Your team brings
- Process context
- Operational knowledge
- Priorities and constraints
- Decision ownership
Data Analysis · additional analytical capacity for your team
Make performance and variation visible.
I support organizations and improvement teams with focused data analysis. The work may examine the performance of a production line, factory, supplier, product family or service process, add analytical capacity to an existing improvement project, or investigate a defined question. Your team retains the process knowledge and decision ownership; I perform the agreed analytical work and turn it into a clear visual evidence brief.
- Kickoff
- 30 min
- Analysis
- Jukka-Matti
- Focused engagement
- ~1 week
- Review
- 30 min
When the service is useful
Add analysis where it helps the work move forward.
The need does not have to be “we need one specific statistical analysis.” A useful engagement can start from a performance area, an existing project, or a focused question.
- 01
Understand operational performance
Build a clearer picture of performance, variation and meaningful subgroups in a production line, factory, supplier, product family or service process.
- 02
Add analytical capacity to a project
Bring an additional analytical resource into an existing internal improvement effort while your team continues to own the process, project and decisions.
- 03
Investigate a focused question
Compare conditions, assess stability or capability, examine an apparent difference, or test a defined hypothesis where the data and study design allow it.
How the collaboration works
Your team keeps the context and the decisions.
The strongest analysis combines operational knowledge with analytical discipline. I join as an additional resource rather than replacing the people who understand the work.
I bring
- Additional analytical capacity
- Statistical and visual methods
- An independent analytical perspective
- A clear evidence narrative
We agree together
- The performance area or question
- Useful data and comparisons
- Scope and evidence boundary
- How the result will support the next decision
After agreement · analysis scope
A useful analysis starts with context, not with a chart type.
The kickoff turns the performance area or decision context into a bounded analytical scope. Four inputs make that work useful.
- 01
Performance area or decision context
Define what needs to become clearer: an operation, supplier, process, project workstream, decision, or focused question.
- 02
Process context and known changes
Explain how the work runs, what has changed, and which conditions or subgroup definitions may matter.
- 03
Measure definition and data structure
Clarify what one observation and each measure mean, including units, order, identifiers and relevant grouping variables.
- 04
Usable, permitted data
Use data your organization is allowed to analyze and share. Sensitive fields can often be removed before transfer.
Worked example · two analytical views
From a broad supplier concern to a more useful question.
This is one example of how the analytical work can unfold—not the definition of the service. The first view asks whether behaviour changed over time. The second asks whether the weak result is broadly shared or concentrated in meaningful subgroups.
Worked example · generalized supplier-delivery data
One concern. Two views. Better questions.
The example shows how a broad supplier-performance concern can first be read over time and then separated into meaningful subgroups. It is not a description of every engagement.Staged Individuals chart of delivery margin. Observation order runs from left to right, zero is the promised date, and each predefined period has its own centre and control limits calculated from moving ranges within that stage.
01 · Performance over time
Has performance remained consistent?
The staged Individuals chart keeps individual deliveries in observation order. Stage-local centres and limits help separate a change in behaviour from ordinary variation.
Individuals chart P1 → P4 · scroll horizontally if needed
P4: stage centre shifts lower 0 = promised date
Stage centre Stage control limits Late Beyond stage limits
02 · Separate the variation
Is the weak result broad or concentrated?
Boxplots and every individual observation share one scale, so similar late counts cannot hide different distributions.
Part family A n 16 · 0 late
median +2.3
Part family B n 24 · 11 late
median +0.2
Part family C n 16 · 0 late
median +2.0
Part family D n 24 · 14 late
median −0.4
What the data supports
The latest period is weaker overall, and the adverse distribution is concentrated particularly in part families B and D.What it does not prove
The supplier, part family, or an operating condition caused the lateness. Causality requires process knowledge and additional evidence.What to investigate next
Examine what changed in the focused deliveries and compare them with deliveries from the same groups that still arrived on time.Identifiers, values, observation order, and analysis-stage boundaries are site-created. The example demonstrates an analytical approach, not a client result.
Two analytical lenses
Explore first. Confirm when the evidence allows it.
The question determines the method. Some engagements remain exploratory; others can test a defined hypothesis when the question, data and study design support it.
01
Exploratory
What patterns, shifts or subgroups deserve a closer look?
Profile the data, view variation over time, compare meaningful groups and sharpen the next operational question.
A clearer performance picture or a more focused question.02
Confirmatory
Does the evidence support a defined hypothesis?
Match the analysis to the question and study design, check assumptions, estimate uncertainty and assess whether the observed difference is defensible.
Support for or challenge to the hypothesis within the limits of the data.The engagement
A bounded analytical work package.
A focused engagement normally moves from kickoff to review in about one week. Broader performance reviews are scoped accordingly rather than forced into the same timetable.
Typical rhythm for a focused engagement
-
Kickoff
We clarify the performance area or question, process context, measures, useful comparisons, available data and evidence boundary.
Agreed analytical scope -
Focused analysis
I inspect the data structure and quality, make variation visible, compare relevant groups or conditions, and test a hypothesis where justified.
Evidence, uncertainty and useful visuals -
Review
We walk through what the data supports, what remains uncertain, and which decision, investigation or additional evidence should come next.
Shared interpretation and next move
The visual evidence brief
An analytical output your team can use.
The deliverable is designed to support the people doing the improvement work—not to sit as a separate analyst report.
- A visual picture of performance and variation
- Patterns and comparisons the data supports
- Uncertainty and conclusions the evidence does not support
- Operational questions or additional evidence worth pursuing
- Visuals usable in a project review, supplier discussion, workshop or management decision
Two ways to add analytical support
Data Analysis
I perform the agreed analytical work.
I join as additional analytical capacity. Your organization keeps the process knowledge, project context and decision ownership; I return a visual evidence brief for the team to use.Project Coaching
Your practitioner performs the analysis.
Your improvement professional or project team owns and performs the analytical work. I coach framing, measurement, method choices, interpretation and the wider project through the six-session flow.Conversation
Let’s talk about the analysis
If Data Analysis could help with the performance area or question in front of your team, let’s talk about the situation and what a useful analytical scope could look like. Scope, contract, required data, and secure transfer are agreed before files are shared.