ANTTI RAUHALA
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CASE_003 / IDX / AUTUMN 2026

Less admin.
More selling.

Finding the bottleneck in a sales process — and turning it into a small, measurable AI pilot proposal.

MY ROLE
Initiator, analyst and presenter
STAGE
Approved to scope in principle
PERIOD
Autumn 2026
Proposal / Pilot not yet run
01 / THE PROBLEM

Where does a salesperson's time go?

A walkthrough of a real deal with the sales director exposed administrative work and handoffs around the sales process: compiling an opportunity form, waiting for an estimate and moving contract paperwork forward.

In that illustrative deal, preparing the opportunity form took about half a day; the estimate could wait up to five working days; and contract paperwork could stall for up to two weeks when the relevant person was unavailable. These were observations from one deal, not company-wide averages.

The problem wasn't how quickly AI could write a proposal. It was how to prepare a request that the next person could act on.

02 / THE CHANGE IN THINKING

Automating the wrong step is still the wrong solution.

I compared a public sales-automation benchmark with IDX's actual process and existing AI-assisted RFP response capability. The bottleneck pointed to preparation and handoffs, not simply document generation.

So I narrowed the proposal: one controlled use case, tested alongside the manual process. AI can reduce preparation effort; it cannot manufacture estimate-team capacity or eliminate every wait.

03 / PROPOSED WORKFLOW

One real problem. Two weeks.

The proposed assistant would transform approved deal information and a client conversation into an estimate-ready brief. A salesperson would check it and submit it using IDX's existing process.

INPUT

Client conversation

Notes and approved deal details

AI DRAFT

Estimate-ready brief

Opportunity form, scope summary, open questions and estimate request

HUMAN CONTROL

Review & submit

Salesperson checks the output and uses the existing workflow

FIG. 01 / Proposed process, not a deployed automation.
04 / TRUST & MEASUREMENT

AI suggests. People decide.

The proposal was designed with clear operational boundaries and success measures before any build commitment.

Drafts onlyNo CRM writes, pricing decisions, contracts or unsupervised external messages.
Human time measuredPreparation plus review, not just AI generation time.
Quality checkedCompleteness, errors and clarification rounds compared with manual work.
Decision checkpointGo, change or stop after the pilot, subject to feasibility and resources.

A handful of cases can demonstrate feasibility, but cannot establish a reliable return on investment.

05 / MY CONTRIBUTION

From discovery to a decision.

I initiated the work, walked through a real sales case, analysed the bottlenecks, reviewed internal and external reference points, specified the narrow pilot, designed the measurement approach and presented it to Nordic management.

I used Claude for research, drafting and critique, while retaining responsibility for the framing, constraints and executive narrative. The decision deck was distilled from a longer explainer into nine main slides plus an appendix.

06 / OUTCOME & NEXT STEP

Approval to scope. Not a claimed saving.

Management gave the go-ahead to scope a two-week pilot in principle, conditional on feasibility, security and budget. The pilot has not yet run and no time-saving or ROI result is claimed.

Next steps are to write a one-page scoping note, baseline five to ten recent estimate requests, and confirm technical, security and budget ownership.

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