> ## Documentation Index
> Fetch the complete documentation index at: https://complete-docs-x17s80.allmind.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Supply Chain
> Map a company's real economic relationships — who it buys from, sells to, competes with, and partners with — with revenue-exposure percentages to size concentration and second-order risk.
Supply Chain is an interactive map of a company's real economic relationships: who it buys from
(suppliers), who it sells to (customers), who it competes with (competitors), and who it partners with
(joint ventures, R\&D, licensing, distribution, manufacturing, marketing, and equity stakes). For each
relationship it surfaces the revenue exposure, the program or product that ties the two companies together,
when the relationship started, whether it is still active, and which side disclosed it. Use it to trace a
company's true second-order dependencies and concentration risk — not just its sector label.
*Find it under **Equities → Supply Chain** for any company.* Users also call it the "Supply chain map,"
"Relationship network," "Customers & suppliers," or the "Economic dependency map."
## What it is
Supply Chain answers one question: who are this company's real counterparties, and how concentrated is the
exposure to each one. Instead of a sector or industry label, it shows the named companies on the other side
of the money flow — the suppliers it depends on for inputs, the customers that drive its revenue, the rivals
it competes with, and the strategic partners it works with.
It loads on a **Network view** by default — the company in the center, suppliers fanning out to the left
(money out) and customers to the right (money in), each sorted by its share of revenue, with partners and
competitors in sections below. From there you can drill into a full, sortable table for any role, open a detail
card on any counterparty, and push the result into the AI assistant or export it.
The relationship graph is built on **FactSet's Revere supply-chain dataset** — roughly 968,000 relationships
across about 457,000 public, private, and government entities — so the picture reflects disclosed economic
ties rather than a classification model.
## When to use it
Reach for Supply Chain when you need to understand who a company actually depends on, and how much:
* **Size customer- or supplier-concentration risk** — find the names that drive an outsized share of
revenue (for example, a single customer at 25%+ of revenue).
* **Find read-through plays** — if a key customer cuts orders or a key supplier stumbles, trace who else is
hit.
* **Map a competitive set from disclosed market overlap** — build a peer/counterparty list grounded in real
relationships, not just a sector bucket.
* **Discover partnership and licensing exposure** — joint ventures, R\&D collaborations, inbound/outbound
licensing, distribution, and equity stakes.
* **Surface names you would not get from sector classification alone** — the second-order suppliers and
customers behind a company's reported numbers.
It is the go-to surface for second-order exposure analysis and for building a peer or counterparty list
before deeper work.
### When to use something else instead
| If you want… | Go to |
| ------------------------------------------------------------------------- | ----------------------------------------------------------------------------- |
| The company's **own financials and segment revenue** | [Financials & Ratios](/data-viewer/financials) |
| **Forward consensus and analyst forecasts** | [Estimates](/data-viewer/estimates) |
| **Who owns the stock** (holders, institutional ownership) | [Overview](/data-viewer/overview) |
| **Price action and competitive valuation comps** | [Price Analysis](/data-viewer/price-analysis) and [Comps](/data-viewer/comps) |
| The **same relationship question answered across many companies at once** | Grids |
| A **written deliverable** built on the relationship map | Reports |
Supply Chain answers "who are this company's real counterparties and how concentrated is the exposure" — not
"what are its reported numbers."
## How to use it
Open a company in the Data Viewer and select **Supply Chain**. It loads on the **Network view** by
default.
The company sits in the center. **Suppliers** (money out) are on the left and **customers** (money in)
are on the right, each with its share of revenue; **partners** and **competitors** appear in sections
below. The header shows a one-line tally of suppliers, customers, partners, and competitors.
Type into **Filter counterparties** to narrow the map to a specific name, ticker, country, or
relationship type. The header shows how many of the total relationships are currently in view.
Use **Expand** to show up to 80 names per side instead of the default top 10; **Collapse** returns to the
compact view. Partner and competitor sections can be expanded and collapsed the same way.
Switch to the **Suppliers**, **Customers**, **Competitors**, or **Partners** tab (each shows a live
count) to see the full, sortable table for that role.
Use the **Source** filter (All / Company / Counterparty) to separate what the company disclosed itself
from what counterparties disclosed about it. Sort by newest, oldest, name, or % of revenue; filter by
start year ('20+, '22+, '24+); toggle **Active only**; and search across name, ticker, relationship type,
context keywords, and ISIN. On the **Partners** tab, use the **Subtype** dropdown to isolate a specific
partnership kind.
Hover any counterparty to open a detail card with the plain-language relationship, the specific
programs/products involved, start (and end) dates, status, revenue concentration, whether the figure is
disclosed or estimated, and which side filed it.
