User Acceptance Rate (UAR): The Number Your Planning Vendor Will Not Publish
95%+
Sustained UAR across enterprise clients
User acceptance rate (UAR), also known as no touch rate, is the share of planning decisions that go live with no planner edits. Solvoyo tracks it on every decision, for every client, and over 95% of Solvoyo recommendations for operational decisions run untouched. If a planner has to fix the answer, the system did not decide.
80M
Weekly decisions at Unilever
8x
Planner productivity at Studenac
50%
Excess inventory reduction
500 bps
Transportation cost reduction
500 bps
Service improvement
Solvoyo tracks UAR together with the business KPIs it is meant to move, so each acceptance figure sits next to a cost, inventory or service result.
What is user acceptance rate (UAR), or no touch rate?
User Acceptance Rate (UAR), also called no touch rate, is the percentage of executed planning decisions that go live with no planner intervention. It measures how often a planning system’s recommendation is right the first time, so it is the most direct test of real supply chain automation.
A planning system can call itself autonomous and still send every order to a planner for review. UAR shows what happens next. When a planner changes a quantity, moves a date or rejects an order, that decision counts against the UAR. When the recommendation goes to the ERP as recommended, it counts for it. Some teams call the same measure plan acceptance rate, while many use no touch rate. UAR is Solvoyo’s own term, defined and measured by Solvoyo, so this page uses UAR and no touch rate interchangeably.
Solvoyo measures UAR per workflow and per SKU and resource. That covers replenishment, purchasing, production, allocation, fulfillment and transportation. Every edit also carries a reason code. That tells the team whether the planner knew something the model did not, or whether the model needs a new input.
High acceptance is the result. Recommendation quality is the cause. Nobody forces planners to stop editing. Instead, the recommendations get good enough that editing adds nothing.
How is UAR (no touch rate) calculated?
UAR =
Decisions executed exactly as recommended
All decisions executed
× 100
UAR at a glance
- Measures
- The share of planning decisions executed with no planner edits
- Also called
- No touch rate
- Level
- Per workflow, per SKU and per resource, with a reason code for each edit
- Solvoyo benchmark
- 95%+ sustained across enterprise clients
- Published range
- 81% in a first year to 100% in fulfillment and transportation
| Planner action | Effect on UAR |
|---|---|
Decision goes live as recommended | Counts as accepted |
Quantity, date, source or route changed | Counts as edited, reason logged |
Decision rejected or replaced | Counts as edited, reason logged |
Why don’t other planning vendors publish UAR?
Solvoyo is the first and only supply chain planning provider that measures UAR on every decision and publishes the results in named case studies. It also tracks UAR with each client as a shared KPI.
Usage metrics such as logins, screens opened or recommendations generated show that people used the tool. But they do not show that the tool made the decision.
Many legacy suites sent planners recommendations they had to rework, and some now sell agents that deliver the same recommendations faster. A bad plan delivered faster is still a bad plan. UAR is how a buyer tells the difference.
Measured
On every decision, per workflow and per SKU, with a reason code for each edit.
Co-owned
Customer Success engineers own UAR alongside service, cost and cash.
Published
In client case studies, including a mid-market CPG at 93% and Studenac at 81%.
How do vendors compare on UAR?
Most tools can generate a recommendation. But fewer can show how often it went live untouched. Read the full comparisons: Solvoyo vs. Traditional Planning Vendors and Solvoyo vs. New AI Startups.
Nine criteria, side by side
| UAR criterion | Traditional planning vendors | New AI startups | Solvoyo |
|---|---|---|---|
| Measures UAR | Usually usage, forecast accuracy and plan adherence. | Usually model accuracy or time saved. | Tracks UAR on every decision: 95%+ sustained across enterprise clients. |
| Publishes UAR in named results | Ask for it. | Ask for it. | Unilever over 95%, a mid-market CPG 93%, Studenac 81%. |
| Logs why a planner edited a plan | Often manual notes. | Varies by product. | A reason code on every edit, with monthly and quarterly reviews of the most edited SKUs. |
| Respects real constraints | Often plans function by function, in sequence. | Depends on the product. Ask for a plan against your own constraints. | One solve weighs cost, service, capacity and lead time together. |
| Acts on the decision | Often stops at the recommendation. Ask whether write-back is live in production. | Ranges from assistants to agents that act. Ask where the action lands. | Approved decisions are pushed to the ERP. |
| Limits set by the client | Varies by suite. | Varies by product. | Role-based limits per workflow, location and decision type. Every action is logged. |
| Ownership after go-live | Often support tickets and separately contracted consulting. | Varies. Ask who owns the number. | Customer Success engineers co-own service, cost and cash. |
| Time to a measurable UAR | Set by program scope. Ask for recent go-lives. | Pilots are usually fast. Ask what separates a pilot from production. | About 12 weeks to a production-ready configuration, with new logic every 3 to 6 weeks. |
| Data before go-live | Data is often cleansed first. | Some approaches assume clean history. | Onboarding includes a data foundation phase. Diagnostics profile the data and fill gaps. |
The middle columns describe typical behavior across each category, not any single vendor. Solvoyo figures come from its published case studies and product pages.
How does Solvoyo reach 95%+ UAR?
Better recommendations mean fewer edits. So a 95% rate comes from recommendations that planners have no reason to change. Seven parts of the Solvoyo platform make that happen.
Clean data
Recommend
Act
Measure UAR and KPIs
Analyze edits and KPIs
- Clean and validate the data
- Recommend
- Act
- Measure UAR and business KPIs
- Analyze edits and KPIs, then back to the data
Each pass through the loop lifts the next recommendation.
