The Building Blocks of Work-as-Prescribed

Work-as-Prescribed – how we translate the desired activities into a set of process and procedure – relies on an understanding of how people think and process information.

The format is pivotal. The difficulties we have in quality are really not much different from elsewhere in society in that we are surrounded by confusing documentation and poorly presented explanations everywhere we look, that provide information but not understanding. Oftentimes we rely on canards of “this is what is expected,” “this is what works” – but rarely is that based on anything more than anecdotal. And as the high incidence of issues and the high cost of training shows, less than adequate.

There is a huge body-of-knowledge out there on cognitive-friendly design of visuals, including documentation. This is an area we as a quality profession need to get comfortable with. Most important, we need to give ourselves permission to adapt, modify and transform the information we need into a shape that aids understanding and makes everyone a better thinker.

Work-as-Prescribed (and work-as-instructed) is the creation of tools and technologies to help us think better, understand more and perform at our peak.

Locus of Understanding

Looking at the process at the right level is key. Think of Work-as-Prescribed as a lens. Sometimes you need a high-powered lens so that you can zoom in on a single task. Other times, you need to zoom out to see a set of tasks, a whole process, or how systems interact.

This is the locus of understanding, where understanding happens. When we take this position, we see how understanding is created. Adopting the locus of understanding means going to the right level for the problem at hand. When we apply it to Work-as-Prescribed we are applying the same principles as we do in problem-solving to developing the right tools to govern the work.

We are conducting knowledge management as part of our continuous improvement.

An important way to look is distributed cognitive resources, which means anything that contributes to the cognitive work being done. Adjusting the locus of understanding means that you can, and should, treat an SOP as a cognitive resource. Some of the memory is in your head and some is in the SOP. Work-as-prescribed is a cognitive resource that we distribute, routinely and casually across the brain and our quality system in the form of documents and other execution aids.

Other tools, like my favorite whiteboard, also serve as distributed cognitive resources.

So, as our documents and other tools are distributed cognitive resources it behooves us to ensure they are based on the best cognitive principles possible to drive the most benefit.

As an aside, there is a whole line of thought about why some physical objects are better at distributed cognitive resources than electronic. Movement actually matters.

Taking it even further (shifting the locus) we can see the entire quality system as a part of a single distributed cognitive system where cognitive work is performed via the cognitive functions of communicating, deciding, planning, and problem-solving. These cognitive functions are supported by cognitive processes such as perceiving, analyzing, exchanging, and manipulating.

Cognitive Activity in Work-As-Prescribed

The tools we develop to provide distributed cognitive activity strive to:

Provide short-term or long-term memory aids so that memory load can be reduced.
Provide information that can be directly perceived and used such that little effort is needed to interpret and formulate the information explicitly.
Provide knowledge and skills that are unavailable from internal representations.
Support perceptual operators that can recognize features easily and make inferences directly.
Anchor and structure cognitive behavior without conscious awareness.
Change the nature of a task by generating more efficient action sequences.
Stop time and support perceptual rehearsal to make invisible and transient information visible and sustainable.
Aid processibility by limiting abstraction.
Determine decision making strategies through accuracy maximization and effort minimization.

Driving Work-As Prescribed

As we build our requirements documents, our process and procedure, there are a few principles to keep in mind to better tap into distributed cognitive resources.

Plan for the flow of information: Think about paths, relationships, seams, edges and other hand-offs. Focus on the flow of information. Remember that we learn in a spiral, and the content needed for a novice is different from that of an expert and build our documents and the information flow accordingly. This principle is called Sequencing.

Break information down into pieces: Called, Chunking, the grouping together of information into ideally sized pieces. When building Work-As-Prescribed pay close attention to which of these chunks are reusable and build accordingly.

The deeply about context: How a tool is used drives what the tool should be.

Think deeply about information structures: Not all information is the same, not every example of Work-as-Prescribed should have the same structure.

Be conscientious about the digital and physical divide: Look for opportunities to integrate or connect these two worlds. Be honest of how enmeshed they are at any point in the system.

