue over time, rather than all at once, sales commissions accounting too has to be broken down into earned revenue over a period of time rather than being accrued all at once.
With spreadsheets, all it takes is one small error for it all to come crashing down.
According to a recent report, finance teams waste 12 hours per month "consolidating, modifying, and correcting the spreadsheets they frequently collaborate on and reuse.
Even if you start out with a simple sales compensation plan today, your comp plans are bound to become complicated as your SaaS company scales. While your Finance team may be able to handle scenarios for 5-10 sales reps, what happens when they need to split the master spreadsheet into tens of different spreadsheets for multiple reps, all with different comp plan structures?
This process requires your accounting team to remember each rep’s comp plan, which will eventually lead them to dread the end of every sales cycle. What’s worse? Your Finance team gets blamed for inaccuracies, and your sales team loses faith in your Finance team.
By choosing to run a manual sales compensation process using spreadsheets, your Finance team loses out on precious time on manual calculations that they could have otherwise invested in more productive tasks.
Switching to sales commission software automates the entire process, saving both your sales and finance teams hundreds of hours. Your sales reps focus on selling while your finance team focuses on other critical tasks such as auditing, financial reporting, and budgeting instead of being worried about payouts.
Suppose a SaaS company that sells CRM software pays its sales representatives 10% commission on each sale. For a deal worth $10,000, a sales rep should receive $1,000.
However, due to calculation errors or misinterpretation of the commission plan, the sales rep gets paid $1,200. While this may not seem much for a single transaction, imagine if this overpayment occurred across hundreds or thousands of sales — this could amount to a significant financial loss for the company.
Now look at it the other way around - imagine that the spreadsheets you’re using have a critical formula error and you’ve been underpaying your sales reps consistently over the last quarter. Imagine a room full of angry reps ready to tear you down. Also, the average cost of replacing a sales rep is $115,000.
Due to the level of manual intervention needed to calculate payouts using spreadsheets, such scenarios are bound to be repeated, making your reps lose faith in your organization, leading to a demotivated sales force, attrition, and eventual decline in sales revenue.
It isn’t your Finance and Operations teams that end up wasting countless hours on calculating sales commissions. Sales reps end up spending a ton of their time double-checking their monthly or quarterly payouts, sifting through the CRM data to validate their closed deals and re-checking their payout spreadsheet to tally both. Not only is this process time-consuming, it is also highly inefficient.
60% of sales reps estimate that they could save 6 hrs or more each week with commissions automation.
In addition to your sales reps being engrossed in commissions calculations instead of selling, this manual process also gives rise to more disputes raised which Finance teams need to resolve by fetching details for each rep manually. All in all, a complete hullabaloo.
It’s the end of the quarter sales, and the finance department created a master spreadsheet of commissions for all the sales reps. After compiling all the data, the Finance Manager realizes that the master sheet cannot be shared with everyone as it is a matter of confidentiality for each sales rep.
What happens next?
Well, the same master spreadsheet now needs to be split into hundreds of spreadsheets and then shared with each rep individually. It doesn’t end there. Now those spreadsheets need to be shared with each rep’s manager.
Spreadsheets are also opaque when it comes to sales compensation calculations. With each rep’s unique comp plan structure and plan policies changing frequently, excel spreadsheets fail to give much needed clarity to sales reps.
Excel's limitations in handling large datasets, its susceptibility to errors, challenges with respect to distribution at scale and confidentiality, make it a less than ideal option for sales commissions.
While it is true that smaller SaaS companies may benefit from designing their sales compensation plans on spreadsheets, Excel cannot be a viable option for those looking to scale.
By making the switch to a specialized sales compensation software for SaaS, companies can drive efficiency, accuracy, and peace of mind, allowing their sales teams to focus on what they do best – closing deals and driving business growth.
Say goodbye to the headaches of manual calculations, errors, and wasted hours. Elevate your SaaS sales compensation management with Visdum – a cutting-edge SaaS Sales Compensation Software.
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Calculating sales commission in Excel involves using a formula that multiplies the sales amount by the commission rate. Assuming the sales amount is in cell A1 and the commission rate is in cell B1, you can use the formula =A1*B1 to calculate the commission. Simply enter this formula in the cell where you want the commission result to appear. Excel will automatically perform the calculation based on the provided sales amount and commission rate.
The formula for calculating sales commission is:
Commission=Sales Amount × Commission Rate
In this formula, the "Sales Amount" is the total value of sales achieved by a salesperson, and the "Commission Rate" is the percentage rate at which the salesperson earns commission. By multiplying these two values together, you get the commission amount earned for a specific sale.
Determining a good sales commission rate depends on various factors, including the industry, product or service type, and sales cycle length. In general, commission rates typically range from 5% to 20%, with the average falling between 7-10%. It's crucial to strike a balance that motivates your sales team while remaining competitive in your industry.
Consider factors such as profit margins, sales goals, and the level of effort required for sales when setting commission rates. Regularly review and adjust rates to align with business objectives and market conditions.