What a supply chain analyst studies to reach the top
$169,060top of the range in District of Columbia · middle $82,320 / yr
AI is transforming this role
Supply Chain Analysts in the United States earn a median of $82,320 a year. Pay starts near $50,890. Pay reaches $169,060 at the top of the range in Washington D.C., the best-paying location for this work among those with at least 500 people in the job.
Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Logisticians, SOC 13-1081). Last checked 9 September 2026.
Entry level
$50,890
Top of the range · District of Columbia
$169,060
Education
Bachelor's degree in Supply Chain or Business
Wages — U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Logisticians). Top of the range is the highest state-level figure among states with at least 500 people in the job. AI-impact rating is PayCrunch's editorial assessment. Updated September 2026.
🆕 New & Trending AI Tools for Supply Chain AnalystReviewed September 2026
We track new AI-tool launches every week and refresh this list — here’s what’s gaining traction for Supply Chain Analyst work right now.
Numeo AINEWPaid / see site
AI dispatch platform that matches loads and plans routes for trucking.
How a Supply Chain Analyst uses it: let AI find better loads and build the most efficient route/schedule
DAT iQNEWPaid / see site
Freight market intelligence with AI rate forecasting and lane analytics.
How a Supply Chain Analyst uses it: price a load right and pick profitable lanes with live market data
NetradyneNEWFleet / see site
AI-powered dashcam that coaches driving and rewards safe behavior.
How a Supply Chain Analyst uses it: get instant in-cab coaching and build a safety record that protects your CDL
NotebookLMNEWFree / $7.99 mo
Google tool that answers questions grounded only in the documents you give it — with citations.
How a Supply Chain Analyst uses it: load your own manuals, policies, or PDFs and ask questions that stay accurate to the source
Motive~$89/vehicle mo
Driver app with AI safety alerts, fuel and route insights (formerly KeepTruckin).
How a Supply Chain Analyst uses it: get real-time safety and fuel coaching and cut idle time on the road
Samsara~$99/vehicle mo
Connected-fleet platform with AI dash cams, routing, and maintenance alerts.
How a Supply Chain Analyst uses it: use AI dashcam coaching and predictive maintenance to stay safe and avoid breakdowns
Route4MePaid / see site
Route optimization that sequences multi-stop trips across 200+ variables.
How a Supply Chain Analyst uses it: turn a list of stops into the fastest, fuel-smart route in seconds
ChatGPTFree / $20 mo
The most-used AI assistant — writing, analysis, research, and images from a plain-language chat.
How a Supply Chain Analyst uses it: draft emails and documents, summarize long files, and get instant answers to on-the-job questions
ClaudeFree / $20 mo
AI assistant known for careful writing, long-document analysis, and coding.
How a Supply Chain Analyst uses it: analyze big reports or spreadsheets and turn messy notes into clean, finished writing
The person who explains the miss
A supply chain analyst spends the week turning a messy operation into a decision someone can make before the next shipment window. A customer order is late, a supplier slipped, a warehouse is holding too much of one product and too little of another, and a planner wants to know whether the problem is demand, a promise the sales team made, or a lead time nobody updated. You gather the records, you separate a one-time shock from a pattern, and you say what should change.
The desk sits between the forecast and the building. You are close enough to inventory, purchase orders, and carrier updates to see the actual flow, and far enough from the dock that your product is an explanation rather than a pallet. Some analysts live inside a manufacturer and watch raw material become finished goods. Some sit with a retailer and watch distribution centers feed stores. Some support a third-party logistics firm and watch many clients at once. The software changes. The habit does not: name the gap, name the cause you can defend, and name the choice.
People hire this title when spreadsheets have outgrown a coordinator's spare afternoon. The analyst is the person who can be asked, in a meeting, why service fell and what it would take to recover it without flooding the building with stock nobody will sell. If you like the hunt through records and you can tell the truth without drama, the work fits. If you need every day to feel like a new crisis you personally drive to the dock, a planner or a supervisor seat may fit better.
