I — Datum
SVEND vs JMP
A direct comparison for teams choosing between JMP and SVEND. Both platforms take quality engineering seriously. The differences are in delivery model, scope, and price.
Ref: JMP 18 (SAS) · SVEND Professional · Montgomery DOE 9th Ed.
II — Comparison
| Dimension | JMP | SVEND |
|---|---|---|
| Deployment | Desktop install (Windows/Mac) | Web browser, zero install |
| Pricing | ~$3,500/seat/year (Pro ~$8,500) | $49–$299/seat/month, cancel anytime |
| DOE | Excellent: custom, definitive screening, augment, mixture, split-plot | Full/fractional factorial, RSM, Plackett-Burman, D-optimal |
| Visualization | Excellent: Graph Builder, profiler, interactive | ForgeViz charting, precision document aesthetic |
| SPC | Control charts + capability | Same + Bayesian Cpk, configurable Nelson rules |
| Scripting | JSL (JMP Scripting Language) | API-first, Python/curl integration |
| Predictive Modeling | Neural nets, bootstrap forest, generalized regression | Focused on quality engineering, not general ML |
| Value Stream Mapping | Not included | Built-in with DES simulation + CI proposals |
| QMS / Hoshin | Not included | Composable QMS, hoshin kanri, X-matrix |
| Collaboration | JMP Live (separate product) | Built-in multi-user workbench |
III — When JMP Is the Right Choice
If your work requires definitive screening designs, mixture experiments, or split-plot DOE. If you need advanced predictive modeling (neural nets, bootstrap forest) alongside quality engineering. If your organization already has SAS infrastructure and JMP fits the existing stack. JMP's DOE platform is the best in class—this is not false modesty.
IV — When SVEND Is the Better Fit
If your focus is quality engineering rather than general data science. If you need VSM, QMS, and hoshin kanri integrated with your statistical analysis. If $3,500/seat/year for quality engineers is hard to justify when the core need is SPC + capability + DOE. If you want free tools your supply chain can access without a license.