For operations, quality and service teams

Statistical Process Control (SPC) Consulting

Is a spike this week a real problem or ordinary noise? Statistical process control gives you a clear answer. With the right control charts, you stop reacting to every small change and act fast when a process truly shifts, whether you run a production line, a clinic or a service desk.

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Best forOperations, quality and service teams

CoversControl charts, capability, rules

You receiveCharts, rules and a monitoring template

ToolsExcel, R, Python

The short answer

What is statistical process control?

Statistical process control (SPC) is a method for monitoring a process over time using control charts. Each chart shows a center line and control limits, usually three standard deviations either side of the average.

Points inside the limits reflect normal, common cause variation. Points outside the limits, or unusual patterns, signal a special cause that is worth investigating.

Signal or noise

Where statistical process control fits in your operations cycle

Operations teams see variation every day and must decide which changes are real. Control charts help, but only when the measurements are reliable and the limits are set correctly. We join at the point where the charts are built and read.

Swipe sideways to see the full diagram

Stage	Who leads	Their work	Where we fit
1. Process goal	Operations manager	Chooses the process and the quality target.	Helps pick a measure that reflects the process and can be tracked.
2. Measurement system	Quality engineer	Checks that the measurement tools are accurate.	Reviews measurement error, so noise is not mistaken for a process shift.
3. Data collection	Operators and supervisors	Records measurements on the line.	Sets up rational subgroups and a simple, consistent recording method.
4. Control charts	Data analyst	Builds charts and calculates control limits.	Calculates the limits, checks the chart rules and explains each signal.
5. Monitoring	Line supervisor	Watches the chart and reacts to signals.	Agrees a response plan, so signals trigger a clear action.
6. Improvement	Process team	Investigates causes and tests fixes.	Checks whether the change shifted the process, using the same charts.

Who it is for

Built for teams like yours.

Manufacturing and quality teams

Monitor defects, dimensions and yields with the right chart types.

Healthcare and service teams

Track waiting times, error rates and turnaround times.

Operations managers

Separate real performance changes from random noise in weekly KPIs.

What you get

Clear deliverables, agreed up front.

A practical monitoring system, not just a chart. Every project is quoted as a fixed price after a free assessment, so you know the cost before work begins.

Selection of the right control chart for each measure
Calculated control limits from your baseline data
Rules for spotting special causes
Process capability analysis (Cp, Cpk) where relevant
A reusable Excel or R monitoring template
Training for the people who will read the charts

Packages and pricing

Pick the depth you need.

Starting prices are shown for each option. Your final price is a fixed quote, agreed after a free assessment of your data and scope, so there are no surprises.

Start with one process

Chart Setup

Control charts for one process measure, set up correctly from the start.

From $400fixed project

Stability check of past data
Control limits calculated
Chart in Excel or R
Guide to reading signals

Get a fixed quote

Recommended for quality targets

Capability Study

Shows whether a process can meet its specification, not just whether it is stable.

From $900fixed project

Everything in Chart Setup
Measurement error review
Cp and Cpk with intervals
Improvement priorities report

Get a fixed quote

For ongoing operations

Monthly Monitoring

We review your charts each month and explain every signal.

From $300per month

Monthly chart update
Signal review and likely causes
Limit recalculation when the process changes

Get a fixed quote

How it works

Four steps from question to answer.

Step 1
Map
We identify the measures that matter and how they are collected.
Step 2
Baseline
We calculate center lines and limits from stable data.
Step 3
Chart
We build charts and agree the rules for action.
Step 4
Embed
We train your team and hand over the template.

Questions we help you answer

If you are asking these, we can help.

Common and special cause variationX bar and R chartsIndividuals and moving range chartsp and u charts for ratesWestern Electric rulesProcess capability (Cp, Cpk)Run charts

Tools we use

ExcelRPythonPower BI

?Is this week’s spike real or random?
?Is our process stable enough to improve?
?Which control chart fits our data?
?Is our process capable of meeting specification?
?Did our change actually improve performance?
?How do we avoid overreacting to noise?

FAQ

Questions about Statistical Process Control

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What is a control chart?

A time series chart with a center line and upper and lower control limits. It shows whether variation in a process is normal or signals something unusual.

Who needs SPC?

Any team that measures the same process repeatedly, such as quality, waiting times, defects, error rates or delivery times.

What is the difference between control limits and specification limits?

Control limits come from your process data and show what it naturally does. Specification limits come from customers or standards and show what it should do.

Which chart should I use?

It depends on the data: individual measurements, subgroup averages, proportions or counts each need a different chart. We select the right one for each measure.

Can SPC run in Excel?

Yes. We build Excel templates that update the chart as you add data, and can also set it up in Power BI or R.

Our services

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AI, automation and coaching