A week built from exceptions
Monday often starts with the misses. You open the orders that did not ship complete, the receipts that arrived short, and the forecast lines that reality has already left behind. You check whether the miss is a data error before you treat it as an operational one. A wrong unit of measure can look like a catastrophe. A duplicate order can look like a demand spike. Cleaning that up is not glamorous, and it is the reason the later recommendation is believable.
Midweek you are usually in the planning conversation. Sales brings what it hopes to sell. Operations brings what the plant or the warehouse can actually do. You bring the comparison: where the forecast has been reliable, where it has been optimistic, and which products deserve a buffer because the supplier's lead time moves around. You do not need to win the room. You need the room to leave with one version of the truth. Analysts who editorialize past the evidence get tuned out. Analysts who only dump tables and refuse a recommendation get replaced by the table itself.
The rest of the week is projects that sound small and change real money. You might rebuild the rule that says when to reorder a part. You might compare two suppliers on reliability, not on the quote alone. You might trace a chronic stockout back to a minimum the system still trusts. You write the finding so a manager who was not in your files can act on it. Charts help when they shorten the story. A paragraph that says what to do on Thursday helps more.
What good looks like on this desk
A useful analysis names the decision, the evidence, and the limit of the evidence. It tells a planner what to change this cycle, and it tells a manager what still needs a human look before anyone rewrites a policy.
Voluntary certificates, and no licence
There is no occupational licence for a supply chain analyst. No state board grants permission to forecast, to study inventory, or to sit in a planning meeting. Employers hire on evidence that you can do the work: coursework, a degree in supply chain, business, engineering, or a neighboring field, and, just as often, time spent as a buyer, a planning coordinator, or an inventory clerk who learned the system from the inside.
Certificates from the Association for Supply Chain Management, the body that carries the APICS credential family, are voluntary. People pursue them to show a shared vocabulary in planning, procurement, or logistics. A certificate can prove you studied that body of knowledge and completed the credential the association issues. It does not replace judgment about a live network, and it does not authorize you to do anything a licence would authorize, because this job has no such licence. Treat the credential as a signal on a resume, then be ready to talk through a real miss you investigated.
The association's home for those credentials is ascm.org. Read the current credential names there rather than trusting an old job posting that still uses a retired label. Prepare by learning the tools your target employers list, usually a spreadsheet at a serious level and one planning or analytics platform, and by practicing short spoken explanations. If you cannot explain a stockout to a warehouse supervisor without hiding inside jargon, the certificate will not carry the interview.
How a hiring manager hears a strong analyst
Applications that move are specific. Name the network you touched: a plant, a retail chain, a hospital supply room, a freight desk. Name the decision your work changed: a reorder point, a supplier the team stopped over-trusting, a report leaders actually opened. A list of software logos without a decision is easy to skip. A degree helps in many postings and is not a universal gate. Internal candidates who already know the company's mess often beat outside candidates who only know the textbook diagram.
In the interview, expect a messy scenario. Service fell, the forecast was wrong, and two departments blame each other. Walk through what you would pull first, what would change your mind, and what you would refuse to conclude from a single week. They are listening for sequence and for humility about bad data. Ask what the analyst owns versus what the planner owns. Ask how often the planning meeting actually changes a number in the system. Ask whether you will be maintaining a report that nobody reads. A beautiful title attached to a neglected dashboard is a frustrating job, and you can spot it if you ask.
Portfolio pieces help when they are honest and stripped of confidential figures. A rewritten excerpt, with the company hidden, that shows how you framed a problem is stronger than a claim that you "improved efficiency." Bring one example of a time you were wrong and corrected the file. Supply chain work is full of revised assumptions. Managers trust people who update the story when the receipt proves the story wrong.
From the report to a lane you own
Early analyst work is often reporting and cleanup. You inherit definitions that contradict each other, and you make them agree. That season teaches you the company's real process, which is rarely the process in the slide deck. After that, the role can widen into a category, a region, or a family of products you know cold. Senior analysts influence the policy, not only the chart: how much buffer is rational, which supplier gets the next volume, which promotion the network cannot support.
