Maturity Models, Utilizing the Validation Program as an Example

Maturity models offer significant benefits to organizations by providing a structured framework for benchmarking and assessment. Organizations can clearly understand their strengths and weaknesses by evaluating their current performance and maturity level in specific areas or processes. This assessment helps identify areas for improvement and sets a baseline for measuring progress over time. Benchmarking against industry standards or best practices also allows organizations to see how they compare to their peers, fostering a competitive edge.

One of the primary advantages of maturity models is their role in fostering a culture of continuous improvement. They provide a roadmap for growth and development, encouraging organizations to strive for higher maturity levels. This continuous improvement mindset helps organizations stay agile and adaptable in a rapidly changing business environment. By setting clear goals and milestones, maturity models guide organizations in systematically addressing deficiencies and enhancing their capabilities.

Standardization and consistency are also key benefits of maturity models. They help establish standardized practices across teams and departments, ensuring that processes are executed with the same level of quality and precision. This standardization reduces variability and errors, leading to more reliable and predictable outcomes. Maturity models create a common language and framework for communication, fostering collaboration and alignment toward shared organizational goals.

The use of maturity models significantly enhances efficiency and effectiveness. Organizations can increase productivity and use their resources by identifying areas for streamlining operations and optimizing workflows. This leads to reduced errors, minimized rework, and improved process efficiency. The focus on continuous improvement also means that organizations are constantly seeking ways to refine and enhance their operations, leading to sustained gains in efficiency.

Maturity models play a crucial role in risk reduction and compliance. They assist organizations in identifying potential risks and implementing measures to mitigate them, ensuring compliance with relevant regulations and standards. This proactive approach to risk management helps organizations avoid costly penalties and reputational damage. Moreover, maturity models improve strategic planning and decision-making by providing a data-backed foundation for setting priorities and making informed choices.

Finally, maturity models improve communication and transparency within organizations. Providing a common communication framework increases transparency and builds trust among employees. This improved communication fosters a sense of shared purpose and collaboration, essential for achieving organizational goals. Overall, maturity models serve as valuable tools for driving continuous improvement, enhancing efficiency, and fostering a culture of excellence within organizations.

Business Process Maturity Model (BPMM)

A structured framework used to assess and improve the maturity of an organization’s business processes, it provides a systematic methodology to evaluate the effectiveness, efficiency, and adaptability of processes within an organization, guiding continuous improvement efforts.

Key Characteristics of BPMM

Assessment and Classification: BPMM helps organizations understand their current process maturity level and identify areas for improvement. It classifies processes into different maturity levels, each representing a progressive improvement in process management.

Guiding Principles: The model emphasizes a process-centric approach focusing on continuous improvement. Key principles include aligning improvements with business goals, standardization, measurement, stakeholder involvement, documentation, training, technology enablement, and governance.

Incremental Levels

BPMM typically consists of five levels, each building on the previous one:

Initial: Processes are ad hoc and chaotic, with little control or consistency.
Managed: Basic processes are established and documented, but results may vary.
Standardized: Processes are well-documented, standardized, and consistently executed across the organization.
Predictable: Processes are quantitatively measured and controlled, with data-driven decision-making.
Optimizing: Continuous process improvement is ingrained in the organization’s culture, focusing on innovation and optimization.

Benefits of BPMM

Improved Process Efficiency: By standardizing and optimizing processes, organizations can achieve higher efficiency and consistency, leading to better resource utilization and reduced errors.
Enhanced Customer Satisfaction: Mature processes lead to higher product and service quality, which improves customer satisfaction.
Better Change Management: Higher process maturity increases an organization’s ability to navigate change and realize project benefits.
Readiness for Technology Deployment: BPMM helps ensure organizational readiness for new technology implementations, reducing the risk of failure.