Use **Add to AI Chat** to send the current network or table into the AI assistant for questions and
workflows, or **Export** to pull the table to CSV, Excel, JSON, or the clipboard.
## What you get
### Views and tabs
| Area | What it is for |
| ----------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Network view** | A single at-a-glance map of the company's economic flows. The company sits in a center panel (name, ticker, country); suppliers fan left under "money out" and customers fan right under "money in," each sorted by revenue share and shown with a **% of Rev** column. Curved connector lines link each counterparty to the company, color-coded by direction, with weight and opacity reflecting whether the relationship is active. By default it shows the top 10 names per side; **Expand** raises this to 80. Two sections below list **Mutual Partnerships** (JV, R\&D, marketing) and **Competitors**. A footer legend explains the color coding and the row markers. |
| **Suppliers tab** | The full list of companies this company buys from (money out). Includes both relationships the company disclosed as its suppliers and inbound relationships where a counterparty disclosed this company as their customer (because that means the counterparty sells to it). A sortable, searchable, exportable table with revenue exposure where disclosed; the tab label carries a live count of distinct supplier relationships. |
| **Customers tab** | The full list of companies this company sells to (money in). Includes both relationships the company disclosed as its customers and inbound relationships where a counterparty disclosed this company as their supplier (they buy from it). This is the primary surface for customer-concentration risk; revenue share is shown where disclosed, with rows around 10%+ reading as a concentration note and 25%+ as concentration risk. |
| **Competitors tab** | Companies competing with this company in one or more shared markets. This is a symmetric relationship that appears regardless of which side disclosed it. Competitors do not carry a revenue-exposure figure, so the Competitors table simply omits the **% of Rev** column (and there is no relationship-type column on this tab). In the network view's competitor section, each row shows its relationship type in place of a revenue percentage. |
| **Partners tab** | Strategic, non-trading relationships: joint ventures, R\&D, licensing, distribution, manufacturing, marketing, and equity stakes. Keeps a **Type** column visible so each partnership kind is identifiable, and adds a **Subtype** dropdown to filter to a specific kind. |
| **Relationship detail card** | Deep context for a single relationship without leaving the page — see below. |
| **Supply Chain reference (legend)** | A built-in glossary so the numbers are read correctly. It explains the four relationship roles, the two disclosure sources (company-disclosed vs counterparty-disclosed, and what each implies for whose revenue the % represents), and the table markers. It states the dataset coverage and notes that a single counterparty can appear in more than one role (for example both supplier and customer). |
### What the detail card shows
Hover any counterparty to open a card with:
* The counterparty's **name, ticker, country, and ISIN** (and, when the matched name differs, the name the
entity was matched as).
* A **plain-language statement of the relationship** from this company's perspective — for example "Supplier
to X," "Customer of X," "Joint venture partner of X," "Contract manufacturer for X," "Equity investor in
X," "Distributor of X's products," or "Licensor to X."
* The **specific programs or products** involved (the context keywords — for example distinct US Government
programs).
* **Start date** and, if the relationship is closed, the **end date**, plus **Active / Closed status**.
* The **revenue concentration figure** with an explicit statement of whose revenue it represents, and whether
it was **disclosed in filings or is a FactSet estimate**.
* **Which side disclosed** the relationship.
### Partner subtypes
The Partners tab's **Subtype** dropdown isolates: All Partners, Joint Venture, Research/Collaboration,
Distribution, Licensee (inbound IP), Licensor (outbound IP), Manufacturing, Marketing, Equity Investee, or
Equity Investor.
### Key capabilities
| Capability | What it does |
| ----------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Relationship network graph** | Visualize suppliers (money out) and customers (money in) around the company, sorted by revenue share, with partners and competitors in sections below. |
| **Role tabs with live counts** | Drill into Suppliers, Customers, Competitors, or Partners as full tables; each tab shows the count of distinct relationships. |
| **Revenue exposure (% of Rev)** | Show the share of the disclosing party's revenue tied to each relationship, used to gauge concentration. |
| **Concentration weighting** | Flag heavy dependencies; rows around 10%+ read as a note and 25%+ as concentration risk, emphasized in the network view. |
| **Disclosure attribution** | Distinguish what the company disclosed itself from what a counterparty disclosed about it, and explain that this changes whose revenue the % refers to. |
| **Source filter** | Slice any table to All sources, Company-disclosed only, or Counterparty-disclosed only. |
| **Program / context detail** | Surface the specific products, contracts, or programs underpinning a relationship (multiple programs under one entity show as x N and are listed in the detail card). |
| **Partner subtype filter** | Isolate JV, R\&D, distribution, inbound/outbound licensing, manufacturing, marketing, or equity relationships. |
| **Counterparty search & filtering** | Filter the network or table by name, ticker, country, relationship type, context keyword, or ISIN. |
| **Sort & time filters** | Sort by recency, name, or revenue share; filter by start year (since 2020 / 2022 / 2024); toggle active-only. |
| **Expand / collapse** | Switch the network between a top-10-per-side compact view and an expanded view of up to 80 per side. |
| **Active / closed status** | Mark each relationship as active or closed (with an end date when closed). |
| **Estimated-value flagging** | Mark revenue figures that are FactSet estimates rather than officially disclosed with an asterisk. |
| **Ticker-collision disambiguation** | Resolve the correct global entity (via the company's ISIN) so an ambiguous ticker does not route to the wrong company on another exchange. |
### What you can take away
* **Interactive supplier/customer network graph** with revenue share per counterparty.