Clean Data First
The first step is cleaning and validating the input data. Data diagnostics run continuously, identifying issues with input data and flagging the most important ones impacting the quality of the recommendations, with AI filling in the gaps where appropriate.
One Solve, Every Constraint
A single mixed-integer pass weighs cost, service, capacity and lead time at once. As a result, planners stop fixing plans that looked feasible in one silo and broke in the next.
Inputs Learned, Not Assumed
Machine learning keeps lead times, price elasticity and sellable stock current, so the optimizer works from numbers that match what happens on the ground.
Every Edit Teaches the Model
Reason codes show which SKUs get edited most over 4, 8 and 12 weeks and why. The team then adds the missing cause to the model, so the edit stops recurring.
Solvi Explains Each Decision
Every recommendation shows its trigger, assumptions, trade-offs and cost impact. A planner can therefore defend the number in a meeting without rebuilding it in Excel.
Autonomy Grows With Trust
Clients choose which decisions Solvi runs on its own, by workflow, location and decision type. Scope widens only when UAR holds.
Hypercare Engineers Own the Number
Customer Success engineers track UAR next to service, cost and cash, and ship new logic in 3- to 6-week sprints when the rate dips. They read UAR together with the business KPIs, so each pass of the loop is judged on both.
What UAR do Solvoyo clients achieve?
User acceptance rates from live client workflows. Ranges show the spread across the workflows each client runs on Solvoyo.
| Client and scale | 50%75%100% | UAR |
|---|---|---|
| Unilever1B data points processed, 80M weekly decisionsDemand planning, inventory planning, production planning and scheduling, capacity planning, DRP, store replenishment, fulfillment and transportation, master data diagnostics, analytics and visibility | Over 95% | |
| Enterprise client800M data points, 400K daily automated decisionsFulfillment and transportation | 100% | |
| Multinational fashion retailer$2B revenue, 60 countries, 10M daily automated decisionsAllocation and replenishment | 93-98% | |
| Mid-market CPG, North America$250M revenue, 60,000+ service locations, 7,000+ SKUsDemand, supply, inventory and production planning | 93% | |
| Enterprise client$4.5B, 12 countriesPurchasing and production | 90-93% | |
| Multinational fashion retailer$500M revenue, 2.3M daily automated decisionsAllocation and replenishment | 86-90% | |
| Studenac Market1,000+ stores, first year liveGrocery store replenishment | 81% |
Last updated: 8 October 2026. Sources: Solvoyo client results (2026 overview), published Solvoyo case studies, and Unilever’s presentation at the 2023 Gartner Supply Chain Planning Summit in London.
90%+
User acceptance rate presented by Unilever’s Head of Supply Chain with the Solvoyo results at the 2023 Gartner Supply Chain Planning Summit in London, alongside 12x faster planning.
80% of IT tools investment fails if the partners don’t strive to continuously improve and adapt. That is what sets our partnership with Solvoyo apart.
Ask every planning vendor for its UAR
- What share of your plans run untouched?
- How do you measure it, and at what level?
- Can a client confirm the number?
Not sure what your own number is? Start there. Solvoyo will show how UAR is measured on live client workflows and what a realistic first-year rate looks like for your network.
User acceptance rate: frequently asked questions
What UAR measures
UAR, also called no touch rate, is the percentage of executed planning decisions that go live with no planner intervention. It shows how often a planning system’s recommendation is right the first time, so it is the most direct measure of real supply chain automation.
Divide the number of decisions executed exactly as recommended by the total number of decisions executed, then multiply by 100. Solvoyo calculates UAR per workflow, per SKU and per resource, and also logs a reason code for every edit.
Solvoyo clients sustain 95%+ UAR across enterprise workflows, with individual results from 81% in a first year to 100% in fulfillment and transportation. The first-year figure matters as much as the peak, because the rate climbs as edit reasons feed back into the model.
A public acceptance rate shows exactly how often planners overrule the system. Solvoyo publishes it because its clients’ results support it.
No. Forecast accuracy measures how close a prediction came to actual demand. UAR measures whether the resulting decision, such as an order, a transfer or a production run, was good enough to execute without change. A strong forecast can still produce a plan that planners reject.
UAR in practice
User adoption rate is the percentage of planners who use the system to make their decisions. It shows whether people have moved to the tool. User acceptance rate, by contrast, is the percentage of executed decisions that go live with no planner edits. It shows whether the recommendations are good. A team can reach 100% adoption, with every planner working in the system, and still have a low UAR if planners edit most of what the system recommends.
No. Planners can edit any decision, and every edit is logged with a reason. Rather, a high UAR means the recommendations are good enough that editing them adds nothing. Clients also decide which decisions Solvoyo may execute on its own.
Solvoyo tracks UAR together with the business KPIs the client cares about, such as OTIF, lost sales, stock cover, capacity utilization and transportation cost, and analyzes them side by side. UAR shows whether planners run the recommendations. The KPIs show whether running them improved service, cost and inventory.
Solvoyo reaches a production-ready configuration in about 12 weeks. Studenac reached 81% UAR, and Solvoyo’s Customer Success engineers then raise the rate through 3 to 6 week sprints that add missing causes to the model.
No. Solvoyo’s data diagnostics profile the data, flag gaps and use machine learning to fill them inside the platform. Onboarding also includes a data foundation phase, and UAR tracking starts on the first day of go-live.