Strategic accounts at the highest level: the largest deal of my career, a global partnership carried through a down market, and five President’s Clubs.
I have been trained in most of the major methods: SPIN at Huthwaite, MEDDIC and MEDDPICC, Miller Heiman, Challenger, and Amazon's Working Backwards. After twenty-two years my read is that they are the same method in different vocabulary, and every one does a single job: it answers the client's VUCA, volatility, uncertainty, complexity and ambiguity, which has lately become BANI, brittle, anxious, nonlinear and incomprehensible.
A buyer in that world copes by forming a confirmation bias: a settled idea of what the problem is and what the answer looks like, decided before you walk in. Consultative selling is a structured, frankly psychological way to probe until that bias surfaces, then align what you sell to it. Economic buyer, champion, decision criteria, implication questions: all of that apparatus exists to expose it. Align to it, and you have resolved enough of their VUCA for them to act. Fail to, and nothing else you do matters.
Recognizing when the bias will not move, and killing the deal early instead of carrying it in the forecast for two quarters. For a leader, that is how you protect your team's capacity and the integrity of the forecast.
I lead the way I sell, pointed inward. Here are the qualities the sales-leadership research keeps finding in the best leaders (RAIN Group, Gartner, the Sales Management Association, CSO Insights, Harvard Business Review), and how I run each.
Every seller gets regular, individual coaching, not just deal reviews.
Weekly one-to-ones with every person on my team: their deals, their opportunities, the obstacles in the way, and coaching on each. I ask leading questions until they reach the answer themselves, because the answer they reach is the one they execute.
A predictable operating rhythm the whole team plans around.
A weekly team meeting in three parts: team and organization updates, a guest from another department or a partner, and what I called Blue Sky, open collaboration in breakout rooms, three or four topics at once. Through remote years it was the team’s water cooler. Today I would run the recordings through AI into one consolidated read-out.
Sales, partner and service teams work one plan, even across reporting lines.
At AWS I owned the account plan for the global MongoDB partnership. The sell-to team reported to me, and the partner and technical service teams had their own leadership and their own remit. I aligned all three: a weekly whole-team call on what is pressing and where executives need to step in, a biweekly call with each team on plans and operations, and a quarterly account review against the plan.
The number is called on facts, with a very small margin of error.
Accuracy comes from visibility: into every deal through Salesforce, into the team through the cadence above, and into the account itself. In the NTT cross-sell program an opportunity review board and a deal intake process qualified every opportunity before it counted.
Every deal is inspected the same way, so a commit means something.
I inspect every deal for the same thing: whether we have surfaced and aligned to the buyer’s own view of the problem. If that view will not move, I would rather lose the deal this month than forecast it for two more quarters.
Quotas are believable and the rules for who gets credit are clear.
I designed the cross-entity compensation model for NTT’s cross-sell program, so a seller is made whole wherever a deal books, and at AWS turned MongoDB’s compensation change into a reason for both field teams to sell together.
AI becomes the seller’s partner and takes load off the job.
I build the systems a team runs on: account research where every figure carries its source, outbound that drafts and waits for a person’s approval, and the reporting that shows where the team should spend its time.
Buyers are self-directed, use many channels, and decide in groups.
Every method answers the buyer’s VUCA, now BANI. I build the path they want to buy through, like the cloud marketplace motion that ran 727 transactions worth $130M.
Decision-makers are engaged early, and kept engaged.
The weekly question on my team call was where executives needed to be involved. A partner’s support counts only once their executives have said yes.
The recognized methods for large, complex deals (MEDDPICC, SPIN, Challenger, Miller Heiman Strategic Selling and Large Account Management) describe the same seller. Here is that seller, and how I work.
Teaches the buyer something new about their own business.
I read the pattern before the account does. At AWS I saw AI coding as a way to make MongoDB easier to build on, and co-led the integration into Amazon CodeWhisperer before AI coding had a popular name.
Engages the whole buying group (six to ten people in a complex purchase, Gartner finds), not one contact.
Multi-threading is still selling: every person in the group has their own VUCA. I find out what matters to each of them, personally and in their job, and make what I am asking help them do that job better, look better, earn more and keep it. Align to that, and people work with you because they believe in it.
Reaches the economic buyer and the C-suite early.
From negotiating a global master services agreement in Japan to C-level relationships across AWS’s MongoDB account, I work where the decision is made.
Knows the metrics, the decision process, the paper process, the champion and the competition.
Every method I was trained in exists to expose the buyer’s settled view of the problem. I qualify to it, and I walk away early when it will not move.
An account plan that sets where to invest, where to stop, and who to know.
I owned the overarching account plan for AWS’s global MongoDB partnership and reviewed every team against it each quarter.
Delivers measurable impact that turns into growth.
The Texas Department of Transportation contract I originated was signed at $190M over five years. AWS’s MongoDB account grew 24.6% in a down market.
Dixon and McKenna found 40 to 60% of deals end in no decision. The best sellers remove the risk and recommend a path.
A buyer stuck in VUCA does not move. Align to the view they already hold and you resolve enough of their uncertainty for them to act.
Implication and need questions, not feature pitches.
I probe until the buyer’s real view of the problem surfaces, then shape the recommendation around it.
Every partner in the deal is sponsored at the executive level.
I closed the price gap on a $42M bid to $15,000 and still lost, because I had assumed the partner’s executives were behind us. I have secured that support early ever since.
| Where | What I did | Source |
|---|---|---|
| Texas Department of Transportation | Originated the IT outsourcing contract from the Dimension Data side: network, security, datacenter and application services. Signed in 2013 at $190M over five years, papered through NTT DATA, which held the only State of Texas contract vehicle among the NTT operating companies. | Source: Texas Tribune, 4 Jun 2013 |
| MongoDB, for Amazon Web Services | AWS’s global MongoDB partnership, a $172M number grown 24.6% year over year in a down market. I owned the account plan and led the fourteen-person account team behind it. The sell-to team reported to me directly, and the partner and service teams aligned to my plan. | Source: AWS performance record, by reference |
| NTT’s top 90 Americas accounts | Reported into the NTT Global Business Office in Tokyo with the Americas. The program sat across the operating companies of Dimension Data, NTT Communications and NTT DATA. Each operating company carried a cross-sell number of its own, and those numbers rolled directly into mine, while their sellers and leaders reported into their own companies. The Cross-Sell Program I led produced more than $200M in contract value and more than $1B in pipeline in 22 months. The nine-person team I led on Japanese multinational accounts drove over $100M in revenue at 90% year-over-year growth. | Source: NTT records, by reference |
| Financial services, insurance, law and global accounts | Banks and asset managers through the algorithmic-trading years, insurers, one of the world's largest law firms, and a global electronics company. Detail on the private pages I share with companies. | Source: Dimension Data records, by reference |