Headcount DashboardFP&A Headcount Console
▤ Month end: Jun 30, 2026

Headcount Dashboard

Everyone at eBay — 12,300 people, $2.58B a year. One thing here does not reconcile and is flagged red; everything else was checked and does. All figures are FTE unless the card says headcount.

Current headcount
12,300
993 contractors, costed apart
▲ vs plan 12,010 heads-basis
Workforce FTE
11,91411,926
a range — 40 engineers in dispute
the number the tool will stand behind
Variance to plan
−96 to −84 FTE
vs approved plan 12,010
1 org over · 5 under
Salary run-rate
$2.58B
$210k/head, fully loaded
▼ derived from the rate card
Open requisitions
244
across 5 role categories
a backfill is not growth
Attrition (YTD)
3.1%
383 leavers, year to date
a flow figure — the toggle moves it
Contractors
993
7% of the workforce
costed apart from FTE
Headcount by business unit Actual vs approved plan · sorted by variance
ActualPlanVarVar %
Advertising & Marketing 1,1191,140 −21−1.8%
People & Workplaces 876890 −14−1.6%
Marketplace & Categories 2,3832,420 −37−1.5%
Technology & Product disputed 3,4493,500 −51 to −39−1.5 to −1.1%
Finance, Legal & G&A 1,2651,280 −15−1.2%
Customer Service & Operations 2,8222,780 +42+1.5%
On plan (±2%)Watch (2–5%)At risk (>5%)
Headcount by leader Top by variance · C-suite named, all others coded
LeaderActualPlanVarVar %
MR Mazen RawashdehSVP & Chief Technology Officer · E-10002 3,4493,500 −51 to −39 -1.5%
JS Jordan SweetnamChief Commercial Officer · E-10003 2,3832,420 −37 -1.5%
JL Julie LoegerSVP, Chief Growth Officer · E-10005 1,1191,140 −21 -1.8%
PA Peggy AlfordSVP, Chief Financial Officer · E-10006 1,2651,280 −15 -1.2%
CB Cornelius BooneSVP, Chief People Officer · E-10007 876890 −14 -1.6%
JI Jamie IannoneCEO — directly oversees Ops (no COO) · E-10004 2,8222,780 +42 +1.5%
SW Samantha WellingtonSVP, Chief Legal Officer & General Counsel within Finance, Legal & G&A
Leaders are the seven executives eBay lists publicly (ebayinc.com/company/our-leaders), mapped to illustrative org units; the figures are demo data. eBay has no COO, so Customer Service & Operations sits under the CEO. Legal & Governance is counted within Finance, Legal & G&A, so that row carries no separate headcount.
Attrition by organization Leavers and rate · switches with the YTD / QTD toggle above
OrganizationLeaversRate
Technology & Product 123 3.4%
Customer Service & Operations 102 3.5%
Marketplace & Categories 72 2.9%
Advertising & Marketing 34 3.0%
Finance, Legal & G&A 32 2.5%
People & Workplaces 20 2.2%
Company 383 3.1%
Actual vs the three plans
Actual FTE11,914–11,926
Approved plan12,010
Forecast 112,016
Forecast 212,037
By level
< 211,49212%
22–257,46661%
26–282,89424%
Exec4484%
Total12,300100%
By region
Americas7,65762%
APAC3,22626%
EMEA1,41712%
US of that7,49661%
Movement
+244
Open requisitions stock
−383
Known leavers (YTD)
993
Contractors stock
Top variances
Advertising & Marketing −21 -1.8%
People & Workplaces −14 -1.6%
Marketplace & Categories −37 -1.5%
Customer Service & Operations +42 +1.5%
Technology & Product −51 -1.5%
Finance, Legal & G&A −15 -1.2%
Key insights Every line is a check that ran — not advice the model wrote
!
Two systems disagree about 40 engineers. They owe 70% to their own roadmap; one system books them at 60%, another at 30% — the higher reading is 130%, over-allocated. Worth 12 FTE / $2.6M. The tool publishes the range and refuses to average them.
Everything else reconciles. 2,786 checks pass: every total re-derived from its rows, every team counted twice (by role and by location) and made to agree, 4,858 allocation cells tested for over-commitment. The 40 above are the only rows over 100%.
Cost is not headcount. Customer Service is 24% of the people and 12% of the cost; 55% of it is APAC. A support seat in Manila is $38k; an engineer in San Jose is $320k. Report headcount alone and the number is wrong by 2.8×.
Source: HRIS · project system · team tracker — all read 06:00 ET today. Rate card effective 1 Jul 2026. The two systems that disagree were both read this morning: a live disagreement, not a stale copy. · Req Room v2.1

Slice it any way you need

A fixed hierarchy only answers the questions its author thought of. How many engineers are on this project, at which site, at what spend? leads with role, not with org — so choose your own hierarchy. Every number is summed from the same 4,858 rows the org tree is built from, so a slice can never disagree with the total.

