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Production planners and expediters

Official title Production, Planning, and Expediting Clerks (SOC 43-5061)

Also called Production planner, Production scheduler, Expediter, Expediting clerk, Material planner

In brief

In May 2025, BLS counted 390,160 US production planners and expediters, with median pay of $59,650 a year. Of the BLS counts since 2003, the highest was 393,980, in May 2023, close to the May 2025 count. The earliest figure here is an estimate of 150,000 from 1940, not measured the same way as today's count. The last full technology era for production planners and expediters: Advanced Planning and Scheduling, 2010 to 2024. APS platforms reduced the headcount required to manage a given volume of production planning transactions.

What the sources say

Official outlook

BLS projects employment to decline 1.3% from 2025 to 2035.

BLS Employment Projections 2025-35

AI exposure studies

  • 51.9% of this job's tasks are exposed to large language models. Not a forecast of job losses. Eloundou and others, 2023
  • 0.88 estimated probability that the whole occupation could be computerised, over an unspecified number of years. Not a forecast of job losses. Frey and Osborne, 2013

Since the 2013 prediction

In 2013, Frey and Osborne put this job's probability of computerisation at 0.88. BLS counted 281,930 of these jobs in May 2013 and 390,160 in May 2025 (+38%, a change derived by Future History).

Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. BLS publishes these counts as yearly survey snapshots and cautions against reading them as a precise trend. In May 2021 BLS changed how it estimates these counts (a model-based method using three years of survey data) and moved fully to the 2018 occupation codes, so part of a change across 2021 can come from the method rather than the work.

Last updated .

Cite this page
APA

Future History. (2026, October 11). Production planners and expediters: jobs and pay since 1940 [Data set; data as of BLS OEWS May 2025; BLS Employment Projections 2025-35]. https://futurehistory.earth/timeline/43-5061

Chicago

Future History. "Production planners and expediters: jobs and pay since 1940." Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35. Last modified October 11, 2026. https://futurehistory.earth/timeline/43-5061.

BibTeX

@misc{futurehistory_43_5061, author = {{Future History}}, title = {Production planners and expediters: jobs and pay since 1940}, year = {2026}, month = oct, howpublished = {\url{https://futurehistory.earth/timeline/43-5061}}, note = {Last updated 2026-10-11. Data as of BLS OEWS May 2025; BLS Employment Projections 2025-35}, }

The access date is today's date on your device.

drag to travel through time
1925195019752000now
2026
Known then as Planning Room Clerk / Instruction Card Clerk (Taylor functional-foremanship era)
Known then as Production Control Clerk / Expediter (wartime and postwar manufacturing era)
Known then as Production Scheduler / Materials Coordinator (MRP and MRP II era)
Known then as Production Planner / Shop Scheduler (ERP transition era)
Known then as Production, Planning, and Expediting Clerks (BLS SOC 43-5061)
Known today as Production, Planning, and Expediting Clerks (BLS SOC 43-5061)
Projected to still be called Production, Planning, and Expediting Clerks (BLS SOC 43-5061)
Data from the May 2025 survey
US Employment
390K
Est.

Stated in source: BLS OEWS

Official statistic
Report an error
Median Annual Wage
$59,650
Est.

≈ $58,121 in 2024 prices (derived by us, CPI-adjusted)

Official statistic
Report an error
Beat · 1911

Frederick Taylor published "The Principles of Scientific Management," the foundational text that articulated the "planning room" concept and the separation of planning work from execution work. The instruction card clerk is the direct institutional ancestor of the production planning clerk.

Beat · 1942

The War Production Board coordinated the largest manufacturing mobilization in US history. Production control departments at plants building aircraft, tanks, and ships expanded rapidly. Women entered production control clerk roles in large numbers for the first time, a workforce shift that largely persisted after 1945.

Beat · 1972

APICS (the American Production and Inventory Control Society, now the Association for Supply Chain Management) formally standardized MRP practices, transforming what had been plant-specific craft knowledge into a credentialed profession. APICS certification (CPIM, Certified in Production and Inventory Management) became a standard hiring credential for production planning roles.