We are building our Work-as-Prescribed through leveraging our quality culture, our framework for coordinating work. Pay attention to:

Shared Standards – Ways we communicate
Invisible Environments – Ways we align, conceptually
Visible Environments – Ways we collaborate
Psychological Safety – Ways we behave
Perspectives – Ways we see (and see differently)

Principles in Practice

When design process, procedure and task documentation leverage this principles by build blocks, or microcontent, that is:

about one primary idea, fact, or concept
easily scannable
labeled for clear identification and meaning, and
appropriately written and formatted for use anywhere and any time it is needed.

There is a common miscomprehension that simple means short. That just isn’t true. Simple means that it passes a test for the appropriateness of the size of a piece of content of providing sufficient details to answer a specific question for the targeted audience. The size of the content must effectively serve its intended purpose with efficiency, stripping off any unnecessary components.

We need to strive to apply cognitive thinking principles to our practice. The day of judging a requirements document by its page length is long over.

Constituents of cognitive thinking applied to Work-As-Prescribed

Managing Events Systematically

Being good at problem-solving is critical to success in an organization. I’ve written quite a bit on problem-solving, but here I want to tackle the amount of effort we should apply.

Not all problems should be treated the same. There are also levels of problems. And these two aspects can contribute to some poor problem-solving practices.

It helps to look at problems systematically across our organization. The iceberg analogy is a pretty popular way to break this done focusing on Events, Patterns, Underlying Structure, and Mental Model.

Events

Events start with the observation or discovery of a situation that is different in some way. What is being observed is a symptom and we want to quickly identify the problem and then determine the effort needed to address it.

This is where Art Smalley’s Four Types of Problems comes in handy to help us take a risk-based approach to determining our level of effort.

Type 1 problems, Troubleshooting, allows us to set problems with a clear understanding of the issue and a clear pathway. Have a flat tire? Fix it. Have a document error, fix it using good documentation practices.

It is valuable to work the way through common troubleshooting and ensure the appropriate linkages between the different processes, to ensure a system-wide approach to problem solving.

Corrective maintenance is a great example of troubleshooting as it involved restoring the original state of an asset. It includes documentation, a return to service and analysis of data. From that analysis of data problems are identified which require going deeper into problem-solving. It should have appropriate tie-ins to evaluate when the impact of an asset breaking leads to other problems (for example, impact to product) which can also require additional problem-solving.

It can be helpful for the organization to build decision trees that can help folks decide if a given problem stays as troubleshooting or if it it also requires going to type 2, “gap from standard.”

Type 2 problems, gap from standard, means that the actual result does not meet the expected and there is a potential of not meeting the core requirements (objectives) of the process, product, or service. This is the place we start deeper problem-solving, including root cause analysis.

Please note that often troubleshooting is done in a type 2 problem. We often call that a correction. If the bioreactor cannot maintain temperature during a run, that is a type 2 problem but I am certainly going to immediately apply troubleshooting as well. This is called a correction.

Take documentation errors. There is a practice in place, part of good documentation practices, for addressing troubleshooting around documents (how to correct, how to record a comment, etc). By working through the various ways documentation can go wrong, applying which ones are solved through troubleshooting and don’t involve type 2 problems, we can create a lot of noise in our system.

Trends/Patterns

Core to the quality system is trending, looking for possible signals that require additional effort. Trending can help determine where problems lay and can also drive up the level of effort necessary.

Underlying Structure

Root Cause Analysis is about finding the underlying structure of the problem that defines the work applied to a type 2 problem.

Not all problems require the same amount of effort, and type 2 problems really have a scale based on consequences, that can help drive the level of effort. This should be based on the impact to the organization’s ability to meet the quality objectives, the requirements behind the product or service.

For example, in the pharma world there are three major criteria:

safety, rights, or well-being of patients (including subjects and participants human and non-human)
data integrity (includes confidence in the results, outcome, or decision dependent on the data)
ability to meet regulatory requirements (which stem from but can be a lot broader than the first two)

These three criteria can be sliced and diced a lot of ways, but serve our example well.

