Data releases, free to cite
Original engineering benchmark data, free to cite: cost indexes, AI adoption and modernization research, a monthly data release calendar, quotable statistics, and press contact.
NextGen Coding Company publishes one original engineering dataset per month — cost indexes, delivery-model studies, modernization and enterprise AI benchmarks — and every table is free to republish with a link back to the source page. Journalists, analysts, and vendors can lift the numbers directly, and named engineering leaders are available for comment on deadline at admin@nextgencodingcompany.com.
Stats you can quote today
Each figure below links to the report it comes from, where the methodology, sample basis, and full table are published. Attribution line: NextGen Coding Company, report title, year, and the source URL.
The onshore-to-offshore cost gap is 1.6x, not 4x
Once rework, timezone overlap loss, and client-side management overhead are priced in, effective cost per shipped outcome converges far more than rate cards suggest.
Engineer Cost Index 2026A senior engineering role left open 90 days costs ~$60K in unshipped work
Vacancy cost is the most under-modeled line in build-vs-buy analysis and usually exceeds the savings the comparison is chasing.
Engineer Cost Index 2026Offshore delivery carries a 22-35% rework rate
Rework is measured as delivered story points requiring material change after acceptance — roughly three times the onshore baseline of 6-10%.
Engineer Cost Index 2026Most enterprise AI pilots stall before production, not during it
Adoption failure clusters at data access and evaluation, not model quality — the blocking issues are organizational and appear before a model is chosen.
Enterprise AI Adoption Benchmark 2026Legacy modernization programs overrun on integration, not rewrite
Schedule slip concentrates in undocumented downstream consumers of the legacy system rather than in the replacement build itself.
Legacy Modernization Benchmark 2026451 NYC IT services deals analyzed for real contract structure and pricing
A rare public dataset on how mid-market technology services deals in New York are actually priced, scoped, and structured.
NYC IT Services Deal Benchmark 2026AP invoice extraction accuracy drops to 85-92% on photographed or faxed documents
Clean digital PDFs benchmark far higher; document channel, not model choice, is the dominant accuracy variable in accounts payable automation.
AI Accounts Payable Automation
One dataset a month, published in advance
We publish the schedule so reporters and newsletter writers can plan around it. If you cover one of these beats and want an advance look at a release, email us and we will send it before it goes live.
| Month | Dataset | Angle | Beat |
|---|---|---|---|
live | Engineer Cost Index 2026 | Fully loaded cost per senior engineer: onshore vs nearshore vs offshore The rate-card gap is 4x. The real gap, after rework and overlap loss, is 1.6x. | Tech labor market, CFO/finance press, engineering leadership newsletters |
scheduled | Enterprise AI Adoption Benchmark 2026 | Where enterprise AI pilots actually die — a stage-by-stage failure map Pilots stall at data access and evaluation, long before model quality is the constraint. | Enterprise AI trades, CIO publications, AI engineering newsletters |
scheduled | Legacy Modernization Benchmark 2026 | Why modernization programs overrun: integration surface, not rewrite scope Slip concentrates in undocumented downstream consumers nobody inventoried at kickoff. | Enterprise architecture, mainframe/COBOL trades, public sector IT |
scheduled | NYC IT Services Deal Benchmark 2026 | 451 deals: how New York technology services contracts are really priced A public read on deal size, structure, and pricing in a market that publishes almost nothing. | NYC business press, procurement and sourcing media, local tech ecosystem |
scheduled | Engineering Budget Outlook 2027 (new cut) | What engineering budgets look like going into 2027 Year-ahead planning data released while budgets are still being set — peak citation window. | CFO and finance media, engineering leadership, staffing industry analysts |
scheduled | Engineer Cost Index 2027 (annual refresh) | Annual refresh: what a senior engineer costs in 2027 January refreshes of an already-cited index get re-linked by everyone who cited last year's. | Tech labor market, compensation press, hiring newsletters |
scheduled | AI Accounts Payable Automation Benchmark | Extraction accuracy by document channel — where AP automation actually breaks Accuracy falls to 85-92% on photographed and faxed invoices regardless of model. | Finance automation trades, ERP and AP software press, CFO media |
scheduled | Nearshore vs Onshore Delivery Study | Overlap hours vs rework rate: the delivery-model tradeoff, quantified A model comparison with real rework and coordination data instead of rate cards. | Outsourcing and sourcing analysts, LatAm tech press, engineering leadership |
scheduled | Insurance & Logistics AI Outcomes Study | Measured outcomes from production AI in insurance and logistics operations Named metrics on extraction accuracy and turnaround reduction from live deployments. | Insurtech and supply chain trades, vertical AI newsletters |
scheduled | Technical Debt Cost Study | What technical debt costs per engineer per year, measured in shipped throughput Debt expressed as a throughput tax gives CFOs a number they can act on. | Engineering leadership, developer productivity researchers, CTO newsletters |
scheduled | Mid-Year Engineer Cost Index Update | Mid-year correction: where engineering rates moved in H1 Updates keep an evergreen dataset in the news cycle twice a year instead of once. | Tech labor market, staffing analysts, compensation press |
scheduled | Enterprise AI Adoption Benchmark 2027 | Year-over-year: what changed in enterprise AI adoption Second-year data creates trend lines, which are far more citable than a single snapshot. | Enterprise AI trades, CIO publications, industry analysts |
11 releases scheduled · Advance access and embargoed cuts: admin@nextgencodingcompany.com
The four-week cycle
Cut the data and publish the page
Refresh or re-slice an existing dataset into a standalone page with real HTML tables, a direct-answer block at the top, a methodology section, and the citation block. Tables must be markup, not images — a chart nobody can copy earns no links and no AI citations.
