If you’re here on this site, you’re likely already pretty knowledgable about and confident in the promise of a value advisory function. That said, it can’t hurt to provide a quick outline of why you might want to establish a program — or why you might want to collaborate with your company’s value advisors.
One quick note on terminology: there are a handful of phrases that folks use when talking about this sort of work. Some mean the same thing and some are distinct. For clarity, value engineering typically covers the pre-sale activities of connecting solutions to potential value and quantifying the opportunity. Value realization typically focuses on the post-sale activities that ensure customers see the results they expect — and therefore feel comfortable renewing their contract. Value advisory, consulting, and management are all broader terms that encompass one or both of those outlined above, and can incorporate customer success functions as well.
With that addressed, we can turn to the main question: why would a value advisory function be beneficial to your organization? Realistically, there are two core benefits: win more deals and win bigger deals. That is, increase your ‘closed won’ percentage and increase average deal size. The aim is to accomplish this by providing better detail and greater reliability to return on investment discussions and by having an additional resource that can help tailor the pitch to the prospect’s business environment (industry, geography, relative size, etc.)
Evaluating the potential is straightforward, and requires only a few pieces of data:
- What is the average deal size in the segment where you would be most likely to focus a value resource? This is not likely overall average deal size, since value professionals are typically deployed in larger deals or with larger potential customers.
- What is your current win rate in that segment?
- What is your typical deal cycle time in that segment? (This is optional and will not be used in the basic analysis below. While there are logical reasons why a value resource could accelerate deals, it has not been something I’ve seen play out.)
- Based on the complexity of your solution set and proposals, what is a realistic number of deals that a value resource could assist with in a year?
- And finally, what uptick in win rates and deal sizes is reasonable to expect based on their contribution?
Those last two items are obviously unknown, so we approach them looking at a range of possibilities.
Scenario: For this example, let’s say that you would have the value advisor help out in a segment whose average deal size is $1,000,000 USD and whose cycle time is around 12 months. At the moment, you win 50% of competitive deals and your pipeline is large enough that a full-time value advisor would be able to max out their capacity (i.e. there are more in-segment deals than they would have time to support).
We’ll assume that an advisor can dedicate their focus to two deals at a time and that their schedules are staggered so that they neatly close at a rate of two per month. Reality is not likely this clean, but it’s helpful for illustration.
Analysis: Over the course of a year, the advisor could be expected to support 24 deals with a total potential value of $24,000,000. Today, you’d win 50% of them, so $12,000,000 revenue is the baseline.
Win Rate. We’ll assume a minimum increase in win rate of 5% and a maximum of 15%, with the end result being a range between 52.5% and 57.5%. That would translate to an expected (i.e. weighted average) net benefit of $600,000 ($24m x 0.025) and $1,800,000 ($24m x 0.075). Practically speaking, that means you’d close roughly 1-4 additional deals that you would have expected to lose.
If we go with the higher of our earlier cost numbers, you would expect to receive a benefit of $600,000 to $1,800,000 on an investment of $300,000 — a 100% to 500% net return.
Deal Size. A similar evaluation works for average deal size in the target segment. We’ll be conservative and look at a maximum increase of 5%. That would mean an average uplift of $50,000 per deal — $1,200,000 in potential revenue ($50k x 24), and $600,000 at the current 50% win rate.
Combined. Rounding out the analysis, we can look at the minimum and maximum benefit to both win rate and deal size and combine them to see an expected benefit of $600,000 (+5% win rate but no impact on deal size) to $2,490,000 (+15% win rate and 5% increase in deal size). That’s a 100% to 730% return.
Reality Check. The last piece of the puzzle is asking how likely it is that we would see these results. Based on past experience, it does not seem unreasonable — but that is purely anecdotal. The 5% win rate figure has been shared online, but I have not seen a rigourous study of this particular metric.
If you’re an optimist, then you’d say there’s a 100% chance of a net return between 100% and 730%.
If you’re skeptical, perhaps you’d say there’s only a 50% chance of a return in that range. The good news there is that at 50%, that’s a weighted benefit of $300,000 to $900,000 — meeting and exceeding breakeven on the investment in your value advisor.
Final Thoughts. As with any value analysis, there are many variables that can swing the results one way or another. This exercise is closer to the outside-in analysis you’d prepare before engaging with a prospect. As you learn more, you reduce the assumptions and increase the reliability. If your baseline win rate and/or average deal size is higher or lower, the expected benefits shift as well. If your value advisor under- or over-performs on their potential impact, the numbers shift once again.
All things considered, without the benefit of hindsight, some level of investment in the value advisory function seems like a fairly safe bet.
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Checking the Math:
number of deals x average deal size x current win rate = baseline expected revenue
number of deals x new average deal size x new win rate = new expected revenue
[ (expected revenue – baseline revenue) / value advisor cost] – value advisor cost = net return