Beat · 1981

By 1981, approximately 8,000 US manufacturers had implemented computerized MRP systems, up from 700 in 1975. This rapid adoption redefined the production planning clerk role from a paper-based card-file specialist into an ERP operator. The transition required training and displaced workers who could not adapt to computer-based systems.

Beat · 1992

SAP released R/3, the ERP product that would dominate global manufacturing for the next three decades. Production planning in SAP PP became a specialized skill in its own right, creating a bifurcation within the occupation: clerks who could navigate SAP transaction codes and master data were paid substantially more and had better employment prospects than those who could not.

Beat · 2025

The WEF Future of Jobs Report 2025 identified data entry clerks, administrative assistants, and records-processing roles as the occupational categories facing the steepest displacement from AI adoption by 2030. Production planning clerks sit at the intersection of these categories, with most of their current transaction-processing tasks addressable by the agentic AI platforms launched in 2025.

How to read this number

OEWS is a point-in-time survey snapshot, not a continuous time series; BLS advises against using it for year-over-year trend comparison.

Each dot is a cited figure over time; the dotted line only links them (values between aren't measured). Hollow dots are estimates.

Official statistic: Copied by a script from a statistics agency table or a published study's table, not retyped by hand. BLS figures and the forecast and exposure tables are also re-checked against that table on every data run. Researched context: Researched from the cited source rather than copied from it by a script, so it is not machine-checked yet. Spot a mistake? Each figure has a “Report an error” link.

Cited forecasts · present → 2035

Will AI replace production planners and expediters? What the research says

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, we show the disagreement rather than an average.

Each figure is stated by the named source; we publish no forecasts of our own. Where sources disagree, the spread is the honest signal.

What published forecasts say
Forecast change in the number of people doing this work, as published by each named source. Bars share one scale on every role, centred on zero and reaching the end at ±30%. Grey marks a small change, 3% or less either way.
BLS Employment Projections 2025-35
→ 2035
-1.3%
BLS National Employment Matrix, 2025-35 cycle, line for SOC 43-5061 (Production, planning, and expediting clerks): 392.1 thousand jobs in 2025, projected 387.1 thousand in 2035, a change of -5.0 thousand (-1.3%). Matrix employment counts all jobs in the occupation, including self-employed workers (0.2% of this occupation in 2025). The average for all occupations in this cycle is +3.5%.
Official statisticReport an error
How exposed is this work to AI (research measures)
Scores as published by each study. Each row says what it measures. These measure what AI could technically do, not forecasts of jobs lost.
Frey & Osborne (2013), "The Future of Employment"
2013 study · Probability of computerisation (2013 model)
88%
probability
What this measures

Published appendix value for SOC 2010 43-5061 Production, Planning, and Expediting Clerks: probability of computerisation 0.88, rank 513 of 702 (rank 1 is least computerisable). Frey and Osborne estimated in 2013, with a Gaussian-process classifier on O*NET variables, how likely the whole occupation is to be technically automatable over "some unspecified number of years, perhaps a decade or two". It is a probability for the occupation, not a share of tasks and not a forecast of jobs lost.

Official statisticReport an error
Eloundou et al. (2023), "GPTs are GPTs"
2023 study · Share of tasks exposed to LLMs (β, human-rated)
51.9%
of tasks
What this measures

Published occupation-level exposure from the paper's occ_level.csv for O*NET-SOC 43-5061.00 Production, Planning, and Expediting Clerks. Shown: human-rated β = 0.519, the share of the occupation's tasks an LLM could do in at least half the time at equal quality, counting tasks that need LLM-powered software at half weight (β = E1 + 0.5 × E2). Other published measures for this occupation: human-rated α (LLM alone) 0.154 and γ (all LLM-assisted) 0.885; GPT-4-rated β 0.596. This measures how much of the work an LLM could touch, not how many jobs disappear.

Official statisticReport an error
Today, in this role

What's changing day to day for production planners and expediters

Three parts of your work where AI is already doing real lifting, and what stays yours.