* **Sortable, searchable relationship tables** for Suppliers, Customers, Competitors, and Partners.
* **Per-relationship detail card** — relationship type in plain language, programs/products, dates, status,
revenue concentration, and disclosure source.
* **Counts** of distinct suppliers, customers, competitors, and partners.
* **Export** to CSV, Excel, JSON, or clipboard (tab-separated).
* **Formatted relationship context pushed into AI Chat** for Q\&A and workflows.
## Data & sources
* The relationship graph — relationship types, revenue-exposure percentages, disclosure direction,
start/end dates, context keywords, and active/closed status — is sourced from **FactSet's Revere
supply-chain dataset**. Coverage is roughly **968,000 relationships across about 457,000 public, private,
and government entities**. The FactSet Revere name appears on the no-data screen and in the reference that
accompanies a hand-off to the AI assistant; the network legend itself shows only the relationship and entity
counts.
* **Entity identifiers** (ticker, ISIN, and country) from FactSet Revere are used to identify counterparties;
the ISIN together with the ticker resolves the correct entity for the company you are viewing.
## Tips & best practices
* **Read concentration on the Customers tab.** Sort by **% of revenue (high to low)**: a customer around
10%+ is worth noting, and 25%+ reads as concentration risk. The network view emphasizes these heavy
dependencies visually.
* **Use the Source filter to know whose number you are reading.** "Company" shows what this company named in
its own filings; "Counterparty" shows what others named about it — and that changes whose revenue the % of
Rev represents.
* **Don't be surprised when an entity appears twice.** Distinct contracts or programs under one counterparty
are kept as separate rows (shown as x N) so you can see the program-level breakdown, and a single company
can legitimately be both a supplier and a customer.
* **Expand before you conclude.** The network shows only the top 10 per side by default; expand to 80, or
open the full role tab, before judging how diversified a company's customer or supplier base really is.
* **Watch the asterisk.** A starred figure is a FactSet estimate, not an officially disclosed number — weight
it accordingly.
* **Use the partner subtypes for risk type, not just count.** Isolating inbound licensing or joint ventures
tells you where strategic and IP exposure sits, separate from straight trading relationships.
* **Hand the map to the AI assistant for the "so what."** Push the network or a table into AI Chat and ask
which customers drive the most revenue, or who is exposed if a key counterparty pulls back.
## Limits & things to know
* **The workspace loads currently-active relationships** (up to about 2,000 per direction). In practice
Status reads "Active" for the rows shown; the **Active only** toggle, the closed markers, the dashed
closed-relationship lines, and end ("Until") dates are part of the interface but typically have no closed
rows to act on with the default load.
* **The network shows the top 10 suppliers and top 10 customers per side by default**; **Expand** raises this
to 80 per side, and a "View all" jump to the full tab only appears when a side has more than 80.
* **Competitor relationships do not carry a revenue-exposure percentage.**
* **% of Rev is the disclosing party's revenue share.** For company-disclosed rows it is this company's
revenue tied to the counterparty; for counterparty-disclosed rows it is the counterparty's revenue tied to
this company — not this company's cost of goods. It is shown only where FactSet has a figure; otherwise it
is blank.
* **Some revenue figures are FactSet estimates** (marked with an asterisk) rather than officially disclosed.
* **Coverage is finite** (about 457,000 entities). Smaller or recently-listed issuers may have no data, and
some regional ticker suffixes may not be mapped — in which case the workspace shows a "no data" message.
* **Entities without a real exchange listing** (governments, central banks, privately-held subsidiaries)
still appear, but their placeholder symbols are suppressed so they don't show as misleading tickers — they
simply have no tradeable ticker.
* **Multiple distinct contracts or programs under one counterparty are kept as separate rows** (shown as
x N) rather than merged, so a single entity can appear several times with different programs.