Start from
Group by
Filter
GroupPeopleFTE Cost / yearShare of cost

Who rolls up to whom

Organization → director → team → the roles inside it, and where those people sit. Every team is broken down twice — once by role and once by location. Two independent counts of the same people; they must come to the same total, or one of them is wrong.

Pick an organization

Headcount by leader

Every leader's organisation on one screen — business unit, seniority band, region and location, with a hiring-velocity read that moves with the YTD/QTD toggle. Pick a leader to drill in; everything below re-scopes to their org. Every figure is a sum over the same 4,858 leaf cells the org tree is built from, so a leader's numbers can never disagree with the company total.

Select a leader to drill in — everything below updates

Workforce overview
Headcount
12,300
people on the books
Projected headcount
12,402
incl. 102 confirmed starts
Gap to target
-290
290 above plan of 12,010
Workforce FTE
11,914
allocated full-time equiv.
Annual spend
$2.58B
fully-loaded run-rate
Hiring velocity
Open requisitions
244
approved, unfilled
New hires · YTD
627
joined year to date
Net change · YTD
+244
hires − leavers
Confirmed starts
102
offers signed, not yet started
Attrition · YTD
3.1%
383 leavers · YTD
By business unittile size = headcount · colour = leader · 18 units · click a card to drill in
Global CS — Americas1,180
Category Management1,020
Seller Experience950
Global CS — EMEA880
Buyer Experience & Search840
Global CS — APAC840
Payments & Risk780
Shipping, Returns & Logistics740
Seller Ecosystem690
Advertising & Promoted Listings620
Trust & Safety560
Talent & People Ops560
FP&A & Controllership540
Brand & Growth Marketing530
AI & Platform470
Legal & Compliance430
Workplaces & Real Estate340
Corporate Development & G&A330
Global CS — Americas1,18010%
Category Management1,0208%
Seller Experience9508%
Global CS — EMEA8807%
Buyer Experience & Search8407%
Global CS — APAC8407%
Payments & Risk7806%
Shipping, Returns & Logistics7406%
Seller Ecosystem6906%
Advertising & Promoted Listings6205%
Trust & Safety5605%
Talent & People Ops5605%
FP&A & Controllership5404%
Brand & Growth Marketing5304%
AI & Platform4704%
Legal & Compliance4303%
Workplaces & Real Estate3403%
Corporate Development & G&A3303%
Colour = leaderMazen RawashdehJordan SweetnamJamie IannoneJulie LoegerPeggy AlfordCornelius Boone
By level bandeBay job levels
< 21
1,492head1,489fte$193Mspend
22–25
7,466head7,136fte$1.49Bspend
26–28
2,894head2,846fte$802Mspend
Exec
448head443fte$98Mspend
Level mix by regionheadcount by seniority band
02,0004,0006,0008,000Americas · < 21 — 857 heads · 11% of region857Americas · 22–25 — 4,799 heads · 63% of region4,799Americas · 26–28 — 1,737 heads · 23% of region1,737Americas · Exec — 264 heads · 3% of region7,657AmericasAPAC · < 21 — 399 heads · 12% of regionAPAC · 22–25 — 1,896 heads · 59% of region1,896APAC · 26–28 — 794 heads · 25% of region794APAC · Exec — 137 heads · 4% of region3,226APACEMEA · < 21 — 236 heads · 17% of regionEMEA · 22–25 — 771 heads · 54% of region771EMEA · 26–28 — 363 heads · 26% of regionEMEA · Exec — 47 heads · 3% of region1,417EMEA
< 2122–2526–28Exec
By regionheadcount & share
Americas · 62% — 7,657 heads · 7,383 FTE · $2.07BAPAC · 26% — 3,226 heads · 3,123 FTE · $252MEMEA · 12% — 1,417 heads · 1,408 FTE · $264M 12,300people
Americas7,65762%
APAC3,22626%
EMEA1,41712%
By location11 sites
San Jose, US
3,450head3,273fte$1.10Bspend
Austin, US
1,769head1,733fte$402Mspend
Salt Lake City, US
1,409head1,376fte$273Mspend
Bangalore, IN
1,404head1,368fte$134Mspend
Manila, PH
1,267head1,207fte$49Mspend
New York, US
868head842fte$257Mspend
Dublin, IE
638head636fte$114Mspend
Shanghai, CN
555head548fte$70Mspend
Berlin, DE
390head389fte$66Mspend
London, UK
389head383fte$84Mspend
Toronto, CA
161head159fte$33Mspend
AmericasAPACEMEA
Workforce overview
