TL 9000 Measurements Auditing the Validation Process

1
TL 9000 MeasurementsAuditing the Validation
Process

• Jerry Wilson
• TL 9000 Program Manager / Lead Auditor
• TÜV SÜD America, Inc.

2
Focus

• There are 4 basic components to the TL 9000
  measurements process as shown below. Today we
  will focus on the Validate step and review a few
  of the things that are verified during an audit
  of this process step.

• Data Sources
• Customer
• Supplier
• Internal system

3
Simplified Process Flow
Inputs
Process
Validate
Y
Collect
Analyze
N
Correct Data
Outputs

• Report to
• MRS
• Organization
• Customers (if required)

4
INPUTS

• The Auditor must gain an understanding of
• the product categories being reported
• the inputs
• What customers or suppliers provide data?
• What data do they supply?
• The collection methodologies for each
• How do they supply it?

5
INPUTS

• The Auditor must assess
• the status of any N/A or Exempt and ensure
  acceptability
• consistency with scope of registration
• Example All Common and Hardware measurements are
  collected if the organizations scope is H
• Review corrective actions if organization has
  previously been on suspended or probation
  status(ref Alert 06-003A)

6
PROCESS

• Look for
• documented validation process (measurements
  handbook 3.5.2. a))
• responsibilities for review and approval
• handling of invalid data
• access to the source data is available for
  validation
• verification that the output from any software
  application or spreadsheet has been verified
  (7.1.C.4 Tools Management)
• ensure correct calculations and proper use of the
  counting and exclusion rules
• Sample calculations, counting, and exclusion
  rules
• Ensure that validation personnel are trained and
  understand the counting rules

7
PROCESS CHANGE

• Look for
• Evidence that when changes are made to software
  applications / spreadsheets used to consolidate
  the information that there is verification that
  the output is acceptable (7.1.C.4 Tools
  Management)
• verify correct calculations
• verify data filters are working correctly
  (counting rules vs. exclusions)

8
OUTPUT

• Look for
• evidence data validation occurs prior to each
  reporting period
• acceptable DCRs for each category
• sample the summary data and comparing to DCRs

9
Indicators

• Possible Indicators
• Management Reviews show consistent poor results
• DCRs indicating zero for NPR / SPR (especially
  for several consecutive months)
• may indicate that the linkage between the
  reporting method and collection system is broken
• Large variations in quantities reported
• Issues related to the date filters orcounting
  rules

10

• Thank You