* **The header tally matches the tab counts.** Both group relationships strictly by type. Inside the graph,
however, a directional partner (licensing, manufacturing, distribution, or an equity stake) is drawn within
the supplier or customer flow, so the per-section column counts there are grouped by money flow rather than
by type.
### Availability
There is no feature-specific gating beyond having access to the Equities (Data Viewer). Availability depends
on the company being covered in the FactSet Revere dataset; when it is not, the workspace shows a "no data"
state.
## Works with other features
**Add to AI Chat** sends the current network or relationship table into the AI side chat — with a
self-contained explanation of direction and revenue-exposure semantics — so you can ask questions or
chain into multi-feature workflows.
Download the active table as **CSV**, **Excel**, or **JSON**, or copy it to the clipboard
(tab-separated) for spreadsheets and notes.
"View all" / "See all" controls in the network move you into the matching Suppliers, Customers, Partners,
or Competitors tab; the tables include a **Network** button to jump back.
Take the counterparty list to a Grid to ask the same relationship or exposure question across many
companies at once.
Use the relationship map as factual context for a generated stock research report on the company — the
Equities workspace can kick one off for the ticker you are viewing.
Pull the filings behind a disclosed relationship with Document Search, and collect them into a Data Room
for the project.
This surface has no add-to-watchlist, bookmark, report-generation, or note-taking control of its own;
cross-feature workflows from here run through **Add to AI Chat** and **Export**. The selected sub-tab is
reflected in the page link, so a specific view can be bookmarked or shared.
## Example workflow
**Goal: assess a company's customer-concentration risk and trace the read-through, then package the work.**
1. Open the company in the Data Viewer and go to **Supply Chain**. On the **Network view**, read the
money-in side to see which customers carry the largest share of revenue.
2. Switch to the **Customers** tab and sort by **% of revenue (high to low)**. Flag any customer around 10%+
(a concentration note) and 25%+ (concentration risk). Hover the top names to confirm the program/product,
the start date, the Active status, and whether the figure is disclosed or a **FactSet estimate**.
3. Set the **Source** filter to **Company** to see only what this company disclosed itself, then to
**Counterparty** to see what others disclosed about it — noting how the revenue basis of the % changes.
4. Press **Add to AI Chat** and ask the assistant, "Which customers drive the most revenue, and who is
exposed if the largest one cuts orders?" — answered against the exact table.
5. Take the customer list to a **Grid** to ask the same exposure question across the company's peers, and use
**Document Search** to pull the filings behind the largest disclosed relationships into a **Data Room**.
6. Generate a **Report** on the company grounded in the relationship map, and **Export** the Customers table
to **Excel** for your model.
## FAQ
From **FactSet's Revere supply-chain dataset**, which maps disclosed relationships across roughly 968,000
connections and about 457,000 public, private, and government entities.
It is the revenue exposure of whoever disclosed the relationship. For company-disclosed rows it is this
company's revenue tied to that counterparty; for counterparty-disclosed rows it is the counterparty's
revenue tied to this company. It is not this company's cost of goods.
Relationships are bucketed by economic role from this company's perspective. If a counterparty disclosed
"this company is our customer," it means they sell to this company, so they correctly appear as a supplier
(money out). The "Disclosed by" attribution and the legend explain this.
Distinct contracts or programs under one entity are kept separate so you can see the program-level
breakdown (shown as x N on the counterparty). A single entity can also legitimately be both a supplier and
a customer.
"Company" shows only relationships this company named in its own filings; "Counterparty" shows only
relationships another company named about this one. This matters because it changes whose revenue the "%
of Rev" figure represents.
Look at "% of Rev" on the Customers tab and in the network: a customer at roughly 10%+ of revenue is worth
noting, and 25%+ reads as concentration risk. Sort by "% of revenue (high to low)" to rank dependencies.
Coverage is finite. Smaller or recently-listed issuers may not be indexed, or the ticker may use a
regional suffix that isn't mapped yet. The workspace shows a "no data" message in that case.
Yes. Use **Export** for CSV, Excel, JSON, or clipboard, or **Add to AI Chat** to push the table or network
into the AI side chat for questions and workflows.
The revenue figure is a **FactSet estimate** rather than an officially disclosed number.
The network's header summary matches the tab counts — both group strictly by relationship type. Inside the
graph, though, a directional partner (licensing, manufacturing, distribution, or an equity stake) is shown
within the supplier or customer flow, so the per-section column counts there are grouped by money flow
rather than by type. Both are correct; they answer different questions.
## Getting help
For help using Supply Chain or to talk through a counterparty-exposure workflow, reach AllMind support
through the in-app support option or your account team. For a guided walkthrough, book a session from the
**Help** link in the top navigation.