Headcount
3,600
people on the books
Projected headcount
3,641
incl. 41 confirmed starts
Gap to target
-100
100 above plan of 3,500
Workforce FTE
3,449
allocated full-time equiv.
Annual spend
$847M
fully-loaded run-rate
Hiring velocity
Open requisitions
97
approved, unfilled
New hires · YTD
220
joined year to date
Net change · YTD
+97
hires − leavers
Confirmed starts
41
offers signed, not yet started
Attrition · YTD
3.4%
123 leavers · YTD
By business unitbar length = headcount · 5 units
Seller Experience
950head871fte$225Mspend
Buyer Experience & Search
840head818fte$197Mspend
Payments & Risk
780head758fte$186Mspend
Trust & Safety
560head545fte$130Mspend
AI & Platform
470head457fte$109Mspend
By level bandeBay job levels
< 21
419head416fte$60Mspend
22–25
2,237head2,116fte$496Mspend
26–28
818head795fte$256Mspend
Exec
126head122fte$35Mspend
Level mix by regionheadcount by seniority band
06251,2501,8752,500Americas · < 21 — 260 heads · 11% of region260Americas · 22–25 — 1,520 heads · 63% of region1,520Americas · 26–28 — 542 heads · 22% of region542Americas · Exec — 88 heads · 4% of region2,410AmericasAPAC · < 21 — 109 heads · 11% of regionAPAC · 22–25 — 598 heads · 63% of region598APAC · 26–28 — 214 heads · 23% of region214APAC · Exec — 27 heads · 3% of region948APACEMEA · < 21 — 50 heads · 21% of regionEMEA · 22–25 — 119 heads · 49% of regionEMEA · 26–28 — 62 heads · 26% of regionEMEA · Exec — 11 heads · 5% of region242EMEA
< 2122–2526–28Exec
By regionheadcount & share
Americas · 67% — 2,410 heads · 2,297 FTE · $700MAPAC · 26% — 948 heads · 911 FTE · $102MEMEA · 7% — 242 heads · 241 FTE · $46M 3,600people
Americas2,41067%
APAC94826%
EMEA2427%
By location9 sites
San Jose, US
1,493head1,406fte$489Mspend
Bangalore, IN
761head729fte$77Mspend
Austin, US
482head469fte$120Mspend
Salt Lake City, US
309head298fte$65Mspend
Shanghai, CN
187head182fte$25Mspend
Dublin, IE
139head138fte$27Mspend
Toronto, CA
126head124fte$26Mspend
Berlin, DE
82head82fte$14Mspend
London, UK
21head21fte$4.9Mspend
AmericasAPACEMEA
Workforce overview
Headcount
2,450
people on the books
Projected headcount
2,468
incl. 18 confirmed starts
Gap to target
-30
30 above plan of 2,420
Workforce FTE
2,383
allocated full-time equiv.
Annual spend
$590M
fully-loaded run-rate
Hiring velocity
Open requisitions
44
approved, unfilled
New hires · YTD
116
joined year to date
Net change · YTD
+44
hires − leavers
Confirmed starts
18
offers signed, not yet started
Attrition · YTD
2.9%
72 leavers · YTD
By business unitbar length = headcount · 3 units
Category Management
1,020head992fte$251Mspend
Shipping, Returns & Logistics
740head720fte$180Mspend
Seller Ecosystem
690head671fte$159Mspend
By level bandeBay job levels
< 21
306head306fte$44Mspend
22–25
1,486head1,419fte$336Mspend
26–28
598head598fte$191Mspend
Exec
60head60fte$18Mspend
Level mix by regionheadcount by seniority band
05001,0001,5002,000Americas · < 21 — 185 heads · 11% of region185Americas · 22–25 — 1,027 heads · 62% of region1,027Americas · 26–28 — 396 heads · 24% of region396Americas · Exec — 43 heads · 3% of region1,651AmericasAPAC · < 21 — 59 heads · 16% of regionAPAC · 22–25 — 212 heads · 57% of region212APAC · 26–28 — 92 heads · 25% of regionAPAC · Exec — 9 heads · 2% of region372APACEMEA · < 21 — 62 heads · 15% of regionEMEA · 22–25 — 247 heads · 58% of region247EMEA · 26–28 — 110 heads · 26% of regionEMEA · Exec — 8 heads · 2% of region427EMEA
< 2122–2526–28Exec
By regionheadcount & share
Americas · 67% — 1,651 heads · 1,589 FTE · $470MAPAC · 15% — 372 heads · 370 FTE · $40MEMEA · 17% — 427 heads · 424 FTE · $79M 2,450people
Americas1,65167%
APAC37215%
EMEA42717%
By location8 sites
San Jose, US
887head840fte$268Mspend
New York, US
453head443fte$131Mspend
Austin, US
311head306fte$71Mspend
Shanghai, CN
222head220fte$27Mspend
Berlin, DE
153head152fte$26Mspend
Bangalore, IN
150head150fte$13Mspend
