DataLift
Name what's broken

FMCG

One number for every SKU.

Sell-in, sell-through, and stock should not be three stories.

DACH · FMCG · ERP, trade spend file, e-commerce, three volume exports · 18-week sequence

0 pack from 4 files

Versions of weekly volume

0% from 29%

Trade spend on a SKU

0.0 hrs from 16 hrs

Pack assembly time

0% from all

SKUs with stock older than 48h

After DataLift

What changed after DataLift

Less manual work. Clearer decisions. More revenue you can see, explain and act on.

2 hrs Manual work reduced

2 hrs

from 30 hrs / week

Manual work reduced

Problem
The week ran on exports, copy-paste, and whoever still knew the file.
What we changed
We joined the sources and automated the pack a person should not still be making.
Outcome
Monday work dropped from 30 hours to 2.
$1.2M Revenue connected

$1.2M

fragmented → traceable

Revenue connected

Problem
Revenue was coming in. Nobody could clearly say where all of it came from.
What we changed
Campaign, CRM, and sales joined into one line from acquisition to cash.
Outcome
$1.2M could be traced to the activity that generated it.
$240K Revenue recovered

$240K

overlooked pipeline

Revenue recovered

Problem
Leads existed, then went late, or vanished between tools.
What we changed
We surfaced the opportunities that still needed a person.
Outcome
$240K in overlooked revenue came back into the pipeline.
81% Revenue attribution

81%

from 36%

Revenue attribution

Problem
Only 36% of revenue could be tied to a known source.
What we changed
Marketing, CRM, and sales were joined on the same customer.
Outcome
Attribution coverage reached 81%. Spend had a destination.
Live Reporting speed

Live

from multi-day packs

Reporting speed

Problem
The room waited on a pack that was already old when it arrived.
What we changed
One view, fed from the systems that already held the truth.
Outcome
Leaders see the week while there is still time to act.
1 flow Disconnected systems

1 flow

from isolated tools

Disconnected systems

Problem
CRM, ads, billing, and ops each told a different story.
What we changed
We connected the stack you already pay for. Nothing new to learn.
Outcome
One connected data flow. The Friday file stopped being the system of record.

What was going on

A mid-sized FMCG or operational brand sells through retail, wholesale, and digital. ERP holds orders and stock. E-commerce has its own performance file. Trade spend lives in finance or in a spreadsheet. Promotions are coded late, or not at all. The leadership pack is assembled by copy and paste.

Who feels it: Commercial lead, operations or supply, finance, and the analyst who currently builds the pack.

The leak

Sales celebrates a shipment. Operations sees a warehouse problem. Finance sees a promotion that was never attached to a SKU or a customer. Channel and promotion performance cannot be judged against contribution in the week it matters.

Why it happened

Retail, wholesale, and digital do not share product and customer language. Trade spend does not attach cleanly. Demand and supply planning sit on a hero spreadsheet. Reporting was layered on top of unresolved definitions of volume, stock, and margin.

How DataLift investigates. We treat commercial, supply, and finance as one operating picture. The work is definitions, joins, and a reporting cadence that matches how the business actually buys, makes, and sells. We do not start with a generic retail dashboard.

What we build

  1. 01 A short list of objects that must be right: SKU, customer, order, stock, promotion.
  2. 02 Shared product and customer language across retail, wholesale, and digital.
  3. 03 Promotion and trade spend attached to SKU and customer where the data can support it, with gaps stated.
  4. 04 A commercial reporting cadence that is not a weekend reconstruction.
  5. 05 A decision on which spreadsheet model is judgement and which is an unofficial warehouse.

How data moves

  1. 01 Orders

    ERP or order system is authoritative for sell-in.

  2. 02 Stock and supply

    Availability is a current fact, not last week’s export.

  3. 03 Channels

    Retail, wholesale, and digital report in the same SKU language.

  4. 04 Promotions

    Trade spend and campaigns attach where a code exists, and are marked unknown where they do not.

Before

  • Three versions of volume, depending on who exported.
  • Promotions judged on activity, not contribution.
  • Stock reported too late to steer.
  • Trade spend that cannot be found on a SKU.
  • A leadership pack that exists because one person did not take Monday off.

After

  • Shared SKU and customer language.
  • Stock and service levels in the same conversation as sell-in.
  • Promotions readable against volume and margin, with gaps honest.
  • A pack that refreshes from the source of truth.
  • Channel arguments that can point at a definition.

What this is worth

  • Fewer competing versions

    Volume, stock, and margin stop being personal files.

  • Faster commercial reporting

    The pack is not a reconstruction project.

  • Clearer promotion judgement

    Spend is attached where it can be, and marked unknown where it cannot.

A view you can trust

Weekly commercial and supply picture

Volume

Source: ERP + channels

  • Sell-in defined
  • Sell-through defined
  • Returns defined

Availability

Source: Stock

  • On hand defined
  • Service risk defined
  • Overstock defined

Investment

Source: Trade + ads

  • Attached spend defined
  • Uncoded promotions defined
  • Channel mix defined

A shared language for SKU, customer, and promotion. Not a claim about lift from a named brand.

Related

If the leak looks familiar, write.

We will say whether a sequence like this is the first job.

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