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Evidence Guide: MSS408008A - Analyse data for relevance to organisational learning

Student: __________________________________________________

Signature: _________________________________________________

Tips for gathering evidence to demonstrate your skills

The important thing to remember when gathering evidence is that the more evidence the better - that is, the more evidence you gather to demonstrate your skills, the more confident an assessor can be that you have learned the skills not just at one point in time, but are continuing to apply and develop those skills (as opposed to just learning for the test!). Furthermore, one piece of evidence that you collect will not usualy demonstrate all the required criteria for a unit of competency, whereas multiple overlapping pieces of evidence will usually do the trick!

From the Wiki University

 

MSS408008A - Analyse data for relevance to organisational learning

What evidence can you provide to prove your understanding of each of the following citeria?

Identify learning from own organisation data

  1. Obtain data from appropriate data systems
  2. Examine data for discontinuities, trends and other possible signs of assignable cause
  3. Examine selected data events to determine root causes of data events
  4. Communicate root causes of data events to relevant stakeholders
Obtain data from appropriate data systems

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Examine data for discontinuities, trends and other possible signs of assignable cause

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Examine selected data events to determine root causes of data events

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Communicate root causes of data events to relevant stakeholders

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Assessed

Teacher: ___________________________________ Date: _________

Signature: ________________________________________________

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Instructions to Assessors

Evidence Guide

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.

Overview of assessment

Competence must be demonstrated in the ability to recognise, extract and record learning from workplace generated data.

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:

sort relevant from irrelevant data, including establishing correlations

find and collate data from less obvious sources

translate data into information relevant to operational and improvement activities

make ongoing additions to the learning system

use the learning system to validate data-based improvement activities.

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.

Required Skills and Knowledge

Required skills

Required skills include:

undertaking self-directed problem solving and decision-making

communicating across all levels in an organisation

preparing reports and recommendations

researching and collating data from a variety of organisation systems and sources, including:

data presented at tool box and other regular team, section and area meetings

data available through ad hoc discussions/meetings with team members, sales and marketing employees, other employees, value stream members, regulators and visitors

data available from interviews with employees and external organisation representatives

operations records which may include data from:

clip boards on the line

problem solving templates

procedures templates

whiteboards or other noticeboards

computers or terminals that allow access to data bases and other electronic records

maintenance records

quality records

warranty and other returns

data from continuous improvement and breakthrough improvement activities (kaizen and kaizen blitz)

complaints from customers, employees and members of the community

equipment down time/maintenance records

non-obvious sources

determining significant data correlations and changes from those which may coincidentally be chronologically correlated

analysing data-related problems and events to root cause

determining value of data for organisational learning, including establishing procedures for monitoring effectiveness of improvement actions based on data

capturing learning through paper-based, electronic or other means (e.g. film and video)

Required knowledge

Required knowledge includes:

competitivesystems and practicestools, including:

value stream mapping

5S

Just in Time (JIT)

mistake proofing

process mapping

establishing customer pull

kaizen and kaizen blitz

setting of key performance indicators (KPIs)/metrics

identification and elimination of waste (muda)

organisational goals, strategies, operations and processes

continuous improvement strategies and processes

communication methods using arrange of media

root cause analysis (RCA)

mathematics and statistics

expected range of performance for operations and processes, including any KPIs

types of knowledge capture and retrieval systems used in the organisation and their applicability, including where used:

SPC processes

six sigma processes

quality processes

plant instrumentation and control data (e.g. SCADA) systems

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 SCADA software, Enterprise Resource Planning (ERP) systems, Materials Resource Planning (MRP) and proprietary systems

statistical process control systems, including six sigma and three sigma

JIT, kanban and other pull-related operations control systems

supply, value, and demand chain monitoring and analysis

5S

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

Data systems

Data systems are to include:

health, safety and environment (HSE) and maintenance systems along with process and quality systems

Codes of practice/standards

Where reference is made to industry codes of practice, and/or Australian/international standards, the latest version must be used

HSE

All changes implemented are expected to be at least neutral, or preferably beneficial, in their impact on HSE

Data

Data may come from any or all of a range of internal and value stream sources, including:

SPC processes

six sigma processes

quality processes

plant instrumentation and control data

Causes of data events

Data events need to be analysed to separate causes of changes in data from those which may coincidentally be chronologically correlated

Performance not to expectation/norm

Performance outside the normal range (good or bad) may be expected to have an assignable cause which when identified can add to knowledge

Other value stream members

Other value stream members includes:

internal and external suppliers and customers

Learning

Learning is something which can be passed on and is a recordable event or method which leads to change in practice

Systems for the capture of knowledge

Systems for the capture of knowledge may be paper based electronic or other and may include:

clip boards on the line

problem solving templates

procedures templates

whiteboards/other noticeboards

databases and other electronic records

incident reports

maintenance requests

They may have as part of them a method of knowledge retrieval and possibly of searching, filing and cataloguing

Record

Appropriate records include systems which ensure knowledge:

is not just retained by an individual

is available to others

survives beyond the departure of individual

has an allocated a level of importance

Stakeholders

Stakeholders may include:

work team members

value stream members