London, UK
143head141fte$30Mspend
Dublin, IE
131head131fte$23Mspend
AmericasAPACEMEA
Workforce overview
Headcount
2,900
people on the books
Projected headcount
2,920
incl. 20 confirmed starts
Gap to target
-120
120 above plan of 2,780
Workforce FTE
2,822
allocated full-time equiv.
Annual spend
$312M
fully-loaded run-rate
Hiring velocity
Open requisitions
48
approved, unfilled
New hires · YTD
150
joined year to date
Net change · YTD
+48
hires − leavers
Confirmed starts
20
offers signed, not yet started
Attrition · YTD
3.5%
102 leavers · YTD
By business unitbar length = headcount · 3 units
Global CS — Americas
1,180head1,148fte$132Mspend
Global CS — EMEA
880head856fte$95Mspend
Global CS — APAC
840head818fte$85Mspend
By level bandeBay job levels
< 21
343head343fte$24Mspend
22–25
1,675head1,618fte$168Mspend
26–28
703head683fte$97Mspend
Exec
179head178fte$23Mspend
Level mix by regionheadcount by seniority band
05001,0001,5002,000Americas · < 21 — 128 heads · 12% of regionAmericas · 22–25 — 649 heads · 60% of region649Americas · 26–28 — 233 heads · 21% of region233Americas · Exec — 79 heads · 7% of region1,089AmericasAPAC · < 21 — 187 heads · 12% of region187APAC · 22–25 — 919 heads · 57% of region919APAC · 26–28 — 409 heads · 26% of region409APAC · Exec — 87 heads · 5% of region1,602APACEMEA · < 21 — 28 heads · 13% of regionEMEA · 22–25 — 107 heads · 51% of regionEMEA · 26–28 — 61 heads · 29% of regionEMEA · Exec — 13 heads · 6% of region209EMEA
< 2122–2526–28Exec
By regionheadcount & share
Americas · 38% — 1,089 heads · 1,072 FTE · $198MAPAC · 55% — 1,602 heads · 1,541 FTE · $81MEMEA · 7% — 209 heads · 209 FTE · $33M 2,900people
Americas1,08938%
APAC1,60255%
EMEA2097%
By location7 sites
Manila, PH
1,226head1,166fte$47Mspend
Salt Lake City, US
615head603fte$105Mspend
Austin, US
474head469fte$92Mspend
Bangalore, IN
279head278fte$22Mspend
Dublin, IE
154head154fte$24Mspend
Shanghai, CN
97head97fte$12Mspend
Berlin, DE
55head55fte$9.0Mspend
AmericasAPACEMEA
Workforce overview
Headcount
1,150
people on the books
Projected headcount
1,159
incl. 9 confirmed starts
Gap to target
-10
10 above plan of 1,140
Workforce FTE
1,119
allocated full-time equiv.
Annual spend
$306M
fully-loaded run-rate
Hiring velocity
Open requisitions
22
approved, unfilled
New hires · YTD
56
joined year to date
Net change · YTD
+22
hires − leavers
Confirmed starts
9
offers signed, not yet started
Attrition · YTD
3.0%
34 leavers · YTD
By business unitbar length = headcount · 2 units
Advertising & Promoted Listings
620head604fte$165Mspend
Brand & Growth Marketing
530head515fte$140Mspend
By level bandeBay job levels
< 21
151head151fte$25Mspend
22–25
688head660fte$175Mspend
26–28
287head284fte$99Mspend
Exec
24head24fte$7.6Mspend
Level mix by regionheadcount by seniority band
0213425638850Americas · < 21 — 99 heads · 12% of region99Americas · 22–25 — 513 heads · 64% of region513Americas · 26–28 — 179 heads · 22% of region179Americas · Exec — 14 heads · 2% of region805AmericasAPAC · < 21 — 7 heads · 14% of regionAPAC · 22–25 — 26 heads · 53% of regionAPAC · 26–28 — 14 heads · 29% of regionAPAC · Exec — 2 heads · 4% of region49APACEMEA · < 21 — 45 heads · 15% of regionEMEA · 22–25 — 149 heads · 50% of region149EMEA · 26–28 — 94 heads · 32% of region94EMEA · Exec — 8 heads · 3% of region296EMEA
< 2122–2526–28Exec
By regionheadcount & share
Americas · 70% — 805 heads · 778 FTE · $238MAPAC · 4% — 49 heads · 49 FTE · $6.2MEMEA · 26% — 296 heads · 292 FTE · $61M 1,150people
Americas80570%
APAC494%
EMEA29626%
By location7 sites
New York, US
415head399fte$125Mspend
San Jose, US
307head297fte$94Mspend
London, UK
154head151fte$34Mspend
Austin, US
83head82fte$19Mspend
Dublin, IE
76head75fte$14Mspend
Berlin, DE
66head66fte$12Mspend
Shanghai, CN
49head49fte$6.2Mspend
AmericasAPACEMEA
Workforce overview
Headcount
1,300
people on the books
Projected headcount
1,309