Usage and Implementation

Assessment: Organizations can conduct BPMM assessments internally or with the help of external appraisers. These assessments involve reviewing process documentation, interviewing employees, and analyzing process outputs to determine maturity levels.
Roadmap for Improvement: Organizations can develop a roadmap for progressing to higher maturity levels based on the assessment results. This roadmap includes specific actions to address identified deficiencies and improve process capabilities.
Continuous monitoring and regular evaluations are crucial to ensure that processes remain effective and improvements are sustained over time.

A BPMM Example: Validation Program based on ASTM E2500

To apply the Business Process Maturity Model (BPMM) to a validation program aligned with ASTM E2500, we need to evaluate the program’s maturity across the five levels of BPMM while incorporating the key principles of ASTM E2500. Here’s how this application might look:

Level 1: Initial

At this level, the validation program is ad hoc and lacks standardization:

Validation activities are performed inconsistently across different projects or departments.
There’s limited understanding of ASTM E2500 principles.
Risk assessment and scientific rationale for validation activities are not systematically applied.
Documentation is inconsistent and often incomplete.

Level 2: Managed

The validation program shows some structure but lacks organization-wide consistency:

Basic validation processes are established but may not fully align with ASTM E2500 guidelines.
Some risk assessment tools are used, but not consistently across all projects.
Subject Matter Experts (SMEs) are involved, but their roles are unclear.
There’s increased awareness of the need for scientific justification in validation activities.

Level 3: Standardized

The validation program is well-defined and consistently implemented:

Validation processes are standardized across the organization and align with ASTM E2500 principles.
Risk-based approaches are consistently used to determine the scope and extent of validation activities.
SMEs are systematically involved in the design review and verification processes.
The concept of “verification” replaces traditional IQ/OQ/PQ, focusing on critical aspects that impact product quality and patient safety.
Quality risk management tools (e.g., impact assessments, risk management) are routinely used to identify critical quality attributes and process parameters.

Level 4: Predictable

The validation program is quantitatively managed and controlled:

Key Performance Indicators (KPIs) for validation activities are established and regularly monitored.
Data-driven decision-making is used to continually improve the efficiency and effectiveness of validation processes.
Advanced risk management techniques are employed to predict and mitigate potential issues before they occur.
There’s a strong focus on leveraging supplier documentation and expertise to streamline validation efforts.
Engineering procedures for quality activities (e.g., vendor technical assessments and installation verification) are formalized and consistently applied.

Level 5: Optimizing

The validation program is characterized by continuous improvement and innovation:

There’s a culture of continuous improvement in validation processes, aligned with the latest industry best practices and regulatory expectations.
Innovation in validation approaches is encouraged, always maintaining alignment with ASTM E2500 principles.
The organization actively contributes to developing industry standards and best practices in validation.
Validation activities are seamless integrated with other quality management systems, supporting a holistic approach to product quality and patient safety.
Advanced technologies (e.g., artificial intelligence, machine learning) may be leveraged to enhance risk assessment and validation strategies.

Key Considerations for Implementation

Risk-Based Approach: At higher maturity levels, the validation program should fully embrace the risk-based approach advocated by ASTM E2500, focusing efforts on aspects critical to product quality and patient safety.
Scientific Rationale: As maturity increases, there should be a stronger emphasis on scientific understanding and justification for validation activities, moving away from a checklist-based approach.
SME Involvement: Higher maturity levels should see increased and earlier involvement of SMEs in the validation process, from equipment selection to verification.
Supplier Integration: More mature programs will leverage supplier expertise and documentation effectively, reducing redundant testing and improving efficiency.
Continuous Improvement: At the highest maturity level, the validation program should have mechanisms in place for continuous evaluation and improvement of processes, always aligned with ASTM E2500 principles and the latest regulatory expectations.

Process and Enterprise Maturity Model (PEMM),

The Process and Enterprise Maturity Model (PEMM), developed by Dr. Michael Hammer, is a comprehensive framework designed to help organizations assess and improve their process maturity. It is a corporate roadmap and benchmarking tool for companies aiming to become process-centric enterprises.