AI is sitting alongside you hereReview AI-generated MRP exception messages and rescheduling recommendations in an APS platform (Kinaxis Maestro, SAP IBP, or o9)

Review AI-generated MRP exception messages and rescheduling recommendations in an APS platform (Kinaxis Maestro, SAP IBP, or o9); approve routine adjustments autonomously proposed by the system; escalate true capacity conflicts or supplier-risk items requiring human negotiation.[5],[6],[1]

Where your edge is

Develop fluency in reading the exception-scoring logic your APS platform uses. Understanding why the system flags a given exception -- and when its recommendation is wrong because it lacks context about a supplier relationship or a customer priority -- is the core judgment skill that keeps planners valuable after automation absorbs routine rescheduling.

AI is sitting alongside you hereMonitor AI-generated material-shortage alerts and inventory availability signals in ERP/APS

Monitor AI-generated material-shortage alerts and inventory availability signals in ERP/APS; validate flagged shortages against confirmed supplier lead times and in-transit data; decide whether to expedite, substitute a BOM alternative, or re-sequence the production order.[6],[7],[1]

Where your edge is

Build deep knowledge of your top critical-path materials: who makes them, typical lead times, and which suppliers can expedite versus which cannot. AI surfaces the shortage; you decide the fix. That decision requires supplier relationship knowledge the system does not have.

AI is sitting alongside you hereManage supplier expediting for late purchase orders: review AI-drafted status-request communications sent by the procurement platform

Manage supplier expediting for late purchase orders: review AI-drafted status-request communications sent by the procurement platform; handle escalation calls with suppliers who are non-responsive or requesting premium-freight or partial-shipment negotiations; document commitments in ERP.[9],[5]

Tools picking this up
Where your edge is

Develop negotiation skills specifically for supplier escalations: how to secure a firm commitment date, how to evaluate whether premium freight cost is justified by the production impact, and how to document the outcome so the ERP reflects reality. Routine supplier pings are automated; you are now the escalation layer.

Where production planners and expediters go next

Natural next steps for someone with your foundation: not exits, evolutions.

What each move takes

Production planning clerks regularly contact suppliers to expedite shipments and verify delivery dates -- this supplier-facing work is the natural bridge into purchasing. Purchasing agents take ownership of the supplier relationship end-to-end: sourcing, RFQ management, contract negotiation, and supplier performance management. The pivot requires developing formal negotiation skills and commercial awareness, but the operational knowledge of supplier lead times, BOM structures, and material criticality transfers directly.

What you'd add
  • · Contract negotiation fundamentals and supplier terms and conditions (ISM CPSM study materials)
  • · Total cost of ownership analysis and supplier scorecard development
  • · RFQ and competitive bid management in a sourcing platform (Coupa, Ariba, or Jaggaer)
  • · APICS CPIM or ISM CPSM certification to validate procurement fundamentals
  • · Supplier risk assessment and dual-sourcing strategy basics
What it takesSome new skills to pick up
Tools of the era

How has the work of production planners and expediters changed since 1903?

The tools that defined the work, one line per era. Select an era to see how it reshaped the work.

  • Planning room + card files (Taylor functional foremanship era)

    Frederick Taylor's 1903 "Shop Management" proposed separating planning from execution on the factory floor. The "planning room" staffed by instruction card clerks, order-of-work clerks, and time-and-cost clerks was the institutional ancestor of the modern production control department. Tools were entirely paper: routing sheets, job cards, and tally books. The clerk's value was in the accuracy of the card file and the speed of written communication to the shop floor.

    Effect on the work

    Taylor's functional foremanship model created the occupation where none had formally existed before. The planning room clerk was a new white-collar position in an era when manufacturing work was almost entirely blue-collar. The specialty grew steadily through the 1910s and 1920s as larger plants adopted scientific management principles.