To these three criteria we add a scale of possible harm to derive our criticality, an example can look like this:

Classification	Description
Critical	The event has resulted in, or is clearly likely to result in, any one of the following outcomes: significant harm to the safety, rights, or well-being of subjects or participants (human or non-human), or patients; compromised data integrity to the extent that confidence in the results, outcome, or decision dependent on the data is significantly impacted; or regulatory action against the company.
Major	The event(s), were they to persist over time or become more serious, could potentially, though not imminently, result in any one of the following outcomes: harm to the safety, rights, or well-being of subjects or participants (human or non-human), or patients; compromised data integrity to the extent that confidence in the results, outcome, or decision dependent on the data is significantly impacted.
Minor	An isolated or recurring triggering event that does not otherwise meet the definitions of Critical or Major quality impacts.

Example of Classification of Events in a Pharmaceutical Quality System

This level of classification will drive the level of effort on the investigation, as well as drive if the CAPA addresses underlying structures alone or drives to addressing the mental models and thus driving culture change.

Mental Model

Here is where we address building a quality culture. In CAPA lingo this is usually more a preventive action than a corrective action. In the simplest of terms, corrective actions is address the underlying structures of the problem in the process/asset where the event happened. Preventive actions deal with underlying structures in other (usually related) process/assets or get to the Mindsets that allowed the underlying structures to exist in the first place.

By applying this system perspective to our problem solving, by realizing that not everything needs a complete rebuild of the foundation, by looking holistically across our systems, we can ensure that we are driving a level of effort to truly build the house of quality.

Risk Management is our Ability to Anticipate

Risk assessment is a pillar of the quality system because it gives us the ability to anticipate in a consistent manner. It is built on some fundamental criteria:

Criteria	Asks	Ensure
Expertise	What sort of expertise is relied upon to look into the future	Diversity in expertise. Drive out subjectivity
Frequency	How often are future threats and opportunities assessed?	Living risk assessments, cycles of review.
Communication	How are the expectations of future events communicated or shared within the system?	Risk register. Knowledge management. Continuous improvement. Management review
Strategy	What is the model of the future	Sensemaking
Time horizon	How far ahead does the system look ahead? Is the time horizon different for different organization areas?	System building
Acceptability of Risks	Which risks are considered acceptable and which unacceptable? On which basis?	Controls
Culture	Is risk awareness part of the organizational culture?	Risk-based-thinking. Mindset

Anticipation Criteria to apply to Risk Management

Documents and the Heart of the Quality System

A month back on LinkedIn I complained about a professional society pushing the idea of a document-free quality management system. This has got to be one of my favorite pet peeves that come from Industry 4.0 proponents, and it demonstrates a fundamental failure to understand core concepts. And frankly one of the reasons why many Industry/Quality/Pharma 4.0 initiatives truly fail to deliver. Unfortunately, I didn’t follow through with my idea of proposing a session to that conference, so instead here are my thoughts.

Fundamentally, documents are the lifeblood of an organization. But paper is not. This is where folks get confused. But fundamentally, this confusion is also limiting us.

Let’s go back to basics, which I covered in my 2018 post on document management.

When talking about documents, we really should talk about function and not just by name or type. This allows us to think more broadly about our documents and how they function as the lifeblood.

There are three types of documents:

Functional Documents provide instructions so people can perform tasks and make decisions safely effectively, compliantly, and consistently. This usually includes things like procedures, process instructions, protocols, methods, and specifications. Many of these need some sort of training decision. Functional documents should involve a process to ensure they are up-to-date, especially in relation to current practices and relevant standards (periodic review)
Records provide evidence that actions were taken, and decisions were made in keeping with procedures. This includes batch manufacturing records, logbooks and laboratory data sheets and notebooks. Records are a popular target for electronic alternatives.
Reports provide specific information on a particular topic on a formal, standardized way. Reports may include data summaries, findings, and actions to be taken.

The beating heart of our quality system brings us from functional to record to reports in a cycle of continuous improvement.

Functional documents are how we realize requirements, that is the needs and expectations of our organization. There are multiple ways to serve up the functional documents, the big three being paper, paper-on-glass, and some sort of execution system. That last, an execution system, united function with record, which is a big chunk of the promise of an execution system.