Key Components of PEMM

PEMM is structured around two main dimensions: Process Enablers and Organizational Capabilities. Each dimension is evaluated on a scale to determine the maturity level.

Process Enablers

These elements directly impact the performance and effectiveness of individual processes. They include:

Design: The structure and documentation of the process.
Performers: The individuals or teams executing the process.
Owner: The person responsible for the process.
Infrastructure: The tools, systems, and resources supporting the process.
Metrics: The measurements used to evaluate process performance.

Organizational Capabilities

These capabilities create an environment that supports and sustains high-performance processes. They include:

Leadership: The commitment and support from top management.
Culture: The organizational values and behaviors that promote process excellence.
Expertise: The skills and knowledge required to manage and improve processes.
Governance: The mechanisms to oversee and guide process management activities.

Maturity Levels

Both Process Enablers and Organizational Capabilities are assessed on a scale from P0 to P4 (for processes) and E0 to E4 (for enterprise capabilities):

P0/E0: Non-existent or ad hoc processes and capabilities.
P1/E1: Basic, but inconsistent and poorly documented.
P2/E2: Defined and documented, but not fully integrated.
P3/E3: Managed and measured, with consistent performance.
P4/E4: Optimized and continuously improved.

Benefits of PEMM

Self-Assessment: PEMM is designed to be simple enough for organizations to conduct their own assessments without needing external consultants.
Empirical Evidence: It encourages the collection of data to support process improvements rather than relying on intuition.
Engagement: Involves all levels of the organization in the process journey, turning employees into advocates for change.
Roadmap for Improvement: Provides a clear path for organizations to follow in their process improvement efforts.

Application of PEMM

PEMM can be applied to any type of process within an organization, whether customer-facing or internal, core or support, transactional or knowledge-intensive. It helps organizations:

Assess Current Maturity: Identify the current state of process and enterprise capabilities.
Benchmark: Compare against industry standards and best practices.
Identify Improvements: Pinpoint areas that need enhancement.
Track Progress: Monitor the implementation and effectiveness of process improvements.

A PEMM Example: Validation Program based on ASTM E2500

To apply the Process and Enterprise Maturity Model (PEMM) to an ASTM E2500 validation program, we can evaluate the program’s maturity across the five process enablers and four enterprise capabilities defined in PEMM. Here’s how this application might look:

Process Enablers

Design:

P-1: Basic ASTM E2500 approach implemented, but not consistently across all projects
P-2: ASTM E2500 principles applied consistently, with clear definition of requirements, specifications, and verification activities
P-3: Risk-based approach fully integrated into design process, with SME involvement from the start
P-4: Continuous improvement of ASTM E2500 implementation based on lessons learned and industry best practices

Performers:

P-1: Some staff trained on ASTM E2500 principles
P-2: All relevant staff trained and understand their roles in the ASTM E2500 process
P-3: Staff proactively apply risk-based thinking and scientific rationale in validation activities
P-4: Staff contribute to improving the ASTM E2500 process and mentor others

Owner:

P-1: Validation program has a designated owner, but role is not well-defined
P-2: Clear ownership of the ASTM E2500 process with defined responsibilities
P-3: Owner actively manages and improves the ASTM E2500 process
P-4: Owner collaborates across departments to optimize the validation program

Infrastructure:

P-1: Basic tools in place to support ASTM E2500 activities
P-2: Integrated systems for managing requirements, risk assessments, and verification activities
P-3: Advanced tools for risk management and data analysis to support decision-making
P-4: Cutting-edge technology leveraged to enhance efficiency and effectiveness of the validation program

Metrics:

P-1: Basic metrics tracked for validation activities
P-2: Comprehensive set of metrics established to measure ASTM E2500 process performance
P-3: Metrics used to drive continuous improvement of the validation program
P-4: Predictive analytics used to anticipate and prevent issues in validation activities

Enterprise Capabilities

Leadership:

E-1: Leadership aware of ASTM E2500 principles
E-2: Leadership actively supports ASTM E2500 implementation
E-3: Leadership drives cultural change to fully embrace risk-based validation approach
E-4: Leadership promotes ASTM E2500 principles beyond the organization, influencing industry standards

