Risk Management Tools, Techniques and Tribulations: The Pain and Recovery in Life Sciences Project Management Institute – SF Bay Area Chapter Embassy Suites,

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Presentation transcript:

Risk Management Tools, Techniques and Tribulations: The Pain and Recovery in Life Sciences Project Management Institute – SF Bay Area Chapter Embassy Suites, Walnut Creek March 17, 2010

Moderator  Tim Salaver, MBA, PMP, CSSMBB  Principal, Cornerstone Systems Solutions  President, Golden Gate Chapter of APICS The Association for Operations Management  EVP, Operations and Technology, Bio Supply Management Alliance  Director, Certification Preparation, PMI-SFBAC 3/17/20102Life Science Risk Management

Supply Chain Risk Management  Bill Coakley, MBA  Sr. Director, Supply Chain Management, SciClone Pharmaceuticals  Chairman, Sourcing Management Steering Committee, Bio Supply Management Alliance 3/17/20103Life Science Risk Management

Project Risk Management  Linda Karr, MBA, PMP  Project Manager, Pharma Technical Development, Genentech  President, San Francisco Chapter of International Society for Pharmaceutical Engineering (ISPE) 3/17/20104Life Science Risk Management

Enterprise & Operations Risk Management  Chris Sam, MS, Risk Management  Executive Director, Craigshannock  Member, Risk Management Steering Committee, Bio Supply Management Alliance  Executive Committee member of the Strategic Risk Management Council of the Conference Board  Former Executive Director, Operations Risk Management, Amgen  25 years in energy industry, previously at ExxonMobil 3/17/20105Life Science Risk Management

Industry Risk Management  Jane Lavine, MBA, CPCU, ARM, CFE  Life Science Risk Management consultant  Former VP, Life Science Practice, Marsh 3/17/20106Life Science Risk Management

The Healthcare System 3/17/2010Life Science Risk Management7

The Healthcare Shuffle 3/17/20108Life Science Risk Management Rx Delivery System Provider

The Life Sciences  Biotechnology  Pharmaceuticals  Medical Devices  Diagnostics  Nutraceuticals  Animal Biologics  Distributors or Delivery System (e.g., Cardinal Health, McKesson, Amerisource-Bergen)  Healthcare Providers 3/17/20109Life Science Risk Management

Managing Risks Related to Pharmaceuticals and Biotechnology  Tremendous Opportunity for Improvement in Healthcare  Electronic Medical Records Standardization Initiative  Driven By Department of Health – Bypassing Standards Bodies  Calling for Compliance by 2015  The Technology exists to Revolutionize Healthcare (not just reform)  Save Lives  Reduce Costs  Improve Quality of Care  The Strategy and Relationships are mostly in Place  Risks remain high for the companies manufacturing the drugs….WHY? 3/17/201010Life Science Risk Management

What happens prior to the drugs getting to the pharmacy? 3/17/2010Life Science Risk Management11 Audience question:

Project Risk Management in the Drug Development Pipeline 3/17/2010Life Science Risk Management12

Typical Drug Development Pipeline Product/Process Development

Panel Question 3/17/2010Life Science Risk Management14  At what point in the pipeline do you get involved and what is your role in managing risk? Product/Process Development

Panel Question 3/17/2010Life Science Risk Management15  In your role, do you have the ability to pull the “andon” cord?

Panel Question 3/17/2010Life Science Risk Management16  In your specific role, how important are you in managing risks to the patient? This question is important to note because while the manufacturer does not have a direct relationship to the patient, the quality of care is dependent on the quality of the product.

Panel Question 3/17/2010Life Science Risk Management17  What tools and techniques do you employ to identify risks?

Project Risk Management in the Product Life Cycle 3/17/2010Life Science Risk Management18

PMI Risk Management Process

Pre-Launch: Commercialization Product Life Cycle 3/17/2010Life Science Risk Management20  What inherent risks are addressed prior to product launch? Product/Process Development

Post-Launch: Commercialization Product Life Cycle 3/17/2010Life Science Risk Management21  What steps do you take to mitigate risks post commercialization? Product/Process Development

Risk Management Tools and Techniques 3/17/2010Life Science Risk Management22

Risk Register - example 3/17/2010Life Science Risk Management23

Risk and Response Log - example 3/17/2010Life Science Risk Management24

Map Key 1. Clinical trials 2. Sales and marketing practices 3. Consumer satisfaction/Company reputation 4. Environmental compliance 5. Business Interruption 6. Employee health and safety 7. Contingent BI- sole source supplier 8. Intellectual Property Infringement 9. Transit/supply chain 10. International regulations Risk Map (source: Marsh)

How to use the Risk Map  The dots represent a sample of risks associated with a life science company  Each company risk profile is unique  The positioning of the risk dots is both qualitative and quantitative analysis  The visual format is used to review the different risk profiles and their relationship to each other  This tool can be used for a function or a specific process