incl. 9 confirmed starts
Gap to target
-20
20 above plan of 1,280
Workforce FTE
1,265
allocated full-time equiv.
Annual spend
$340M
fully-loaded run-rate
Hiring velocity
Open requisitions
21
approved, unfilled
New hires · YTD
53
joined year to date
Net change · YTD
+21
hires − leavers
Confirmed starts
9
offers signed, not yet started
Attrition · YTD
2.5%
32 leavers · YTD
By business unitbar length = headcount · 3 units
FP&A & Controllership
540head526fte$142Mspend
Legal & Compliance
430head418fte$113Mspend
Corporate Development & G&A
330head321fte$84Mspend
By level bandeBay job levels
< 21
161head161fte$25Mspend
22–25
817head782fte$201Mspend
26–28
286head286fte$105Mspend
Exec
36head36fte$8.6Mspend
Level mix by regionheadcount by seniority band
03757501,1251,500Americas · < 21 — 112 heads · 11% of region112Americas · 22–25 — 652 heads · 63% of region652Americas · 26–28 — 240 heads · 23% of region240Americas · Exec — 28 heads · 3% of region1,032AmericasAPAC · < 21 — 18 heads · 15% of regionAPAC · 22–25 — 66 heads · 55% of regionAPAC · 26–28 — 27 heads · 23% of regionAPAC · Exec — 8 heads · 7% of region119APACEMEA · < 21 — 31 heads · 21% of regionEMEA · 22–25 — 99 heads · 66% of regionEMEA · 26–28 — 19 heads · 13% of region149EMEA
< 2122–2526–28Exec
By regionheadcount & share
Americas · 79% — 1,032 heads · 1,000 FTE · $297MAPAC · 9% — 119 heads · 117 FTE · $13MEMEA · 11% — 149 heads · 148 FTE · $30M 1,300people
Americas1,03279%
APAC1199%
EMEA14911%
By location7 sites
San Jose, US
470head450fte$165Mspend
Salt Lake City, US
322head314fte$72Mspend
Austin, US
205head201fte$53Mspend
Bangalore, IN
119head117fte$13Mspend
Dublin, IE
78head78fte$15Mspend
London, UK
71head70fte$14Mspend
Toronto, CA
35head35fte$7.4Mspend
AmericasAPACEMEA
Workforce overview
Headcount
900
people on the books
Projected headcount
905
incl. 5 confirmed starts
Gap to target
-10
10 above plan of 890
Workforce FTE
876
allocated full-time equiv.
Annual spend
$189M
fully-loaded run-rate
Hiring velocity
Open requisitions
12
approved, unfilled
New hires · YTD
32
joined year to date
Net change · YTD
+12
hires − leavers
Confirmed starts
5
offers signed, not yet started
Attrition · YTD
2.2%
20 leavers · YTD
By business unitbar length = headcount · 2 units
Talent & People Ops
560head545fte$118Mspend
Workplaces & Real Estate
340head331fte$71Mspend
By level bandeBay job levels
< 21
112head112fte$14Mspend
22–25
563head541fte$114Mspend
26–28
202head200fte$55Mspend
Exec
23head23fte$5.3Mspend
Level mix by regionheadcount by seniority band
0175350525700Americas · < 21 — 73 heads · 11% of region73Americas · 22–25 — 438 heads · 65% of region438Americas · 26–28 — 147 heads · 22% of region147Americas · Exec — 12 heads · 2% of region670AmericasAPAC · < 21 — 19 heads · 14% of regionAPAC · 22–25 — 75 heads · 55% of region75APAC · 26–28 — 38 heads · 28% of regionAPAC · Exec — 4 heads · 3% of region136APACEMEA · < 21 — 20 heads · 21% of regionEMEA · 22–25 — 50 heads · 53% of region50EMEA · 26–28 — 17 heads · 18% of regionEMEA · Exec — 7 heads · 7% of region94EMEA
< 2122–2526–28Exec
By regionheadcount & share
Americas · 74% — 670 heads · 647 FTE · $164MAPAC · 15% — 136 heads · 135 FTE · $11MEMEA · 10% — 94 heads · 94 FTE · $15M 900people
Americas67074%
APAC13615%
EMEA9410%
By location7 sites
San Jose, US
293head280fte$87Mspend
Austin, US
214head206fte$46Mspend
Salt Lake City, US
163head161fte$31Mspend
Bangalore, IN
95head94fte$8.8Mspend
Dublin, IE
60head60fte$9.9Mspend
Manila, PH
41head41fte$1.9Mspend
Berlin, DE
34head34fte$4.9Mspend
AmericasAPACEMEA
Chart forms are matched to each panel's job (treemap for part-to-whole, donut for share, stacked columns for composition); the amber is toned so the palette clears the dark-mode contrast band. Leaders are the seven executives eBay lists publicly, mapped to illustrative org units; figures are demo data that foot to 12,300.