Culture:

E-1: Some recognition of the importance of risk-based validation
E-2: Culture of quality and risk-awareness developing across the organization
E-3: Strong culture of scientific thinking and continuous improvement in validation activities
E-4: Innovation in validation approaches encouraged and rewarded

Expertise:

E-1: Basic understanding of ASTM E2500 principles among key staff
E-2: Dedicated team of ASTM E2500 experts established
E-3: Deep expertise in risk-based validation approaches across multiple departments
E-4: Organization recognized as thought leader in ASTM E2500 implementation

Governance:

E-1: Basic governance structure for validation activities in place
E-2: Clear governance model aligning ASTM E2500 with overall quality management system
E-3: Cross-functional governance ensuring consistent application of ASTM E2500 principles
E-4: Governance model that adapts to changing regulatory landscape and emerging best practices

To use this PEMM assessment:

Evaluate your validation program against each enabler and capability, determining the current maturity level (P-1 to P-4 for process enablers, E-1 to E-4 for enterprise capabilities).
Identify areas for improvement based on gaps between current and desired maturity levels.
Develop action plans to address these gaps, focusing on moving to the next maturity level for each enabler and capability.
Regularly reassess the program to track progress and adjust improvement efforts as needed.

Comparison Table

Aspect	BPMM	PEMM
Creator	Object Management Group (OMG)	Dr. Michael Hammer
Purpose	Assess and improve business process maturity	Roadmap and benchmarking for process-centricity
Structure	Five levels: Initial, Managed, Standardized, Predictable, Optimizing	Two components: Process Enablers (P0-P4), Organizational Capabilities (E0-E4)
Focus	Process-centric, incremental improvement	Process enablers and organizational capabilities
Assessment Method	Often requires external appraisers	Designed for self-assessment
Guiding Principles	Standardization, measurement, continuous improvement	Empirical evidence, simplicity, organizational engagement
Applications	Enterprise systems, business process improvement, benchmarking	Process reengineering, organizational engagement, benchmarking

In summary, while both BPMM and PEMM aim to improve business processes, BPMM is more structured and detailed, often requiring external appraisers, and focuses on incremental process improvement across organizational boundaries. In contrast, PEMM is designed for simplicity and self-assessment, emphasizing the role of process enablers and organizational capabilities to foster a supportive environment for process improvement. Both have advantages, and keeping both in mind while developing processes is key.

The Lack of Objectivity in Quality Management

ICH Q9(r1) can be reviewed as a revision that addresses long-standing issues of subjectivity in risk management. Subjectivity is a widespread problem throughout the quality sphere, posing significant challenges because it introduces personal biases, emotions, and opinions into decision-making processes that should ideally be driven by objective data and facts.

Inconsistent Decision-Making: Subjective decision-making can lead to inconsistencies because different individuals may have varying opinions and biases. This inconsistency can result in unpredictable outcomes and make it challenging to establish standardized processes. For example, one manager might prioritize customer satisfaction based on personal experiences, while another might focus on cost-cutting, leading to conflicting strategies within the same organization.
Bias and Emotional Influence: Subjectivity often involves emotional influence, which can cloud judgment and lead to decisions not in the organization’s best interest. For instance, a business owner might make decisions based on a personal attachment to a product or service rather than its market performance or profitability. This emotional bias can prevent the business from making necessary changes or investments, ultimately harming its growth and sustainability.
Risk Management Issues: In risk assessments, subjectivity can significantly impact the identification and evaluation of risks. Subjective assessments may overlook critical risks or overemphasize less significant ones, leading to inadequate risk management strategies. Objective, data-driven risk assessments are essential to accurately identify and mitigate potential threats to the business. See ICHQ9(r1).
Difficulty in Measuring Performance: Subjective criteria are often more complicated to quantify and measure, making it challenging to track performance and progress accurately. Objective metrics, such as key performance indicators (KPIs), provide clear, measurable data that can be used to assess the effectiveness of business processes and make informed decisions.
Potential for Misalignment: Subjective decision-making can lead to misalignment between business goals and outcomes. For example, if subjective opinions drive project management decisions, the project may deviate from its original scope, timeline, or budget, resulting in unmet objectives and dissatisfied stakeholders.
Impact on Team Dynamics: Subjectivity can also affect team dynamics and morale. Decisions perceived as biased or unfair can lead to dissatisfaction and conflict among team members. Objective decision-making, based on transparent criteria and data, helps build trust and ensures that all team members are aligned with the business’s goals.

