Apply statistics to operational processes

This unit of competency covers the skills and knowledge required to apply statistical theory and principles to the analysis and control of processes and operations.


This unit applies to a person working in an organisation applying statistical process control on processes or operations. The statistical process control will usually be used to monitor the processes or operations and determine when action needs to be taken. The appropriate action will then be taken in accordance with standard procedures.

The unit includes applying knowledge of frequency distribution and variation to the data/chart to distinguish between random and non-random variation and assumes understanding of the process and/or equipment to help interpret those results.

This unit primarily requires the application of skills associated with gathering and analysing data and communicating statistical information to others. This unit also has a strong emphasis on problem solving, initiative and enterprise, planning and organising, and self-management to solve problems and manage processes.


Not applicable.

Elements and Performance Criteria


Collect process data


Interpret sampling scheme


Obtain measurements in accordance with standard procedures


Handle data, as required


Interpret data


Plot data on appropriate control chart


Distinguish between random and non-random patterns of results


Identify results outside the control limits


Recognise situations requiring action


Take appropriate action in accordance with standard procedures


Determine cost of non-conformance


Calculate control limits


Consult relevant stakeholders to determine appropriate limits


Use relevant methods to calculate/revise control limits


Plot limits on control chart


Explain impact of limit to relevant stakeholders

Required Skills

Required skills

Required skills include:

applying a range of sampling procedures

analysing samples and data for variation, relevance, reliability and representativeness

problem solving the causes of variation in a process

communicating with other employees to obtain samples/data and to explain results and limits

plotting or documenting results

undertaking calculations, including:

basic arithmetic functions

mean, range, mean of means, standard deviation (using appropriate calculation aids)

using statistics to support process and operations control

Required knowledge

Required knowledge includes:

sampling techniques

purpose of sampling and measurement

random, systematic and stratified sampling

purpose of replication of data for statistical control

samples, populations, finite and infinite populations and the differences

methods of calculating means, standard deviations and the like and their purpose in statistical control

the meaning of broad/narrow frequency distributions/range/standard deviations and skewed distributions in process terms

concept of limits, including:

1 sigma warning limits

2 sigma warning limits

3 sigma control limits

6 sigma limits

types of control charts and their applications to different types of process/product and for different purposes

process causes of variation and typical cause types of non-random variation

non-process (e.g. measurement) causes of variation

recognition of stable and unstable processes

causes of stability/instability in the process

calculation of control limits/process capability and the applications of different control limits

the standard distribution curve and confidence limits

Evidence Required

The evidence guide provides advice on assessment and must be read in conjunction with the performance criteria, required skills and knowledge, range statement and the Assessment Guidelines for the Training Package.

Critical aspects for assessment and evidence required to demonstrate competency in this unit

A person who demonstrates competency in this unit must be able to provide evidence of the ability to:

follow sampling procedures

apply basic statistical processes

analyse data to identify variations and non-conformances

plot or document results.

Context of and specific resources for assessment

Assessment of performance must be undertaken in a workplace using or implementing one or more competitive systems and practices.

Access may be required to:

workplace procedures and plans relevant to work area

specifications and documentation relating to planned, currently being implemented, or implemented changes to work processes and procedures relevant to the assessee

documentation and information in relation to production, waste, overheads and hazard control/management

reports from supervisors/managers

case studies and scenarios to assess responses to contingencies.

Method of assessment

A holistic approach should be taken to the assessment.

Competence in this unit may be assessed by using a combination of the following to generate evidence:

demonstration in the workplace

workplace projects

suitable simulation

case studies/scenarios (particularly for assessment of contingencies, improvement scenarios, and so on)

targeted questioning

reports from supervisors, peers and colleagues (third-party reports)

portfolio of evidence.

In all cases it is expected that practical assessment will be combined with targeted questioning to assess underpinning knowledge.

Where applicable, reasonable adjustment must be made to work environments and training situations to accommodate ethnicity, age, gender, demographics and disability.

Guidance information for assessment

Assessment processes and techniques must be culturally appropriate and appropriate to the oracy, language and literacy capacity of the candidate and the work being performed.

Range Statement

The range statement relates to the unit of competency as a whole. It allows for different work environments and situations that may affect performance. Bold italicised wording, if used in the performance criteria, is detailed below. Essential operating conditions that may be present with training and assessment (depending on the work situation, needs of the candidate, accessibility of the item, and local industry and regional contexts) may also be included.

Competitive systems and practices

Competitive systems and practices may include, but are not limited to:

lean operations

agile operations

preventative and predictive maintenance approaches

monitoring and data gathering systems, such as Systems Control and Data Acquisition (SCADA) software, Enterprise Resource Planning (ERP) systems, Materials Resource Planning (MRP) and proprietary systems

statistical process control systems, including six sigma and three sigma

Just in Time (JIT), kanban and other pull-related operations control systems

supply, value, and demand chain monitoring and analysis


continuous improvement (kaizen)

breakthrough improvement (kaizen blitz)

cause/effect diagrams

overall equipment effectiveness (OEE)

takt time

process mapping

problem solving

run charts

standard procedures

current reality tree

Competitive systems and practices should be interpreted so as to take into account:

the stage of implementation of competitive systems and practices

the size of the enterprise

the work organisation, culture, regulatory environment and the industry sector

Sampling scheme

Sampling scheme may include:

sampling for attributes or sampling for variables

batch, continuous or custom made products

number of items/samples

size of sample

timing of sampling

location of sampling points

type of sample

number/type of measurements to be done on each sample

sampling equipment

measurement/testing equipment/methods


Procedures may include:

work instructions

standard operating procedures

formulas/ recipes

batch sheets

temporary instructions and similar instructions provided for the smooth running of the plant

good operating practice as may be defined by industry codes of practice (e.g. good manufacturing practice (GMP) and responsible care)

government regulations

Procedures may be:

written, verbal, computer-based or in some other format

Handle data

Handle data may include:

calculating means, ranges, mean of means and standard deviations (using appropriate calculation aids)

entering data into a software package

recording data either in writing or electronically

other required manipulations of the data

Control chart

Control charts may include:





other relevant charts


Random variation is the term used in statistical control to refer to those variations for which no cause can be found


Non-random (also called identifiable cause, assignable cause or special cause) are those variations for which a cause can be found and so the cause of the variation eliminated. Non-random variation may also be used to predict possible breaches of the control limits

Control limits

Control limits (also referred to as process capability) are those limits within which the process will operate if it is 'under control'

Cost of non-conformance

Cost of non-conformance includes:



unplanned service

excess inventory

complaint handline




labour costs

material costs

infrastructure costs/overhead

utility costs

Appropriate limits

Appropriate limits may include:

1 sigma warning limits

2 sigma warning limits

3 sigma control limits

6 sigma limits


Unit sector

Competitive systems and practices

Employability Skills

This unit contains employability skills.

Licensing Information

Not applicable.