Some people stay analysts because they like the craft and do not want a team. That is a full career, especially in companies large enough to have principal or lead analyst seats. Others move into planning, procurement, logistics coordination, or a manager role that owns people and a budget. The manager move asks for a different muscle. You will be accountable for a result you no longer calculate yourself, and you will spend more of the day on conflict, hiring, and tradeoffs. Do that move because you want the accountability, not because the analyst title feels like a waiting room.
Adjacent titles are easy to blur and should stay distinct when you talk pay. A buyer negotiates and places orders. A planner sets the supply plan. A logistics coordinator chases freight. An analyst may support all three and still not be those jobs. When you interview for the next seat, use its title and its wage picture. The figures below describe this analyst comparison, not the manager job you might want later and not the coordinator job you might have left.
Reading the published figures once
These figures are the May 2025 wage release, for Logisticians. The series is broader than the analyst title, so use it as the published comparison for this kind of work, and keep the job name precise when you negotiate. A new analyst often starts near $50,890. Typical pay across the country is $82,320. The gap from entry to that median is $31,430. A new analyst still learning the company's definitions belongs nearer the entry figure. An analyst who already owns a recurring decision and a trusted report should look hard at anything stuck far below $82,320.
State medians, in this order, are Washington at $107,250, the District of Columbia at $104,770, Maryland at $102,700, Massachusetts at $100,360, and Hawaii at $100,340. Washington holds the highest median. The high end of the published range for the District of Columbia reaches $169,060. That high end and the District's median of $104,770 are different statistics. Quote $169,060 only as the top of the published range there. Quote $104,770 when you mean the District's median. Mixing them makes an ordinary analyst offer sound like the top of the range.
The national median sits $86,740 below that District range high end, and it sits $24,930 below Washington's median. Puerto Rico's middle wage is $54,380, the lowest. Washington's middle wage sits $52,870 above that. Those two medians are a geographic spread, not a promise that moving will produce the difference. Cost of living, industry mix, and the actual duties behind the posting all sit outside the wage release. Use the spread to stay humble about a national number, then return to the offer in front of you.
Bringing the figures into the offer
Start the pay conversation from the work, then attach a figure. If the role is a first analyst seat with heavy cleanup and close supervision, $50,890 is the honest reference, and you can still ask where the company expects someone to stand after a year of good work. If you already run a category analysis that leaders use, put $82,320 on the table as the national median and ask what in the offer matches that responsibility. The $31,430 gap is the distance between those two references. It is a fair way to talk about growth inside the title. It is a poor way to demand the entire gap on day one without the duties that justify it.
Use a state median only when the job is actually in that place. A Washington posting can be discussed against $107,250, which is $24,930 above the national median, without pretending every Washington employer pays the median. A Hawaii posting can be discussed against $100,340. A Massachusetts posting can be discussed against $100,360. Maryland's median is $102,700. None of those medians is the District of Columbia upper published bound of $169,060. If a recruiter offers the high end as a "typical" District salary, separate the statistics out loud and return to $104,770 as the District median.
Ask what else is in the package only in the company's own terms: bonus logic, shift or on-call expectations, and whether the analyst is included in the same review cycle as the planners. Do not invent dollar values for those pieces. You can say that a base near the entry figure plus a vague bonus is still an entry-level structure until the bonus is defined. You can say that a base near the Washington median is a different conversation from a base near $50,890. Leave with the statistic you meant still intact. The fastest way to weaken a good case is to call a median a high end, or to call this series a private survey of one company's analysts.
The top of Supply Chain Analyst pay — and how to get there with AI
$169,060what Supply Chain Analyst pay reaches in District of Columbia
Highest state-level top-of-range annual wage for Logisticians, among states with at least 500 people in the job. U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025.
And the role it leads to — Transportation, Storage, and Distribution Managers — reaches $223,700 in Massachusetts.
