1Bechtel National Inc.

Using Human Performance Analysis to Eliminate Errors

Presented September 13, 2006DOE Integrated Safety Management Best Practices Workshop

Jim HummerConfiguration Management

Bechtel National, Inc.Hanford Waste Treatment and Immobilization Plant

2

WTP is the Solution to Hanford Tank Waste Cleanup

Legacy waste from WWII and Cold War production 53 million gallons of radioactive and chemical waste Waste is stored in 177 underground storage tanks 67 of the tanks have leaked

one million gallons of waste Left unchecked, the waste

could reach the Columbia River

WTP is fundamental to cleaning up nuclear waste

See www.waste2glass.com for additional information on WTP

3

WTP is DOE’s Largest Capital Procurement

Located in the heart of the DOE Hanford Site Three major nuclear facilities for

conditioning and vitrifying the waste An analytical laboratory Electric, steam, water,

and air utilities Operations and

maintenance buildings

See www.waste2glass.com for WTP Facility Fact Sheets

4

Pretreatment FacilityPretreatment Facility

High-Level Waste FacilityHigh-Level Waste Facility

Low-Activity Waste FacilityLow-Activity Waste Facility

LabLab

5

Software Applications Streamline Production

Several integrated software applications share information Engineering Procurement Construction Maintenance Business Services

6

Component Information Starts in CIS

Create and assign unique component identification numbers to equipment, valves, pipelines, and in-line components

Associate quality, safety, and technical data with the components Establish component-to-document relationships

CIS did not exist before the WTP Project.

The Component Information System is a database application fully integrated with CAD design software to:

7

CIS Error Rates are Low, but Expectations are High

Our target is achieve zero errors in critical data fields Over 71 thousand components are managed in CIS Over 2.9 million data fields are associated with these components Information is exported to eight downstream applications Critical data are monitored and action taken weekly When the error rate >1%, additional corrective action is initiated.

An error is any data field that is incorrect, incomplete, or inconsistent with issued design documents.

Critical data are associated with safety, environmental compliance, and quality

8

Eliminating Errors Calls for a New Approach

Significant error reduction was realized from: Modifying work processes Revising procedures Software modifications

Additional error reduction is a management objective

HPI — Human performance improvement is the tool

80 % Caused by Human Error

20 % Equipment Failure and

Other Causes

All Error Occurrences

Human Error Occurrences

70 % Latent Organizational Weaknesses

30 % Individual

Errors

9

HPI Provides the Insight to Eliminate Errors

Corrective action is used to fix errors

HPI is used to fix the conditions that cause errors

The CIS HPI uses a Behavioral Engineering Model (BEM) diagnostic tool recommended by the Society of Human Resource Management (SHRM)

Higher

Lower

Performance Results

Knowledge

Capacity

Motives

Incentives

Resources

Information

Impact

Cost

Lower

Higher

Leveraging the Solution

Leveraging the Solution (Adapted from ISPI,

2001, p. 6.3).

10

BEM Helped Define our Analysis Process

Key activities of the HPI analysis include: Validate that problems are the consequence of human

performance errors Develop and tailor lines of inquiry to identify the conditions that

cause those errors Interview the users of the software applications Consolidate conditions identified in interviews Analyze for BEM system factors - information, resources, and

incentives, and define corrective actions

11

Validate Conditions are Human Performance Errors

Adverse condition reports were reviewed to determine if errors were due to human performance, the work process, or software. The analysis team found examples of human error

One skill-based error Several rule-based errors Several knowledge-based errors

Errors committed ranged from inattention to detail to necessary violations to get the job done in spite of work process and software limitations.

12

Tailor Lines of Inquiry to the User

Lines of inquiry were designed to derive information that could be analyzed to determine What working steps are followed What knowledge is required What expectations are communicated to the user What influences may be present in the work environment

Seeking to understand what those who use CIS understand when doing their work was the goal for discovery.

13

Find the Right People to Interview

Fourteen users were interviewed Interview candidates were selected from all CIS users User picked to vertically cut through the work flow process Users represented both good and bad performers The number of interviewees

was based on ANSI/ASQC Z1.4 to obtain a statistically valid sample size

14

Identify the Conditions that Cause Errors

Conditions identified from interviews were combined and consolidated to identify less than adequate system factor. The BEM analysis determined:

1. Information available to CIS users is inadequate

– Users could not identify what procedural requirements apply to CIS

– Shared work processes are not adequately defined

– Procedure do not adequately address the role of automation

– Users are not always aware of procedure changes

15

Identify the Conditions that Cause Errors (continued)

2. Resources available to CIS users is inadequate

– Users do not understand downstream use of CIS information

– The CIS users guide is not kept up to date

– Schedule priority influences data quality

3. Incentives are not used to improve CIS users human performance to prevent errors

– Data discrepancy reports are not used to motivate users

– Discretionary rewards are used inconsistently to recognize performance

Corrective actions were developed with responsible management to correct or eliminate the conditions found

16

Recommendations

Four information recommendation for procedures and training

Three recommendations to improve resources available to the users

Two recommendations to apply incentives in the work process

Three OTHER recommendations

One lesson learned submitted

17

Conclusion

The goal of zero data errors continues to point to additional areas of improvement that cannot be reached by process, procedure, and software modifications without considering conditions that affect human performance.

HPI analysis disclosed conditions, that when altered or eliminated, will benefit all users, and reduce errors in CIS.

18

Summary

Human Performance Analysis was a success because of upfront planning

1. Tailored lines of inquiry helped extract most useful information

2. The many interviewees, and differing roles in the work process, reinforced what conditions affected performance

3.The Behavioral Engineering Model used helped structure the analysis The team and management are confident that corrective

actions identified will help us achieve zero errors.