There’s no question that value selling works.
Most companies want to create a value framework, but it’s a project that requires a unique skill set. You need someone who’s technical enough to understand the features nuances, the business acumen to understand how driving specific KPIs impacts the top and bottom line of a balance sheet, and the writing skills to put it into words. It’s why value engineers come from a few key backgrounds. The main being:
It’s a matter of sitting down, doing a deep dive by talking to customers and salespeople, and working through what the value framework is.
Now that the time is right, you've decided to sit down and create your value framework. A common question - where do you start?
Answering that question is the goal of this article.
Our team is lucky to have learned from the best value teams in tech. There's a clear set of patterns amongst these teams. Here's the secret sauce:
From small startups to public companies, here’s how most companies categorize their value into one of 4 categories:
Category 1: Revenue
A trend our customers' prospects talk about - especially given the current economic climate - is that saving money isn't’ enough.
When IT or customer support asks for budget for a new tool, they have to show not only how it will reduce existing costs, but also how it will contribute to net new revenue. Cost centers need to transform into revenue centers.
The exercise here - think about how your solution affects the top-line. Does it increase pipeline? Increase conversions? Free up support agents to become outbound sales development reps?
In most cases, you can use this to estimate a small number of net new contracts that close thanks to your product. To bring this to a financial value, multiply it by the average contract size. Winning 10 extra deals a year has huge ROI. Being conservative tells the story without breaking credibility.
Category 2: Cost Reduction
We'll break down cost reduction into two categories: Labor and Operational.
Labor
This is the most common, and largest area of savings that value models quantify. If you sell software, your product likely automates something a human was spending time doing manually. They are paid some amount to do that task. This is our path to quantifying the value.
The basic formula:
Time to complete task x Reduction in time it takes with your product = Time freed up.
Time freed up x cost of a person's time = value.
For example:
A Data Analyst cost is $60 per hour. They spend 20 hours a month doing impact analysis.
If your product (say a data catalog for example), could reduce this by 50%, and bring the time down to 10 hours, that means:
20 hours now x 50% = 10 hours saved each month.
10 hours each month x $60 = $600 in value saved each month.
It's rare that a company actually reduces any existing headcount after buying a tool (this is another can of worms for another post). But this formula is a way that gets us to a number we can put in a business case.
Ask yourself - who is your end-user, and what task are you making easier? By answering 1) how much time you save them and 2) how much their time is worth, you have your dollar value.
Operational Reduction and Tool Consolidation
A big benefit of SaaS tools is tool consolidation. By reducing the net number of tools a company needs, there's money saved. It's a line item that even the CFO or head of procurement would understand.
Ask the question - what are the existing solutions that you're up against in sales situations? Does your product fulfill the need that the prospect is using 3 separate tools to address today? Do you reduce the required spend on other tools?
Category 3: Risk Reduction
Risk reduction is particularly important when selling security products. There are two main ways of quantifying the value of risk reduction:
1. Reducing the likelihood of a breach.
2. Reducing the likelihood of human error.
Security Breach
The most consistent formula for putting a dollar value to risk reduction is the expected value formula:
Cost of breach x likelihood of breach = value at risk.
Value at risk x reduction in risk = value.
Cost of breach includes any damage to your brand, fines, etc.
Ask yourself - by what magnitude does your product reduce the likelihood of a breach? The cost of cyber attacks is rising rapidly (McKinsey estimates its pushing 10.5 trillion), so reducing it will have significant ROI.
An example:
$10,000,000 cost of breach x 1% likelihood of breach = $100,000 value at risk.
$100,000 value at risk x 50% risk reduction = $50,000 of value.
Reducing the risk of human error
Software reduces the risk of human error. When there is human error, the responder (a human) spends time remediating the error. The formula for value in this case:
Number of Times task occurs x Likelihood of error = Number of errors
Number of errors x responder hours remediate error = responder time lost.
Now we can tie this back to the same framework as Category 2 - and use labor costs as the financial factor to quantify the savings.
Category 4: New Value Gain
This category of metrics is the hardest to quantify, but ends up one of the most impactful. Tools like Okta, Salesforce, etc. impact the entire company, and consequently impact the culture. These culture shifts have huge ROI, but are so downstream that they often go overlooked.
To try and quantify these, here are the best practices we have found:
Putting it all together
If your company is single-product or moving towards a platform model with 8-10 total items across the 4 categories, you’re in a good spot. In most cases, your champion and key stakeholders are going to focus on a subset. Simple is always better.
If you need the extra man power in identifying what your value metrics will be - get in touch with us - it’s a muscle we’ve grown over the years.
We’re hoping to continue this blog series, so let us know if there are any topics you’d like addressed or if you have any questions.