$50,890entry$82,320middle$169,060top end
An analyst in the middle of this field is trusted with the data; the one at the top of the range is trusted with the decision, and what usually stands behind that trust is a professional supply chain or project qualification rather than another year served.
The tasks that pay here are the ones with a signature attached: performing system lifecycle cost analysis and developing component studies, redesigning the movement of goods to raise value and cut cost, planning maintenance and repair analysis and test equipment recommendations, and reviewing logistics performance against targets and benchmarks. Employers hire that judgement against a credential, because a credential is shorthand for having been examined on inventory theory, contract terms and cost models. A model now does the reading alongside you, turning a dense standard into questions, explaining a total-cost formula, marking practice answers, which removes the usual reason people stall halfway through a qualification while working full time.
Your playbook, by where you are now
Just startingLearn the systems your employer already paid for
Get the enterprise resource planning ERP software out of the hands of the one person who understands it and learn to pull your own extracts.
Rebuild a recurring extract in Microsoft Access or Microsoft Excel so it refreshes instead of being retyped every month.
Sit in on a lifecycle cost study, then ask to own the component analysis on the next one.
Begin the entry-level supply chain qualification while the theory is still close to what you handle daily.
Have ChatGPT quiz you on the syllabus in the half hour before work, then check every answer against the study text.
What proves it: The first-level professional qualification, passed while working full time.
Realistic span: your first two years
A few years inPut your name on a costed recommendation
Take one route or warehousing redesign from the movement study through to a cost you are prepared to defend in front of a customer.
Check whether a change genuinely moved a measure using IBM SPSS Statistics rather than arguing from the shape of a chart.
Write the technical manual and training material for the process you redesigned, a duty already on your job description that almost nobody performs.
Draft that manual from your own notes with an assistant, then walk a new starter through it and fix everything they trip over.
Add the project management credential, since redesigns above a certain size are run as projects and staffed accordingly.
What proves it: A signed redesign with your lifecycle cost analysis and the training manual that came with it.
Realistic span: years two to five
ExperiencedBecome the person the qualification implies
Own the technology question for the function: which logistics technology advances to adopt, on what evidence, and what each one replaces.
Take the advanced tier that expects supplier and network decisions rather than planning technique alone.
Handle proprietary supplier and cost material properly, because control of that data is usually what decides who gets the sensitive studies.
Publish the performance review against service agreements in Microsoft Power BI so it arrives without you assembling it.
Move a step toward distribution management, where the same analysis carries budget authority.
What proves it: An advanced qualification alongside a technology decision the function actually adopted.
Realistic span: years five and beyond
The next 90 days
Pick the lifecycle cost study or route redesign your team keeps postponing, take it, and in the same week register for the qualification covering the theory behind it. Doing both at once is the point. The exam material stops being abstract when you are applying it to a real component study on Monday, and the study gives the exam something to be about. Ninety days is enough to finish the analysis, write the short technical manual that goes with it, and clear the first paper.
Wage figures: BLS OEWS, May 2025. The playbook is PayCrunch editorial guidance, not a guarantee of pay or placement.
Every figure is the national median from the U.S. Bureau of Labor Statistics (OEWS) shown on that role’s own page.
Never used AI before? Start here (2 minutes).
Start where the payoff is biggest: analyzing data in plain language. Load a de-identified dataset into Julius AI or use Microsoft 365 Copilot in Excel and ask questions the way you'd ask a colleague — 'which SKUs drive 80% of stockouts,' 'what's the trend in on-time delivery by supplier.' It compresses hours of pivot tables and formulas into minutes, and it's the fastest way to see AI's value in your role.
For deeper skills, learn a bit of Python (with an AI assistant writing and explaining the code) for forecasting and optimization, and use Claude or ChatGPT to turn analysis into executive-ready narrative. Keep proprietary and supplier data out of consumer tools — practice on public or de-identified data until you've confirmed what your company has approved.