Where the money goes

Headcount and cost are not the same shape. Report one and you have told the CEO something that is wrong by a factor of 2.8, depending on which organization they ask about.

Cost by organization
OrganizationPeopleShare of peopleCost / yearShare of costCost / head
Technology & Product costs more than its size 3,60029%$847M$850M33%$235k
Marketplace & Categories 2,45020%$590M23%$241k
Finance, Legal & G&A 1,30011%$340M13%$261k
Customer Service & Operations costs less than its size 2,90024%$312M12%$108k
Advertising & Marketing 1,1509%$306M12%$266k
People & Workplaces 9007%$189M7%$210k
Company12,300100%$2.58B100%$210k
Cost by site — the reason the orgs differ
SiteFTEHeadcountCountryCost / yearCost / headShare of cost
◍ San Jose, US Americas3,2733,450United States$1103M$320k43%
◍ Austin, US Americas1,7331,769United States$402M$227k16%
◍ Salt Lake City, US Americas1,3761,409United States$273M$194k11%
◍ Bangalore, IN APAC1,3681,404India$134M$95k5%
◍ Manila, PH APAC1,2071,267Philippines$49M$38k2%
◍ New York, US Americas842868United States$257M$296k10%
◍ Dublin, IE EMEA636638Ireland$114M$178k4%
◍ Shanghai, CN APAC548555China$70M$126k3%
◍ Berlin, DE EMEA389390Germany$66M$170k3%
◍ London, UK EMEA383389United Kingdom$84M$216k3%
◍ Toronto, CA Americas159161Canada$33M$205k1%
All sites11,91412,30011 sites$2584M$210k100%
The variance bridge concept — this engine isn't built yet
Plan said 790. The actual is 758. The tool must explain the whole 32-FTE gap, and every reason for it — the drivers sum to the gap exactly, or the tool reports that it cannot decompose it. It never plugs a residual to make the arithmetic close.
Reason the plan and the actual differFTEKind
Leavers not yet backfilled−38timing
Roles open past their start date−24timing
Backfills not started yet−11timing
Contractor conversions+41permanent
Unexplained0residual
Payments & Risk: plan 790 → actual 758-32reconciles exactly

Which plan are you measuring against?

The approved plan, and the two forecasts that have replaced it since. The same organization is over plan against one and under against another — so a tool that shows you a single "variance" without saying which plan it used is not telling you anything.

Actual against all three plans
OrganizationActual FTEApproved planvs AOPForecast 1vs F1Forecast 2vs F2
Technology & Product3,4493,4613,500−513,520−713,545−96
Marketplace & Categories2,3832,420−372,405−222,395−12
Customer Service & Operations2,8222,780+422,800+222,8220
Advertising & Marketing1,1191,140−211,132−131,125−6
Finance, Legal & G&A1,2651,280−151,274−91,270−5
People & Workplaces876890−14885−9880−4
Company — Jamie Iannone CEO E-1000111,91411,92612,010−9612,016−10212,037−123

Customer Service is the whole point. It is +42 FTE against the approved plan — the only organization over. Against forecast 2 it is exactly on plan. Nothing about the organization changed; only the baseline did. Whoever picks the baseline picks the answer, which is why this tool always names it.