Every organization I’ve been in has a huge problem with subjectivity, and I’m confident in asserting none of us are doing enough to deal with the lack of objectivity, and we mostly rely on our intuition instead of on objective guidelines that will create unambiguous, holistic, and
universally usable models.

Understand the Decisions We Make

Every day, we make many decisions, sometimes without even noticing it. These decisions fall into four categories:

Acceptances: It is a binary choice between accepting or rejecting;
Choices: Opting for a subset from a group of alternatives;
Constructions: Creating an ideal solution given accessible resources;
Evaluations: Here, commitments back up the statements of worth to act

These decisions can be simple or complex, with manifold criteria and several perspectives. Decision-making is the process of choosing an option among manifold alternatives.

The Fallacy of Expert Immunity is a Major Source of Subjectivity

There is a widely incorrect belief that experts are impartial and immune to biases. However, the truth is that no one is immune to bias, not even experts. In many ways, experts are more susceptible to certain biases. The very making of expertise creates and underpins many of the biases. For example, experience and training make experts engage in more selective attention, use chunking and schemas (typical activities and their sequence), and rely on heuristics and expectations arising from past base rate experiences, utilizing a whole range of top-down cognitive processes that create a priori assumptions and expectations.

These cognitive processes often enable experts to make quick and accurate decisions. However, these mechanisms also create bias that can lead them in the wrong direction. Regardless of the utilities (and vulnerability) of such cognitive processing in experts, they do not make experts immune from bias, and indeed, expertise and experience may actually increase (or even cause) certain biases. Experts across domains are subject to cognitive vulnerabilities.

Even when experts are made aware of and acknowledge their biases, they nevertheless think they can overcome them by mere willpower. This is the illusion of control. Combating and countering these biases requires taking specific steps—willpower alone is inadequate to deal with the various manifestations of bias.

In fact, trying to deal with bias through the illusion of control may actually increase the bias due to “ironic processing” or “ironic rebound.” Hence, trying to minimize bias by willpower makes you think of it more and increases its effect. This is similar to a judge instructing jurors to disregard specific evidence. By doing so, the judge makes the jurors notice this evidence even more.

Such fallacies’ beliefs prevent dealing with biases because they dismiss their powers and existence. We need to acknowledge the impact of biases and understand their sources to take appropriate measures when needed and when possible to combat their effects.

Fallacy	Incorrect Belief
Ethical Issues	It only happens to corrupt and unscrupulous individuals, an issue of morals and personal integrity, a question of personal character.
Bad Apples	It only happens to corrupt and unscrupulous individuals. It is an issue of morals and personal integrity, a question of personal character.
Expert Immunity	Experts are impartial and are not affected because bias does not impact competent experts doing their job with integrity.
Technological Protection	Using technology, instrumentation, automation, or artificial intelligence guarantees protection from human biases.
Blind Spot	Other experts are affected by bias, but not me. I am not biased; it is the other experts who are biased.
Illusion of Control	I am aware that bias impacts me, and therefore, I can control and counter its affect. I can overcome bias by mere willpower.

Six Fallacies that Increase Subjectivity

Mitigating Subjectivity

There are four basic strategies to mitigate the impact of subjectivity.

Data-Driven Decision Making

Utilize data and analytics to inform decisions, reducing reliance on personal opinions and biases.