Failure Mode and Effects Analysis - example 3/17/2010Life Science Risk Management27 If RPN 1 or 2 is more than 100 you must do an abatement plan. Title:Risk Management Presentation FMEA #:1 Product Name:Professional Development Meeting Originator:Tim Salaver Process:Awareness and development of RM tools Issue Date:3/17/2010 Equipment: Revision Date: Participants:PMI Type of FMEA:P-FMEA Location:Embassy Suites, Walnut Creek FMEA Types:System Design, Detailed Design, Process, Equipment * RPN = Risk Priority Numbe r Failure Item: Potential Severity 1 Potential Occurrence 1 Current Detection 1 Current Detection 2 RPN 1* RPN 2* RecommendedOwnerDue Action Results Process FailureEffect(s) ofCause(s)/Control(s)ContainmentAction(s) DateActions Severity 2 Occurrence 2 Detection 3 RPN 3 Machine modefailureMechanism(s)in place Taken People of Failure Risk Management Presentation Instructor Lack of Learning Transfer 2 Incompetent Presenters 3 Presenter Experience 2None Review of training results and prepare on weak items Tim Salaver and Panelists 03/17/10 0 Risk Management Presentation Materials Lack of Understanding 4 Not Enough Time To Prepare 5 Mostly Developed Ahead of Presentation 3None Have Time to have Materials Proofed Independently Tim Salaver and Panelists 03/17/10 0 Risk Management Presentation Time Lack of Time To Fully Explain Content 9 The presentation is not comprehensive enough 4Experience2None Adjust materials to be covered or lengthen time Tim Salaver and Panelists 03/17/ If RPN 1 or 2 is more than 100 you must do an abatement plan.

Workshop on Preparing an FMEA Failure Mode and Effects Analysis is an effective tool in managing risks 3/17/2010Life Science Risk Management28

FMEA Process  Analysis of potential failure modes within a system for classification by severity or determination of the effect of failures on the system  Widely used in manufacturing industries in various phases of the product life cycle  Increasingly finding use in the service industry  Failure modes are any errors or defects in a process, design, or item, especially those that affect the customer, and can be potential or actual  Effects analysis refers to studying the consequences of those failures 3/17/2010Life Science Risk Management29 Example FMEA Worksheet Function Failure mode Effects S (severity rating) Cause(s) O (occur- rence rating) Current controls D (detectio n rating) CRIT (critical characte ristic RPN (risk priority number) Recomm ended actions Responsi bility and target completi on date Action taken

FMEA Terms  Failure mode - A failure mode is an event that causes a loss of a required function.  Failure effect - Immediate consequences of a failure on operation, function or functionality, or status of some item.  Indenture levels - An identifier for item complexity. Complexity increases as levels are closer to one.  Local effect - The Failure effect as it applies to the item under analysis.  Next higher level effect - The Failure effect as it applies at the next higher indenture level.  End effect - The failure effect at the highest indenture level or total system.  Failure cause - Defects in design, process, quality, or part application, which are the underlying cause of the failure or which initiate a process which leads to failure.  Severity: - The consequences of a failure mode. Severity considers the worst potential consequence of a failure, determined by the degree of injury, property damage, or system damage that could ultimately occur. 3/17/2010Life Science Risk Management30 Example FMEA Worksheet Function Failure mode Effects S (severity rating) Cause(s) O (occur- rence rating) Current controls D (detectio n rating) CRIT (critical characte ristic RPN (risk priority number) Recomm ended actions Responsi bility and target completi on date Action taken

3/17/2010Life Science Risk Management31

Step 1 – Detect a Failure Mode  A worksheet needs to be created, which contains the important information about the system, such as the revision date or the names of the components. On this worksheet all the items or functions of the subject should be listed in a logical manner, based on the block diagram.  Describe the system and its function.  Good understanding simplifies further analysis.  Consider both intentional and unintentional uses.  A block diagram of the system needs to be created. 3/17/2010Life Science Risk Management32 Example FMEA Worksheet Function Failure mode Effects S (severity rating) Cause(s) O (occur- rence rating) Current controls D (detectio n rating) CRIT (critical characte ristic RPN (risk priority number) Recomm ended actions Responsi bility and target completi on date Action taken

FMEA Cause and Effect Diagram 3/17/2010Life Science Risk Management33

Step 2 - Severity  Determine all failure modes based on the functional requirements and their effects  A failure mode in one component can lead to a failure mode in another component  Write these effects down in terms of what the user might see or experience  Examples: degraded performance, noise or even injury to a user  Each effect is given a severity number (S) from 1 (no danger) to 10 (critical)  Prioritize the failure modes and their effects  Severity 9 or 10 actions are considered changes in design by eliminating the failure mode 3/17/2010Life Science Risk Management34 Example FMEA Worksheet Function Failure mode Effects S (severity rating) Cause(s) O (occur- rence rating) Current controls D (detectio n rating) CRIT (critical characte ristic RPN (risk priority number) Recomm ended actions Responsi bility and target completi on date Action taken