  • Kardex visible-record system + paper travelers (wartime production control era)

    The Kardex visible-record cabinet, manufactured by the Kardex Rand company, became the standard tool of the production control clerk through the 1940s and 1950s. Each job order had a card visible in a tiered tray; the clerk updated status by pulling the card, marking progress, and refiling it. "Travelers" were paper job packets that physically accompanied work orders through every operation on the shop floor. The expediter's job in this era was literally physical: walking the shop floor, reading the travelers, noting delays, and escalating to the foreman. The wartime mobilization of 1941-45 -- when US industrial output doubled in four years -- drove the production control function to a new scale and sophistication, with entire departments dedicated to scheduling the flow of bomber subassemblies or tank components across multiple plants.

    Effect on the work

    The wartime manufacturing boom created a large new class of production control clerks, many of them women entering the workforce for the first time. Postwar, many of these workers remained as US manufacturing continued its expansion through the 1950s consumer goods boom.

  • Computerized MRP (Material Requirements Planning, Black and Decker 1964, IBM 1401)

    In 1964, Joseph Orlicky, an engineer working with IBM, implemented the first computerized MRP system at Black and Decker using an IBM 1401 mainframe. MRP replaced the manual card-file approach to materials tracking: given a master production schedule, a bill of materials, and current inventory levels, the computer calculated exactly what materials were needed and when. By 1975, hundreds of US manufacturers had implemented MRP systems; by 1981, that number had grown to approximately 8,000. For the production planning clerk, MRP did not eliminate the job -- it changed it. Instead of manually netting requirements from card files, the clerk now ran the MRP program, interpreted its output (the "exception messages" flagging material shortages or late orders), and took action on what the computer surfaced. The role shifted from data entry and manual calculation toward exception management and expediting.

    Effect on the work

    APICS (the professional association for production and inventory management) standardized MRP practices in 1972 and grew between 1965 and 1980, reflecting the occupational growth and professionalization of the production planning function during this era.

  • MRP II (Manufacturing Resource Planning, Oliver Wight 1983)

    In 1983, Oliver Wight, one of MRP's original architects, formalized Manufacturing Resource Planning (MRP II), which extended the original material-focused MRP to include labor capacity, machine capacity, and financial planning in the same system. MRP II meant that a production planner scheduling a job had to account not just for whether the material was available but whether the work center had capacity and whether the labor-hours were in budget. By 1989, roughly one-third of the US software industry's revenue came from MRP II products. The planning clerk's role grew more complex: instead of tracking material alone, the planner now held a richer model of the whole plant in the system, and exception management required understanding both material and capacity constraints simultaneously.

    Effect on the work

    MRP II systems increased the cognitive demand of the production planning role while also increasing its leverage: a single planner could now manage significantly more complexity than was possible with manual card files. Employment of production planning clerks peaked in this era as US manufacturing remained large and the systems amplified individual productivity without yet reducing headcount.

  • Enterprise Resource Planning (ERP: SAP R/3 1992, Oracle, Baan)

    SAP released R/3 in 1992, the product that would come to define ERP across global manufacturing. MRP II systems, which had been standalone or mainframe-hosted, migrated into integrated ERP platforms where production planning, purchasing, finance, and sales shared a single live database. For the production planner, ERP meant two things: vastly better visibility into the full supply chain (purchase orders, inventory, and work orders were all in one system) and a far more demanding technical environment (SAP PP module transactions, master data management, authorization roles). By the late 1990s, fluency in SAP or Oracle was effectively a hiring prerequisite for production planning roles at medium-to-large manufacturers. ERP also enabled the first meaningful automation of routine scheduling: the MRP run could be executed automatically on a schedule, rather than requiring a clerk to manually initiate it.

    Effect on the work

    ERP consolidation in the late 1990s and early 2000s enabled manufacturers to handle more production planning work with fewer clerks per plant. Employment in the occupation declined modestly from its late-1990s peak through the 2000s, with each ERP upgrade cycle typically accompanied by a "headcount rationalization" in the production control function.