The one rule, forever: Supply chain data is confidential and financially sensitive. Never paste proprietary demand data, supplier contracts, pricing, or cost structures into a consumer AI tool — and if you work at a public company, treat material non-public information accordingly. Verify every AI-generated number, model, and line of code before it drives a purchase order or a forecast: these outputs move real inventory and cash. AI can encode bias and miss context on supplier risk and relationships — keep human judgment on those calls.
The plays — exact steps, exact prompts
Do these in order. Each one is copy-paste ready. You do not need to know anything about AI going in.
1
Sharpen demand forecasts with AI
Why this pays: Forecast accuracy is the metric your whole operation keys off — better forecasts mean fewer stockouts and less dead inventory, which is measurable money. The analyst who moves the forecast-accuracy number is the one who gets promoted to senior demand planner, the role at the top of the range.
Julius AIMicrosoft 365 CopilotPython
1
Move beyond a simple moving average: use Julius AI or an AI-written Python script (with libraries like Prophet) to test forecasting approaches against your history, using de-identified data.
2
Have the AI design a rigorous forecasting and backtest so your accuracy claim holds up.
Copy-paste this prompt
I'm forecasting demand for [product category] with this de-identified history [describe: SKUs, granularity, seasonality, promotions]. Recommend an appropriate forecasting approach, how to handle seasonality and promotional spikes, how to backtest it properly (train/test split and error metrics like MAPE and bias), and the three most common forecasting mistakes that would make my results look better than they are.
Use de-identified data only, and validate every result on a true holdout — an over-fit forecast that fails in production costs real inventory dollars.
What you'll haveA measurable lift in forecast accuracy — the number that promotes you into senior demand-planning pay.
2
Optimize inventory and network cost
Why this pays: Inventory ties up cash and warehousing costs money; the analyst who can right-size safety stock and reorder points, or reshape the network, delivers savings leadership can bank. Quantified cost reductions are the single most promotable thing you can produce.
ThroughPut AIPythonKinaxis
1
Use specialized tools like ThroughPut AI or planning platforms such as Kinaxis where available, and AI-assisted Python to model inventory policy and network trade-offs on your data.
2
Work through the optimization logic so you can defend the recommendation, not just run it.
Copy-paste this prompt
Help me right-size inventory for [a set of SKUs] with this de-identified demand and lead-time data [describe]. Walk me through calculating safety stock and reorder points for a target service level of [98%], how lead-time variability changes the answer, the cash-vs-service trade-off to present to leadership, and how to identify slow-moving and obsolete stock to release cash. Show the formulas so I can verify them.
Verify every formula and assumption — these numbers set real reorder points and cash positions. Confirm the service-level target with the business before acting.
What you'll haveQuantified inventory and network savings leadership can bank — the impact that carries senior-analyst compensation.
3
Automate reporting and build live dashboards
Why this pays: Every hour spent rebuilding the weekly report is an hour not spent on analysis that creates value. Automating reporting and standing up self-serve dashboards makes you visibly efficient and frees you for the high-impact work that gets noticed and rewarded.
Microsoft 365 CopilotPower BITableau
1
Use Excel with Copilot to automate recurring analyses and Power BI or Tableau to build dashboards for the KPIs stakeholders ask about — OTIF, inventory turns, forecast accuracy, landed cost.
2
Design the dashboard around the decisions it should drive.
Copy-paste this prompt
I'm building a supply chain KPI dashboard for [operations leadership]. From these available metrics [list], recommend the 6-8 KPIs that best show performance and risk, how to lay them out for a one-screen executive view, what targets or benchmarks make each meaningful, and two misleading ways supply chain data is commonly displayed that I should avoid.
Confirm data sources are current and approved, and sanity-check that each KPI is calculated the way the business defines it.
What you'll haveReporting on autopilot and self-serve dashboards — the freed time and visibility that get high-impact analysts promoted.
4
Model disruptions and run what-if scenarios
Why this pays: Resilience planning is where analysts become strategic. The one who can quickly quantify the impact of a supplier failure, a port delay, or a demand spike — and show mitigation options — earns a seat in real decisions, and that seat pays.