Open roles, and the people who left

244 open requisitions and 383 known leavers. They are counted apart, deliberately: a backfill is not growth. Replacing someone who left restores a seat; it does not add one. A tool that adds them together will tell you the company is growing when it is standing still.

Open requisitions by role category
Role categoryOpen reqsKnown leaversCurrent people
Engineering971233,600
Customer Support481022,900
Marketplace & Category44722,028
G&A33522,200
Marketing & Ads2234964
Product & Design00417
Data & Analytics00191
All open roles24438312,300
Where the open roles are
SiteOpen reqsKnown leavers
◍ San Jose, US Americas118167
◍ Manila, PH APAC3968
◍ Bangalore, IN APAC2436
◍ Austin, US Americas2039
◍ New York, US Americas1927
◍ Salt Lake City, US Americas1733
◍ London, UK EMEA47
◍ Toronto, CA Americas20
◍ Dublin, IE EMEA11
◍ Berlin, DE EMEA01
◍ Shanghai, CN APAC04

How it stays honest

The one idea the whole thing defends: the model reads numbers, it never writes one. Everything below is a constraint the tool imposes on itself — and the checks that prove it did.

What this tool refuses to do
It will not average two systems that disagree.
Averaging 0.30 and 0.60 produces 0.45 — a number neither system claims, that nobody can defend in a room. The tool publishes 11,914–11,926 and names the 12 FTE it cannot confirm.
It will not clamp an over-allocation.
40 people are booked at 130% under the higher reading. A tidier tool would cap them at 100% and the problem would vanish from the report. This one shows the 12 FTE that cannot exist.
It will not plug a variance bridge.
The drivers sum to the gap exactly, or the tool reports that it cannot decompose it. A residual line that quietly absorbs the difference is a lie with a label on it.
It will not invent a zero.
A source that is silent about a team is silent. It does not mean the team has nobody in it. Missing is not zero.
It will not count a backfill as growth.
383 people left. Replacing them restores a seat; it does not add one. They are counted apart from the 244 open roles.
It will not let the model write a number.
The LLM maps columns and reads values. Every figure on every screen is arithmetic over rows — checked by a script that fails loudly if a total does not equal the rows beneath it.
How the numbers are checked

Every total on every screen is re-derived from the rows beneath it by a script — 2,786 checks, all passing. It fails loudly if it cannot even find the thing it is meant to check, because a selector that matches nothing must fail, not silently pass.

  • Every parent equals the sum of its children — organization, director, team, role, site.
  • Every team is counted twice — once by role, once by location. Two independent counts of the same people. They must agree with each other, not merely with the parent.
  • Every project is counted three times — by role, by who lends the people, and by where they sit.
  • The defensible FTE may never exceed headcount. The ceiling may — but only on a contested row, where it is reported as an over-allocation rather than clamped away.
  • 4,858 allocation cells checked for over-commitment. 40 people came back over 100%.
  • The bars are drawn from the same numbers as the tables — a picture built from a second copy of the data is a second chance to be wrong.
What is built, and what is not

built and running The bitemporal ledger, the reconciliation engine, the agentic column mapper (34 of 34 columns mapped correctly, zero wrong answers — checked by code that would fail if the guess were wrong), and the rollup arithmetic behind every figure here.

concept — not built yet The variance bridge and the time-phased forecast are drawn. The engine that would compute them is the next thing to build, and this page says so rather than letting you assume otherwise.

The honest caveat. The behaviours are pinned by tests on a 254-person engineering dataset. The 12,300 people here are illustrative, scaled to eBay's real footprint (FY2025 Form 10-K: ≈12,300 globally, ≈7,200 in the United States). Everyone below the C-suite appears by employee code, never by name; the seven named executives are eBay's real, publicly-listed leaders, mapped to illustrative units.

The five words that cause every argument
Headcount
People. One person is one head, whichever team borrows them. Heads do not split.
FTE
Full-time equivalent — a share of a person's time. A person split evenly across two projects is 1 head and 0.5 FTE on each. FTE adds up; heads do not.
Contractors
Counted and costed apart. Folding them into headcount is how a company accidentally reports 8% more people than it employs.
AOP / F1 / F2
The approved operating plan, and the two forecasts that have replaced it since. Which one you measure against changes whether an org is over or under.
Over-allocated
Someone booked past 100% of their time. It cannot be true, so it is surfaced, never clamped.