Establish clear metrics with key performance indicators (KPI), key behavior indicators (KBI), and key risk indicators (KRI) that are aligned with objectives.
Implement robust data collection and analysis systems to gather relevant, high-quality data.
Use data visualization tools to present information in an easily digestible format.
Train employees on data literacy and interpretation to ensure proper use of data insights.
Regularly review and update data sources to maintain relevance and accuracy.

Standardized Processes

Implement standardized processes and procedures to ensure consistency and fairness in decision-making.

Document and formalize decision-making procedures across the organization.
Create standardized templates, checklists, and rubrics for evaluating options and making decisions.
Implement a consistent review and approval process for major decisions.
Regularly audit and update standardized processes to ensure they remain effective and relevant.

Education, Training, and Awareness

Educate and train employees and managers on the importance of objective decision-making and recognizing and minimizing personal biases.

Conduct regular training sessions on cognitive biases and their impact on decision-making.
Provide resources and tools to help employees recognize and mitigate their own biases.
Encourage a culture of open discussion and constructive challenge to promote diverse perspectives.
Implement mentoring programs to share knowledge and best practices for objective decision-making.

Digital Tools

Leverage digital tools and software to automate and streamline processes, reducing the potential for subjective influence. The last two is still more aspiration than reality.

Implement workflow management tools to ensure consistent application of standardized processes.
Use collaboration platforms to facilitate transparent and inclusive decision-making processes.
Adopt decision support systems that use algorithms and machine learning to provide recommendations based on data analysis.
Leverage artificial intelligence and predictive analytics to identify patterns and trends that may not be apparent to human decision-makers.

The Mistake I See in Most Quality Risk Management SOPs

I have a little trick when reviewing a Quality Risk Management SOP. I go to the process/procedure map section, and if I see only the illustration from ICH Q9, I know I am looking at an organization that hasn’t actually thought about risk management.

A risk management process needs more than the methodology behind individual risk management (assess, control, review). It needs to include the following:

Risk Plan: How do you manage risk management holistically? Which systems/processes have living risk assessments? What are your planned reviews? What significant initiatives around quality risk management are included?
Risk Register: How do you manage your entire portfolio of risks? Link to quality management review.
Selection of tools, and even more importantly, development of tools.
Mechanisms and tools for risk treatment
Improvement strategy for the quality risk management program. How do we know if the program is working as intended?
How to define, select, and train risk owners
How to engage the appropriate stakeholders in the risk process

Too many quality risk management SOPs do not read like process or procedure. They read like a regurgitation of ICH Q9 or the ISO31000 documents. Neither is a good thing. You must go deeper and create an executable process to govern the system.

Global versus Local Process and Procedure and the eQMS

Companies both large and small grapple with how and when to create standard work at the global level, while still having the scalability to capture different GXP activity families and product modality.

I’ve discussed before on document hierarchy and on the leveling of process and procedure. It is really important to level your processes, and this architecture should be deliberate and shepherded.

This really gets to the heart of work-as-imagined and prescribed, and the concept of standard work.

Benefits of Standard Work

Ensures all work is done according to the current best practice
Consistency is the essential ingredient of quality
Allows organizations to scale rapidly
Puts the focus on the process and not an individual or team
Makes improvements easier and faster

Global versus Local Process and Procedure in the Document Hierarchy

Most Quality Hierarchies look fairly similar.

Excluding the Program level (which becomes even more important) we can expand the model in the process band to account for global versus local.

Global and local process within the document hierarchy

Quality Manual and Policy remains global with local input and determine the overall structure of the quality management system.

Global Process is created when a process is majority task and role driven at a global level. It is pan-GXP, pan-modality, pan-geography. It is the standard way of work to drive consistency across and through the organization.

Local Process is created when a process is specific to a specific GXP, product modality, geography.

Procedure, which describes the tasks, can be created off of local or global process. When the global process has localizations (a CAPA is a CAPA but how I build action items may differ across sites), I can build local versions off the global process.

