Use case

Deal desk pricing and CPQ.

From the field, AI native workflow redesign of pricing and cpq approvals process within Deal Desk Sales function.

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Convolving expertise

A senior Convolving delivery team partnered with the deal desk for one sprint. Operators from our expert network – with forty combined years inside enterprise CPQ, finance, and legal review – reviewed the redesign at each checkpoint. Forward-deployed engineers built inside the team's CPQ, CRM, and approval-matrix stack. One flat fee, artifact out, no retainer creep.

Situation

Today a non-standard quote takes one to three days to clear deal desk. The AE assembles the package; finance, legal, and product weigh in serially.

Discount logic lives in a policy document, an approval matrix, and the heads of three reviewers. Non-standard term review is a forwarded email thread. Most quotes wait on a reviewer who is doing other work; the deal slows in the last mile, when the buyer is closest to signing.

Approval time 1–3 days From submission to approved quote
Reviewer load Heavy Three to five reviewers per non-standard quote
Quote-to-close Adds days Approval is the late-stage drag
Policy adherence Variable Depends on reviewer attention

Click any node to see the activities and tools behind it. Open the canvas in fullscreen for the horizontal view.

Complication

Largest obstacles and inefficiencies.

One to three days at the last mile.

The buyer is closest to signing when the deal goes to desk. Every day of delay erodes the close.

Three to five reviewers, all part-time on this.

Finance, legal, and product reviewers triage between their day jobs. Quotes wait on attention, not on judgement.

Policy adherence drifts under volume.

Under quarter-end load, reviewers approve to keep deals moving. The matrix is honoured at the start of the quarter, not at the end.

Resolution

The AI-native cycle.

Same five steps. Click any node to see what the redesign does in that step.

Approval time Hours ▼ 80–90% vs today
Reviewer load Light AI clears standard, humans rule on exceptions
Quote-to-close Faster Last-mile drag removed
Policy adherence Uniform Every quote against the same rubric
Key changes

What the redesign actually shifts.

Cycle compression

  • Standard quotes clear in hours, not days.
  • Non-standard quotes route to the right reviewer with full context.
  • Last-mile drag on quote-to-close goes away.

Reviewer capacity

  • Reviewers rule on exceptions, not standard discount.
  • One review queue replaces the email thread.
  • Quarter-end pressure stops eroding policy adherence.

Policy discipline

  • Every quote scored against the same rubric.
  • Decisions cite the policy line that drove them.
  • Reviewer edits feed back into the library.

Audit and control

  • Every approval logs model version and reviewer override.
  • Concession patterns surface to finance in real time.
  • Sales leadership reads the desk queue, not anecdote.

Deploy this in your team.

The redesign above ships as a step-by-step playbook. Discount-policy mapping, approval-matrix rule library, exception-routing spec, model documentation, and the rollout cadence we use on engagements.

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