How this dashboard works, end to end

Every number on every other tab starts as five spreadsheets that disagree with each other. Here is the whole journey from those messy files to a single figure a leader can trust — in plain English, no jargon.

12,300
people counted across the org
$2.58B
annual people cost
244
open requisitions
12 FTE
flagged — never guessed
34/34
columns mapped · 0 wrong
2,786
checks re-foot every number
  1. 1
    Five files arrive — none agree on format
    HRIS, the ATS, Anaplan, and two side spreadsheets. Same ideas, different column names.
    HRIS
    employee_idcost_centerjob_levellocationfte_pctstart_dateemployment_type
    ATS
    req_idstatusteamlevelaccepted_onexpected_start
    Anaplan
    CCOrgFiscalHdctApproved FTEContractors Incl
    Sheet A
    TeamCCHdctQ3 Ask (fte)LvlLocUpdated
    Sheet B
    GroupCostCtrHeadsBandSiteAsOf
  2. 2
    A self-correcting AI agent maps each column
    A claude-sonnet-5 agent proposes a mapping onto 20 canonical fields; the checks push back, and it revises — up to three times. What it still can’t prove — like a raw fte_pct — it escalates to a person.
    ↺ failed checks written back into the prompt — retry up to 3×
    1
    Propose
    the agent reads each column and suggests a field + a reason
    claude-sonnet-5 · offline
    2
    Hard-check
    code runs checks that would fail if the guess were wrong
    ✓ Proven — kept
    → Person — if still failing after 3
    cost_centerCost centreProven
    job_levelLevelProven
    employment_typeStaff / contractorProven
    fte_pctFTEEscalated
    the AI proposes — it cannot self-certify
  3. 3
    A guess is trusted only if it can be proven
    Evidence counts only from a check that would fail if the guess were wrong. Confidence is computed, never claimed.
    Do the cost-centre codes actually exist?counts as proof
    Is it the only column that looks like cost centres?counts as proof
    Do the totals reconcile to a figure we already know?counts as proof
    “It looks like a name”never counts
  4. 4
    Proven facts enter a twice-dated ledger
    Every fact carries two dates — when it was true, and when we learned it — so any past date reads honestly.
    Cost centre CC-4472 = 88 people
    True from
    1 Apr 2026
    Known since
    30 Jun 2026
  5. 5
    Disagreements are sorted, not split
    The real case: two systems book 40 engineers’ time differently — leaving 12 FTE (the 11,914–11,926 gap) the tool won’t guess.
    Company FTE if the project system is right
    11,926
    vs
    …if the tracker is right
    11,914
    Never averaged to 11,920 — a number neither system claims.
    Published as a range 11,914–11,926 FTE, with 12 FTE flagged, not guessed.
    Agreed · all matchReconciled · a rule decidesContested · shown as a gap
  6. 6
    A person resolves what the AI could not
    Escalations go to human review; the fix is re-proven, versioned, and logged. Nothing is silently corrected.
    ● Escalated
    The AI couldn’t prove this mapping.
    ● Resolved
    A person approves or overrides. Re-run to prove it still reconciles, versioned v1→v2, decision logged.
  7. 7
    Everything consolidates into one number
    Rolled up by cost centre and org, every figure tagged — and that total is what every other tab shows.
    HRISATSAnaplanSheet ASheet B
    One consolidated headcount
    12,300 people · 11,914–11,926 FTE
    agreedreconciledcontestedsingle-source
Where AI is used — and where it deliberately isn’t
One AI agent
The schema mapper — model claude-sonnet-5, run offline. It self-corrects up to against the checks, and is forbidden from writing a number, its own evidence, or a confidence score.
Everything else is deterministic
The checks, the reconciliation, the ledger, the roll-up — plain arithmetic that gives the same answer every time. No model, no guessing. The live dashboard makes zero AI calls.
A person, for the rest
What the agent can’t prove is escalated to a human, who approves or overrides — then the system replays the whole mapping to re-verify before anything is saved.
One agent, tightly boxed. The AI does the judgement a person would find tedious; deterministic code does the proof; a human makes the calls the numbers can’t — and none of it runs live against your data.

The one rule the whole system defends: the AI reads numbers — it never writes one. A figure it cannot prove is handed to a person; a figure two sources dispute is shown as a gap, never a guess.

Want every constraint spelled out, and the 2,786 checks that enforce them?