Microsoft 365 CopilotPythonClaude
1
Build flexible scenario models in Excel with Copilot or Python so you can answer 'what if' on demand instead of rebuilding a spreadsheet each time.
2
Have the AI stress-test a disruption scenario and surface second-order effects.
Copy-paste this prompt
Model a supply chain disruption scenario: [e.g., a key supplier of a critical component goes offline for 8 weeks]. Given [describe inventory, lead times, alternatives generically], walk me through quantifying the impact on service and cost, the mitigation options (safety stock, dual-sourcing, expedite, allocation) with their trade-offs, and the second-order effects I might overlook. Frame it as options for leadership with rough cost and risk for each.
Keep supplier identities and contract terms out of the prompt. Model logic drives real risk decisions — verify assumptions and confirm supplier realities with procurement.
What you'll haveFast, credible disruption and scenario analysis — the strategic capability that earns a seat in leadership decisions.
5
Turn analysis into an executive narrative that wins
Why this pays: Analysis nobody acts on creates no value, and the analyst who translates numbers into a clear, persuasive recommendation is the one who influences decisions and gets promoted. Communication is the multiplier on every other skill here.
ClaudeChatGPT
1
Turn your findings into a tight, decision-oriented story for leadership.
Copy-paste this prompt
Turn this supply chain analysis into a one-page executive summary for operations leadership: [paste your generalized findings and numbers]. Lead with the bottom line and the dollar impact, then the two or three drivers behind it, a clear recommendation with estimated cost and benefit, and the key risk. Plain business language, no jargon, for someone who has three minutes.
The AI structures and sharpens the message — the analysis and the numbers must be yours and verified. Keep confidential figures out of consumer tools.
2
Ask the AI to challenge your recommendation the way a skeptical VP of Operations would, and prepare answers before you present.
What you'll haveRecommendations leadership acts on — the influence that converts good analysis into promotions and pay at the top of the range.
Your 12-month sequence to the top of the range
How the plays above stack into a path from median pay toward the $169,060 tier.
Month 1
Adopt plain-language data analysis (Julius AI or Excel Copilot) on de-identified data to replace hours of manual pivoting, verifying every output.
Months 2-3
Learn enough AI-assisted Python to run real forecasts and inventory models, and automate one recurring report into a live dashboard.
Months 3-6
Deliver a quantified win — a forecast-accuracy lift or an inventory-cost reduction — and package it in an executive summary.
Months 6-12
Specialize (demand planning, network optimization, or procurement analytics) and present scenario analysis to leadership — the senior profile behind pay at the top of the range.
Gear for this job
As an Amazon Associate, PayCrunch earns from qualifying purchases. Links to books and tools are for the job on this page; we only recommend what we’d use in the work.
Same live O’Reilly 3rd already on data-scientist / python-developer / market-research-analyst. This leftover page names learn a bit of Python for forecasting and optimization; Months 2–3 is Learn enough AI-assisted Python to run real forecasts and inventory models; FAQ says that is where the promotable, dollar-impact analysis lives. Not CompTIA Data+ and not leftover Ross Exam P (that is actuary). Confirm 109810403X. Live page HTTP 200, no PC_GEAR / amazon.com/dp / tag=paycrunch-20 at 2026-09-17 4:44 PM PT.
Next steps for a Supply Chain Analyst
Some links below are affiliate or partner links. PayCrunch may earn a commission if you enroll or subscribe through them, at no extra cost to you. Wage figures on this page still come from the Bureau of Labor Statistics, not from these programs.
Supply Chain Analyst work is specific enough that a stamped 'check out these courses' block would be noise. BLS files this work as Logisticians (SOC 13-1081). O*NET Job Zone 4 is typical: a bachelor's degree, so the honest next credential is a professional certificate or bachelor's-level coursework — not a random catalog dump.
The occupation's listed knowledge areas include Transportation and Engineering and Technology; the links search those subjects, not a generic 'career courses' list.
