What we solve ·Where do I put the budget?
Vanguard · Guide
Where is your sales cycle breaking down, and what can actually move it?
The forecast does not hold and we do not know why a deal falls until it has already fallen.
Where automation moves the needle in a long sales cycle, meaning qualifying, responding and forecasting, and what they are selling you that moves nothing.
Prioritization for enterprise salesSend this page to whoever decides
This sounds like you if
- The sales cycle changed and the forecast stopped reflecting it.
- Preparing a technical proposal takes you weeks.
- The sales cycle got longer and the cause is not isolated by stage.
Use this today, without hiring anyone
The calculation of time lost on opportunities that were never going to close. It is the most expensive number in your area and it comes out of your own system in an afternoon.
- Pull the closed lost opportunities from the last twelve months and keep the ones lost after stage two. Those already consumed real work.
- Estimate the hours per opportunity: meetings, proposal, demo, follow up. Ask two salespeople and average; you do not need precision, you need an order of magnitude.
- Multiply and apply the loaded hourly cost of your commercial team. That is the cost of qualifying badly, and it is usually larger than any tool being offered to you.
- Now the uncomfortable part: at what stage were they lost? If most fall after stage three, you do not have a demand generation problem: you have a qualification problem, and no tool fixes it.
And a forecast honesty test that runs itself: compare what you forecast two quarters ago against what actually closed, opportunity by opportunity. The difference is not bad luck, it is a pattern, and it is always at the same stage.
How we solve it
The method, not the promise.
- The real cycle gets reconstructed stage by stage with your data: duration, pass through rate and cause of loss.
- The effort spent on opportunities that were never going to close gets quantified. That number orders everything else.
- The candidates get ordered by measurable effect on qualifying, responding and forecasting, which are the three bottlenecks of a long cycle.
- Whatever does not apply to a long sale gets dropped, with the reason written.
- The requirements get turned into acceptance criteria to demand from whichever vendor gets contracted afterwards.
What you receive
- The sales cycle map with duration, pass through rate and cause of loss by stage.
- The figure for effort spent on unqualified opportunities.
- The ranking of candidates with their estimated effect and the assumption left open.
- The reasoned exclusions and the acceptance criteria for the vendor.
The proof that applies here
- Global Product Manager of two corporate products taken to the Gartner Magic Quadrant.
- 19 years in both chairs of corporate selling: selling from HPE and IBM and buying from Citi.
- Six Sigma Black Belt, for the part about measuring the cycle before giving an opinion on it.
Before you hire
The scope reaches as far as the sales cycle: it does not go into customer analytics, propensity or predictive retention, which is different ground and a different vendor.
What decides this is which side of the table the person analyzing it sat on. This gets reviewed by someone who filled in vendor questionnaires from the selling side and assessed them from the buying side, and knows at what stage large deals actually fall.
Of the deals you lost last year, at what stage did most of them fall?
If the problem is a different one
The assessments people bring me talk about the company. I run operations.
Prioritization for operations
We have been two months inside the customer's questionnaire and every answer opens three more.
Enterprise readiness
They are pushing us to put AI into recruiting and I am the one who signs off on whatever comes out.
Prioritization for people functions