The maturation mind is to go from mostly paper execution, to paper-on-glass, to end-to-end integration and execution to drive up reliability and drive out error. But at the heart, we still have functional documents, records, and reports. Paper goes, but the document is there.

So how is this failing us?

Any process is a way to realize a set of requirements. Those requirements come from external (regulations, standards, etc) and internal (efficiency, business needs) sources. We then meet those requirements through People, Procedure, Principles, and Technology. They are interlinked and strive to deliver efficiency, effectiveness, and excellence.

So this failure to understand documents means we think we can solve this through a single technology application. an eQMS will solve problems in quality events, a LIMS for the lab, an MES for manufacturing. Each of these is a lever for change but alone cannot drive the results we want.

Because of the limitations of this thought process we get systems designed for yesterday’s problems, instead of thinking through towards tomorrow.

We get documentation systems that think of functional documents pretty much the same way we thought of them 30 years ago, as discrete things. These discrete things then interact through a gap with our electronic systems. There is little traceability, which complicates change control and makes it difficult to train experts. The funny thing, is we have the pieces, but because of the limitations of our technology we aren’t leveraging them.

The v-model approach should be leveraged in a risk-based manner to the design of our full system, and not just our technical aspects.

System feasibility matches policy and governance, user requirements allow us to trace to what elements are people, procedure, principles, and/or technology. Everything then stems from there.

Quality-as-Imagined versus Quality-as-Done

Assumptions about how work is carried out is often very different from the reality of the work. This is the difference between work-as-imagined and work-as-done. Assumptions about work as imagined often turn out to be wrong because they are based on a fundamental misunderstanding. Steven Shorrock on Humanistic Systems has been doing a great series on proxies for work-as-done that I recommend you read for more details.

The complexity of our organizations implies a certain level of inevitable unexpected variability and thus a gap between Work-as-Imagined and Work-as-Done. Work-as-Imagined reflects how work is understood by those who are separated from it by time or space; it is an over-simplified version of what is actually going on. Work-as-Done takes account of what it means to function effectively, despite resource-constrained circumstances. The analysis of the gap between Work-As-Imagined and Work-as-Done usually indicates that performance variability is present in both desired and undesired outcomes and, therefore, successful outcomes do not necessarily occur because people are behaving according to Work-as-Imagined.

The same concept applies to the nature and implications of the gap between the prescribed quality practices and policies, Quality-as-Imagined, and the way they are deployed in practice, Quality-as-Done.

This gap should be no surprise. Our organizations are complex systems, and complexity can give rise to unintended consequences.

The interesting thing is that quality can drive a reduction of that gap, solving for complexity.

	Dynamic Interactions	Wide Diversity	Unexpected Variability	Resilience
Social	Interactions between employees	Employees with varying skill levels Employee turnover Diversity of functions performed by employees (e.g. multiskilling)	Errors when operating equipment and tools Unexpected behaviors Absenteeism Variability in human labor demand Unexpected outcomes from social interactions (e.g. conflicts and alliances)	Employees’ ability to anticipate risks Critical analysis of data Informal agreements between workers to distribute the workload
Technical	Interactions between production resources Interactions due to tightly coupled operations (e.g. time constraints, low inventories, capacity constraints)	Product diversity Diversity of quality requirements Diversity of client requirements	Technical disruptions Resource availability (e.g. maintenance staff) Variability in production times (e.g. cycle time, lead time) Dimensional variability (e.g. potential for defects)	Inspection readiness Corrective, preventive and predictive measures
Work Organization	Interactions between information sources Interactions between functions Interactions between processes Interactions between performance indicators	Diversity in managerial controls Diversity in relationships with external agents Diversity of rules and procedures	Variability in the hiring of new workers Changing priorities (e.g. frequent rescheduling due to unexpected conditions) Variability in timing and accuracy of information	Negotiation, partnership and bargaining power with suppliers and clients Investments on new resources Multidisciplinary problem-solving meetings
External Environment	Interactions between the organization, suppliers, and clients Interactions with regulatory bodies	Diversity in suppliers Diversity in clients	Variability in Demand/Need Variability in logistics	Capacity and slack management

Examples of Complexity Impact