Pharmalyze.AI
Client · European pharma distributorIndustry · Pharmacy retail & distributionSep 2026

AI-assisted sales target planning

A commercial team set the next cycle's targets for 106 pharmacy chains across 6 brands in about three hours — work that had taken several working days. In one two-hour session they put 214 business questions to their own data, roughly one answered question every 34 seconds.

Sep 18, 2026 · Vladimir Simeonov

AI-assisted sales target planning

Results at a glance

full target-setting cycle, against several working days
~3 hrs
pharmacy chains covered
106
brands planned in parallel
6
business questions processed in one 2-hour session
214

Working cadence: one answered business question every 34 s, sustained across the session.

01 — The challenge

Target setting ran one brand, one chain, one spreadsheet at a time.

Each planning cycle began with an extract request. Sell-in history, sell-out by chain, prior-year attainment and chain-level agreements lived in separate systems, and the planning team reconciled them brand by brand in spreadsheets.

Every "what if we moved this chain up 5%?" meant another pass through the data and another wait on an analyst. The cycle stretched across several working days, and by the end of it the assumptions at the start were no longer the ones being discussed.

  • Sell-in history

    ERP extract, per brand

    On request

  • Sell-out by chain

    106 chains, mixed formats

    Monthly

  • Prior-year attainment

    Planning spreadsheets

    Per cycle

  • Chain agreements

    Commercial terms, shared drive

    Untracked

02 — Where the numbers come from

Four sources, one model, one conversation.

Sources

Sell-in · ERP
Sell-out · 106 chains
Targets & attainment
Chain agreements

Pharmalyze model

Brands × chains × periods, reconciled nightly

In the session

Ask a target question in plain language

Read the answer as metric cards and progress-vs-target

Commit the number, move to the next chain

03 — In the app

A planning session is a conversation, not an export.

The team worked straight through the chain list in chat. Each question returned the brand's sell-in for the period, its position against the current target and the prior-year comparison — enough to set a number and move on.

Because every answer came from the same model, the six brands were planned in parallel rather than in sequence, and nothing had to be re-reconciled at the end.

04 — Before and after

One cycle, measured the same way twice.

MeasureBeforeWith Pharmalyze.AI
Full target-setting cycleSeveral working days~3 hours
Brands planned at once1, in sequence6, in parallel
Pharmacy chains coveredSampled106, all of them
Questions answered per sessionA handful, each on request214
Time to an answered questionHours to next day34 s
Analyst involvementExtract per questionReview only
Industry
Pharmacy retail & distribution
Market
Europe
Scope
106 chains · 6 brands
Planning cadence
Quarterly target setting

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