Step 3 - Occurrence  Detailed development section of the FMEA process  Necessary to look at the cause of a failure and how many times it occurs  A failure cause is looked upon as a design weakness  All the potential causes for a failure mode should be identified and documented  Examples of causes are: erroneous algorithms, excessive voltage or improper operating conditions  A failure mode is given an occurrence ranking (O), again 1–10 3/17/2010Life Science Risk Management35 Example FMEA Worksheet Function Failure mode Effects S (severity rating) Cause(s) O (occur- rence rating) Current controls D (detectio n rating) CRIT (critical characte ristic RPN (risk priority number) Recomm ended actions Responsi bility and target completi on date Action taken

Step 4 - Detection  When appropriate actions are determined, test their efficiency  The proper inspection methods need to be chosen  How likely a failure can be identified or detected.  Each combination from the previous 2 steps receives a detection number (D).  Assigned detection number measures the risk that the failure will escape detection.  A high detection number indicates that the chances are high that the failure will escape detection, or in other words, that the chances of detection are low. 3/17/2010Life Science Risk Management36 Example FMEA Worksheet Function Failure mode Effects S (severity rating) Cause(s) O (occur- rence rating) Current controls D (detectio n rating) CRIT (critical characte ristic RPN (risk priority number) Recomm ended actions Responsi bility and target completi on date Action taken

Risk Priority Numbers  RPN = S × O × D  Easy to determine the areas of greatest concern  Modes that have the highest RPN should be given the highest priority for corrective action  Whenever a design or a process changes, an FMEA should be updated 3/17/2010Life Science Risk Management37 Example FMEA Worksheet Function Failure mode Effects S (severity rating) Cause(s) O (occur- rence rating) Current controls D (detectio n rating) CRIT (critical characte ristic RPN (risk priority number) Recomm ended actions Responsi bility and target completi on date Action taken

Exercise  Can you determine the order of need for change in the following three examples:  Severity (5), Occurrence (4), Detection (2) = 40  Severity (9), Occurrence (2), Detection (2) = 36  Severity (8), Occurrence (1), Detection (8) = 64  The correct order for action is #2, #1, #3. Why? 3/17/2010Life Science Risk Management38 Example FMEA Worksheet Function Failure mode Effects S (severity rating) Cause(s) O (occur- rence rating) Current controls D (detectio n rating) CRIT (critical characte ristic RPN (risk priority number) Recomm ended actions Responsi bility and target completi on date Action taken

Next Steps  Eliminate the failure mode with severity of 9 or 10  Minimize the severity of other failure modes  Reduce the occurrence of the failure mode  Improve the detection (reduce the number)  Update the FMEA  At the beginning of a cycle  Changes are made to the operating conditions  A Change is made in the design  New regulations are instituted  Customer feedback indicates a problem 3/17/2010Life Science Risk Management39

Advantages  Improve the quality, reliability and safety of a product/process  Improve company image and competitiveness  Increase user satisfaction  Reduce system development timing and cost  Collect information to reduce future failures, capture engineering knowledge  Reduce the potential for warranty concerns  Early identification and elimination of potential failure modes  Emphasize problem prevention  Minimize late changes and associated cost  Catalyst for teamwork and idea exchange between functions  Reduce the possibility of same kind of failure in future 3/17/2010Life Science Risk Management40

Sample BioPharma Case presented by Chris Sam Intro to Cp and Cpk (Measurements of process capabilities used in quality analysis.)  Cp - Inherent Process Capability  Note: in some industries this calculation is called pk. This is the ratio of the Upper Specification Limit minus the Lower Specification Limit to six sigma. It is denoted by the symbol Cp.  Cp = (Upper Spec Limit - Lower Spec Limit) 6Sigma Actual  Cannot calculate Cp if specifications are one sided. In other words, if specification only has an upper parameter specification limit or a lower specification limit, Cp is ignored and only Cpk can be used.  Confusion about the difference between Cp and Cpk. The difference is in calculating the actual sigma or standard deviation, either using an estimate, or the actual calculations.  Terms are sometimes used interchangeable, even though they are not. the same.  Statistics IS a science, and as such, all theory should be able to be validated by such peer reviews. 3/17/2010Life Science Risk Management41

Sample BioPharma Case presented by Chris Sam  Introduction to FMEA software  You help to complete the missing information  Using Cp and Cpk analysis 3/17/2010Life Science Risk Management42

Q&A 3/17/2010Life Science Risk Management43

Additional Resources  APICS The Association for Operations Management (  Bio Supply Management Alliance (  International Society for Pharmaceutical Engineers (  Strategic Risk Management Council ( board.org)  Marsh Risk Consulting ( For more information, please send to 3/17/2010Life Science Risk Management44

THANK YOU FOR YOUR PARTICIPATION Have a safe and risk-free drive home!!!

Risk Map (source: Marsh) Likelihood Low High