For an example, Document and Record Management.

This approach takes real vision among leaders to drive for consistency and simplicity. This activity is a core component in good system design, no matter the size of the organization.

Principle	Description	Application for Global and Local Process
Balance	The system creates value for the multiple stakeholders. While the ideal is to develop a design that maximizes the value for all the key stakeholders, the designer often has to compromise and balance the needs of the various stakeholders.	The value of standard work really shines here.
Congruence	The degree to which the system components are aligned and consistent with each other and the other organizational systems, culture, plans, processes, information, resource decisions, and actions.	We gain congruence through ensuring key processes are at the global level.
Convenience	The system is designed to be as convenient as possible for the participants to implement (a.k.a. user friendly). System includes specific processes, procedures, and controls only when necessary.	The discussion around global versus local will often depend on how you define convenience
Coordination	System components are interconnected and harmonized with the other (internal and external) components, systems, plans, processes, information, and resource decisions toward common action or effort. This is beyond congruence and is achieved when the individual components of a system operate as a fully interconnected unit.	How we ensure coordination across and through an organization.
Elegance	Complexity vs. benefit — the system includes only enough complexity as is necessary to meet the stakeholder’s needs. In other words, keep the design as simple as possible and no more while delivering the desired benefits. It often requires looking at the system in new ways.	Keep this in mind as global for the sake of global is not always the right decision.
Human	Participants in the system are able to find joy, purpose and meaning in their work.	Never forget
Learning	Knowledge management, with opportunities for reflection and learning (learning loops), is designed into the system. Reflection and learning are built into the system at key points to encourage single- and double-loop learning from experience to improve future implementation and to systematically evaluate the design of the system itself.	Building the right knowledge management into the organization is critical to leverage this model
Sustainability	The system effectively meets the near- and long-term needs of the current stakeholders without compromising the ability of future generations of stakeholders to meet their own needs.	Ensure the appropriate tools exist to sustain, including regulatory intelligence. Long-term scalability.

Pillars of Good System Design for Gloval and Local Process

Utilizing the eQMS to drive

The ideal state when implementing (or improving) an eQMS is to establish global processes and allow system functionality to localize as appropriate.

So for example, every CAPA is the same (identify problem and root cause, create plan, implement plan, prove implementation is effective. This is a global process. However, one wants specific task detail at a lower level, for example GMP sites may care about certain fields more the GCP, medical device has specific needs, etc. These local task level needs can be mainted within one workflow.

The Key is Fit-For-Purpose Fit-for-Use

A fit for purpose process meets the requirements of the organization.

A fit for use process is usable throughout the lifecycle.

Global and localizing processes is a key part of making both happen.

Design Problem Solving into the Process

Good processes and systems have ways designed into them to identify when a problem occurs, and ensure it gets the right rigor of problem-solving. A model like Art Smalley’s can be helpful here.

Each and every process should go through the following steps:

Define those problems that should be escalated and those that should not. Everyone working in a process should have the same definition of what is a problem. Often times we end up with a hierarchy of issues that are solved within the process – Level 1 – and those processes that go to a root cause process (deviation/CAPA) – level 2.
Identify the ways to notice a problem. Make the work as visual as possible so it is easier to detect the problem.
Define the escalation method. There should be one clear way to surface a problem. There are many ways to create a signal, but it should be simple, timely, and very clear.

These three elements make up the request for help.

The next two steps make up the response to that request.

Who is the right person to respond? Supervisor? Area management? Process Owner? Quality?
How does the individual respond, and most importantly when? This should be standardized so the other end of that help chain is not wondering whether, when, and in what form that help is going to arrive.

In order for this to work, it is important to identify clear ownership of the problem. There always must be one person clearly accountable, even if only responsible for bits, so they can push the problem forward.

It is easy for problem-solving to stall. So make sure progress is transparent. Knowing what is being worked on, and what is not, is critical.

Prioritization is key. Not every problem needs solving so have a mechanism to ensure the right problems are being solved in the process.