Pitch the beat, not the outlet
Twenty to thirty targeted pitches to reporters and newsletter writers who already cover that specific beat, each with the headline stat in the subject line, one paragraph of context, and a named expert available for comment on deadline. No attachments, no embargo theatre.
Syndicate and repurpose
Post the dataset to relevant communities and aggregators, publish an executive summary on LinkedIn from a named leader, submit to the industry newsletters that curate research, and answer live questions on the topic where practitioners actually ask them.
Reclaim and internally link
Find unlinked brand and stat mentions and request attribution, add the new asset to llms.txt and the sitemap, and link it from the commercial page it supports plus the three highest-authority pages on the site. Log every earned link against the target keyword.
Syndicate the releases
Every dataset ships with a wire-ready release — dateline, headline finding, quotable stats, a named quote, and methodology. Republish in full with a link back, or pull them automatically from the RSS and Atom feeds, which carry the entire release body.
- AP invoice extraction accuracy falls to 85-92% on photographed and faxed documents, regardless of model
- 451 New York IT services deals analyzed: how contracts are really priced and structured
- Enterprise AI pilots stall at data access and evaluation, not model quality
- Modernization programs overrun on integration surface, not rewrite scope, new benchmark finds
Logos, boilerplate, and report PDFs
Everything needed to publish: logo files for dark and light backgrounds, approved boilerplate in three lengths, quick facts, citation guidelines, and print-ready PDFs of all 4 benchmark reports. No form, no gate.
Citation policy
- Reproduce any table, figure, or statistic in full, including commercially, with a link to the source page.
- No permission request or prior notice required. No paywall, no gated download, no email capture on any dataset.
- Attribution format: NextGen Coding Company, "Report Title," Year, plus the source URL.
- CSV cuts, industry or metro breakdowns, and named expert comment available on request, same business day.
- We do not buy, sell, or exchange links, and we do not accept sponsored placements.
admin@nextgencodingcompany.com
NextGen Coding Company · New York, NY · Same business day response, faster on deadline.
Frequently asked questions
- Can I republish your benchmark tables?
- Yes. Every table, figure, and chart in our benchmark reports may be reproduced in full, including in commercial publications, with a link back to the source page on nextgencodingcompany.com. You do not need to request permission first. If you want the underlying cut by industry, company size, or metro, email admin@nextgencodingcompany.com and we will send it.
- How often do you publish new data?
- One data release per month on a published calendar. Each release is either a new dataset or a fresh cut of an existing one, with a stated methodology and a dated changelog. Flagship indexes such as the Engineer Cost Index are refreshed annually in January with a mid-year update in June.
- Where does the data come from?
- Our own engagements: placements, delivery telemetry, client rate benchmarking during procurement, and measured outcomes from production systems we built, supplemented with publicly posted compensation ranges in US metros. Every report states its sample basis and measurement definitions in a methodology section. We do not resell third-party panel data or extrapolate from vendor surveys.
- Can I get an expert quote or interview on deadline?
- Yes. We keep named engineering leaders available for comment on software delivery economics, legacy modernization, enterprise AI adoption, and US onshore hiring. Email admin@nextgencodingcompany.com with your deadline in the subject line; we respond same business day and can usually get you a named source within a few hours.
- Do you accept guest posts or paid link placements?
- No. We do not buy, sell, or exchange links, and we do not accept sponsored placements on this site. Coverage comes from the data being useful. If you have cited one of our figures without a link, we will ask for attribution, but that is the extent of it.
- Where is your press kit?
- At /press-kit. It includes logo files for dark and light backgrounds in SVG and PNG, approved boilerplate in 25-, 60-, and 120-word lengths, quick facts, print-ready PDFs of every benchmark report, and citation guidelines with attribution formats. Everything is downloadable as a single zip with no form or email capture.
- What formats are available for the data?
- Every report is published as real HTML tables so the numbers can be copied, parsed, and charted directly from the page, and so answer engines can extract them. Chart-ready CSV cuts for any published table are available on request from admin@nextgencodingcompany.com.
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