Supply Chain Analysts in this dataset list Amazon Redshift among the tools in use, so a program that names that stack is a better fit than a survey course.
Coursera search for transportation — a professional certificate or bachelor's-level coursework that lines up with business and finance, not a generic professional-development aisle.
FlexJobs screens remote, hybrid, freelance, and flexible listings so you are not wading through unverified ads. This is a job-board search for Supply Chain Analyst work, not a claim that they list a counted SOC 13-1081 inventory.
Write a Supply Chain Analyst resume, or one aimed at Transportation, Storage, and Distribution Managers, instead of a blank template. Resume Now is a resume builder; we are not claiming a counted template set for this SOC.
A Supply Chain Analyst resume that names the actual tasks on this page, or the step-up title Transportation, Storage, and Distribution Managers, beats a blank template when you apply.
What Supply Chain Analysts earn by state
These are the Bureau of Labor Statistics’ own figures for Logisticians, state by state — not a cost-of-living adjustment applied to the national number. Only states employing at least 500 people in the occupation are shown, because a state median drawn from a handful of workers is noise rather than a signal.
Washington
$107,250
highest of them · +30% vs the national median
Puerto Rico
$54,380
lowest of the 47 states and territories that qualify · -34% vs the national median
The same job pays $52,870 more a year at the median in Washington than in Puerto Rico — 97% higher. That gap is what the Bureau measured, before any question of what it costs to live in either place. The top-of-range figure quoted at the head of this page, $169,060, is a different statistic in a different place: it is the 90th-percentile wage in District of Columbia. The state that pays the typical worker most and the state where the best-paid go highest are not always the same one.
Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025, SOC 13-1081. 47 states and territories clear the 500-employee reporting floor for this occupation; those below it are left out rather than shown with a wide error band.
Free data. Use any of it.
PayCrunch publishes verified, BLS-sourced salary + AI-playbook data on 1,000+ professions — free, no signup.
It will replace the parts of the job that are pure spreadsheet mechanics, and reward the analysts who move up to judgment. AI forecasts and optimizes, but deciding which trade-off the business should make, understanding supplier relationships and risk, and defending a recommendation to leadership are human. The analysts who use AI to deliver bigger, faster wins become more valuable; those who only run reports are the ones most exposed.
Is it safe to use ChatGPT or Julius with company data?
Only within approved tools and never with sensitive data. Proprietary demand data, supplier contracts, pricing, and cost structures must stay in your company's sanctioned systems, and at a public company you must handle material non-public information with care. Use consumer AI on public or fully de-identified data, and confirm what your employer has authorized before analyzing anything confidential.
How do I trust an AI forecast or model?
By validating it, not believing it. Backtest every forecast on a true holdout, check the error metrics honestly, and verify the formulas in any model before it sets a reorder point. AI can produce confident, over-fit results that fail in production and confident code that has a subtle bug. Treat AI output as a fast draft you must prove out — because it moves real inventory and cash.
How does AI actually increase a supply chain analyst's pay?
By turning your work into quantified savings and getting you promoted. Better forecasts, right-sized inventory, and disruption models produce dollar impact you can point to; automated reporting frees time for that high-value work; and clear executive communication gets it acted on. Those wins move you into senior and specialized roles — demand planning, network optimization — at the $169,060 end of the band.
What should I learn first?
Plain-language data analysis with Julius AI or Excel Copilot on de-identified data — it replaces your most time-consuming manual work immediately and shows results you can quantify. Then add a little AI-assisted Python for real forecasting and optimization, which is where the promotable, dollar-impact analysis lives.
Methodology & sources
Salary (median, 10th, top of the range) — U.S. Bureau of Labor Statistics, OEWS.
By state — the Bureau of Labor Statistics’ own state medians, limited to states employing at least 500 people in the occupation. No cost-of-living arithmetic is applied to a wage anywhere on this page.
The plays — PayCrunch's own step-by-step guidance using publicly available AI tools. Tool names/URLs are real and current as of August 2026; prompts written to work as-is. Verify any professional output before relying on it.