A donut breakdown of GL postings by the SAP module that generated them, the shape of your financial automation.
At a glance
Every line in the S/4HANA Cloud Universal Journal carries the module that created it: SD (Sales and Distribution) for billing-driven revenue, MM (Materials Management) for goods movements and vendor invoices, PP (Production Planning) for manufacturing postings, and FI (Financial Accounting) for direct journal entries including manual postings. This card draws that mix as a donut over the last 30 days. The shape tells a story: a rising SD share means your ecommerce integration is scaling and posting automatically, while a rising FI manual share means people are typing entries that should be automated, which is a controls and automation gap worth investigating.
| What it counts | The distribution of journal entries across source modules (SD, MM, FI, PP, and others such as AA asset accounting) over the trailing 30 days, shown as a share of total postings. |
| What it reveals | The balance between automated, integration-driven postings (SD, MM, PP) and direct FI postings. A healthy commerce-led business is SD-heavy and automated; a high FI manual share is a red flag. |
| Data source | SAP S/4HANA Cloud Universal Journal (ACDOCA / BKPF), reading the source-module and transaction-origin attributes on each document. |
| Company Code scope | Respects the selected Company Code filter; rolls up every Company Code visible to the connected SAP business user / API role by default. |
| Real-time vs batch | Aggregated over the rolling 30-day window and refreshed on each connector poll. |
| Time window | 30D (trailing 30 days) |
| Alert trigger | Informational, no threshold |
| Roles | owner, finance |
Calculation
Calculated automatically from your SAP data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading.Worked example
A growing commerce business running SAP S/4HANA Cloud, comparing the journal mix across two 30-day windows: one ending 31 Mar 26 and one ending 31 May 26, after a storefront integration go-live in April.| Source module | Share (30D to 31 Mar 26) | Share (30D to 31 May 26) | Read |
|---|---|---|---|
| SD (Sales and Distribution) | 38% | 61% | Ecom integration scaling, automation working |
| MM (Materials Management) | 22% | 19% | Steady goods-movement and vendor-invoice volume |
| FI (manual and direct) | 31% | 14% | Manual share falling, controls improving |
| PP (Production Planning) | 6% | 4% | Stable manufacturing postings |
| Other (AA, etc.) | 3% | 2% | Background |
| Total postings | 100% | 100% |
- The SD share jumped from 38% to 61% after the integration go-live. This is the signal you want to see when a storefront connection scales: more revenue is posting automatically from billing documents instead of being keyed by hand. The donut visibly fills with SD. If you have just connected a commerce platform and the SD share does not move, the integration may not be flowing as expected, which is worth checking against the IDoc and missing-document cards.
- The FI manual share fell from 31% to 14%. Before the integration, nearly a third of postings were direct FI entries, many of them manual catch-ups for sales that the system did not capture automatically. After go-live, automation absorbed most of that work and the manual share dropped by more than half. A falling FI share alongside a rising SD share is the textbook shape of a maturing, well-controlled finance function.
- A spike in the FI manual share is the warning to act on. This card has no alert threshold, but the FI slice is the one to watch. If FI manual postings climb instead of fall, it usually means an integration broke (so people are keying entries to compensate), a process gap opened, or controls slipped. A rising manual share is also a SOX-style audit concern because manual postings carry higher error and override risk.
- MM and PP shares are mostly structural. Goods movements and manufacturing postings tend to track operational volume, not automation maturity, so their shares move slowly. A sudden MM spike can correlate with a goods-movement problem (for example the double-posting that drives negative on-hand), so a jump there is worth a look even though the card is informational.
Sibling cards merchants should reference together
The source-module mix is a context card; it explains the shape behind several sharper signals. Pair it with these.| Card | Why pair it with Journals by Source Module |
|---|---|
| Manual Journals (FB50/FB60) as % of Total | Zooms into the FI manual slice with a hard threshold. This card shows the mix; that one alerts when manual gets too high. |
| Journal Entries Failing to Post (idoc error queue) | A falling SD share can mean sales IDocs are failing rather than posting. Read together to confirm. |
| Idoc Error Queue Depth (last 24h) | The integration-health gauge behind the SD share. A growing error queue caps SD growth. |
| Journal Imbalances (debit != credit) | Tells you which source module is generating broken postings when imbalances appear. |
| Open / Unposted Journal Entries | A rising manual share often comes with a parked-document backlog. |
| SAP S/4HANA Health Score | The composite roll-up. Automation maturity (high SD, low manual FI) feeds the score. |
Reconciling against SAP
Where to look in S/4HANA Cloud: The closest native equivalents inside the SAP Fiori launchpad are:Display Journal Entries / Manage Journal Entries grouped or filtered by source and transaction origin (conceptually transaction FB03 for individual documents) Journal Entry Analyzer for the analytical breakdown by document type and origin Embedded Analytics: the journal-line CDS query grouped by the source-module / transaction-origin attribute over the period Compact Document Journal for a posting-source overview across a date rangeDirect link template:
https://my{tenant}.s4hana.cloud.sap/sap/bc/ui2/flp#JournalEntry-displayList
To reproduce the donut, run the journal-entry list for the same 30-day posting-date range and group by source module or transaction origin, then take each module’s count as a share of the total. SD-originated documents come from billing, MM from goods movements and logistics invoice verification, PP from production confirmations, and FI from direct postings including the manual FB50 / FB60 transactions. The shares should agree with the card within rounding and any difference in how borderline document types are classified.
Common mistakes when comparing against SAP’s own reports:
- Counting by amount instead of by document count. The donut is a count-of-postings share by default. A value-weighted view will look different because a few large FI postings can dominate by amount while being rare by count.
- Misclassifying logistics invoice verification. Vendor invoices via logistics invoice verification originate in MM even though they hit FI accounts. Grouping by GL account rather than by source module will misattribute them.
- Ignoring reversals and clearing. Reversal and clearing documents inflate the FI count if included. Decide whether to count them consistently on both sides.
| Reason | Direction | Why |
|---|---|---|
| Count vs value weighting | Either | The card weights by document count. A value-weighted report shifts the mix toward whichever module carries the largest amounts. |
| Source-module classification | Either | Borderline document types (logistics invoice verification, intercompany) can be attributed to different modules depending on the grouping field. |
| Reversal and clearing inclusion | Either | Whether technical FI documents (reversals, clearings) are counted affects the FI share. |
| Company Code scope | Either | Running the SAP report at a different Company Code scope than the dashboard filter changes the mix. |