  • Advanced Planning and Scheduling (APS): o9, Kinaxis RapidResponse, SAP IBP

    Where ERP automated the data management layer, Advanced Planning and Scheduling (APS) platforms automated the decision-recommendation layer. Kinaxis RapidResponse (widely adopted 2010s), SAP Integrated Business Planning (launched 2014), and o9 Solutions (founded 2009, scaled through 2010s-2020s) could ingest live demand signals, model the full supply network in memory, and generate recommended rescheduling actions in near-real time. For the production planner, APS transformed the job from "run MRP, read exception messages, manually re-sequence" into "review the system's recommended actions, approve or override, escalate the cases the system cannot resolve." Routine reschedule calculations that previously took a planner half a day could now be done in minutes by the system.

    Effect on the work

    APS platforms reduced the headcount required to manage a given volume of production planning transactions. Manufacturers implementing Kinaxis or SAP IBP routinely reported reductions in planning headcount as part of the business case.

  • Agentic AI supply chain orchestration (Kinaxis Maestro Agents, Oct 2025)

    In October 2025, Kinaxis launched Maestro Agents, described as "AI co-workers" that move planners "from issue to action in seconds" by autonomously handling routine exception resolution -- material shortages, late purchase orders, capacity conflicts with standard remedies -- and routing only genuine escalations to the human planner. Similar agentic capabilities arrived in SAP IBP and o9 through 2025. The distinction from earlier APS is significant: prior systems generated recommendations for a human to approve; agentic systems execute within pre-authorized rule sets without requiring approval for each action. For the production planner, this is the qualitative shift that earlier tools only approximated: the system now acts, and the human reviews the log rather than the queue.

    Effect on the work

    Scope Recruiting's 2026 analysis placed entry-level transactional production planning clerks at "90-95% likelihood of reduction by 2035." The survivable residual concentrates in exception judgment, cross-functional negotiation, APS configuration, and supplier relationship management.

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Production, Planning, and Expediting Clerks employment and pay by year

On record since1903
Latest US employment390,160 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Latest US median pay$59,650 (May 2025)Source: BLS OEWS May 2025Official statisticReport an error
Outlook-1.3% by 2035Source: BLS Employment Projections 2025-35Official statisticReport an error
View all 28 years of cited US data, each linked to its source
YearUS employmentAnnual pay (median unless marked)SourceReport
1940150,000n/aEst., IPUMS USA Researched contextReport
1956n/a$3,900Est., Derived estimate Researched contextReport
1960300,000n/aEst., US Census Bureau Researched contextReport
1980420,000$14,500Est., IPUMS USA (employment) Researched contextEst., University of Missouri Libraries (pay) Researched contextReport
2000330,120$30,590BLS OEWS 2000 Official statisticReport
2003277,030$34,820BLS OEWS May 2003 Official statisticReport
2004285,940$36,340BLS OEWS May 2004 Official statisticReport
2005287,980$37,590BLS OEWS May 2005 Official statisticReport
2006286,160$38,620BLS OEWS May 2006 Official statisticReport
2007283,930$39,690BLS OEWS May 2007 Official statisticReport
2008281,660$40,480BLS OEWS May 2008 Official statisticReport
2009274,140$41,560BLS OEWS May 2009 Official statisticReport
2010266,170$42,220BLS OEWS May 2010 Official statisticReport
2011272,910$43,100BLS OEWS May 2011 Official statisticReport
2012278,490$43,740BLS OEWS May 2012 Official statisticReport
2013281,930$44,630BLS OEWS May 2013 Official statisticReport
2014297,050$45,670BLS OEWS May 2014 Official statisticReport
2015309,110$46,150BLS OEWS May 2015 Official statisticReport
2016321,780$46,760BLS OEWS May 2016 Official statisticReport
2017336,000$46,670BLS OEWS May 2017 Official statisticReport
2018350,150$47,580BLS OEWS May 2018 Official statisticReport
2019370,380$48,260BLS OEWS May 2019 Official statisticReport
2020362,090$49,640BLS OEWS May 2020 Official statisticReport
2021367,200$48,040BLS OEWS May 2021 Official statisticReport
2022389,920$50,630BLS OEWS May 2022 Official statisticReport
2023393,980$53,900BLS OEWS May 2023 Official statisticReport
2024385,000$57,770BLS OEWS May 2024 Official statisticReport
2025390,160$59,650BLS OEWS May 2025 Official statisticReport
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