Effective Change Management

Both Curious Cat and A Lean Journey tell me that the ASQ Influential Voices blogs are covering change management. I do love a good blog carnival, and change management is sort of my thing, so I am going to jump in.

It’s often said that people don’t resist “change” so much as they resist “being changed.” So, the job of change management is clear: In a nutshell, you must explain why the affected people should want to change, and thereby cultivate readiness instead of resistance.

 What are some recommended strategies or tactics to help achieve successful change management?

My first piece, of advice, abandon the idea that change management only involves people. Just as all systems are made of people, organization, process and technology; all changes impact all four and need to be viewed holistically.

Second, get rid of the artificial barriers between change management and change control. Change management is the how of change – assess, handle and release. Change control is the what, the execution steps. Remember that all changes are really just projects, and vice versa. The level of change determines the level of activity.

Level of Change Change Management Change Control
Transactional Minor Few

Closely clustered

Operational Major Several

Across several areas

Transformational Fundamental Many

Iterative

Often in waves

Simplify your variety of change controls and strive for scalability within one change management (and control) system. Utilize the levers, which include: regulatory (compliance), product release and risk.

Knowledge Management

Change Management and Knowledge Management are closely entwined. An effective change management system includes active knowledge management, in which information from multiple sources is integrated to identify stimuli for changes needed to improve product and/or process robustness.

There are key interactions with document management and training.

Risk Management

Risk management enables changes and helps assess:

  • The proposed change
  • The effectiveness of the change once implemented

Change Is

Propose the Change

curent and future

Make it SMART:

  • Specific – The proposal needs to be accurate and leave no doubt as to what the change will achieve.
  • Measurable – How will the system owner (sponsor) know when the project is complete.
  • Achievable – Make the change as small as possible after all it is easier to eat an elephant one bite at a time. It is far easier to manage a few smaller change than one big one. This is why operational and transformational changes are many changes and often iterative.
  • Realistic – Make the change easy to deliver, if it is over complicated then it is likely to hit problems and run over budget, be delivered late or of poor quality.
  • Timely – Does the change have to be complete by a certain date? If so put it in the scope that the project has to be complete by that date. Are there dependencies and independencies?

Evaluate

The change Project team leverages SMEs to harness the collective intelligence (synergy) for the benefit of the site.

  • Relevancy – The information gathered is of value
  • Reliability – The process by which the information is collected should be consistent
  • Accuracy – The data should be expressed in a manner that most accurately reflects its information content
  • Efficiency – The design and implementation of the tasks should minimize the burden

Evaluates all four areas (process, technology, people and organization). Includes communication of the change and training.

Vision Importance
What is the vision for this change Why is this change important to our organization
Success Measurements Process Measurements
How will we measure success How will we show progress towards our vision?
Who and what is affected?
What people, departments and processes need to change in order to realize our vision?
How will we support people?
What actions will we do to support people through the change?
What is our plan?
Detailed action plan

Build in effectiveness reviews to your plan.

Implement

Execute the change plan, provide evidence of completion. Escalate significant risks or delays.

Close

Ensure change plan was executed and benefits realized.

Hold a lessons learned.

lessons learned

Conclusion

Change management is a system. It should have its own cycles of improvement and grow as you execute changes. Change is a fundamental pillar of a quality system and spending the time to build a robust system will reap dividends and prove itself a good idea again and again.

 

 

FDA issues new guidance on Post Approval Changes

This past week the FDA issued a draft guidance “Post Approval Changes to Drug Substances” from the Center for Drug Evaluation and Research on post-approval changes for drug substances to provide clarity to holders of drug master files and holders of new and generic drug applications on which reporting category manufacturing changes fall into as well as the information required to support these changes.

Like any guidance this is supposed to “describe the Agency’s current thinking on a topic” and in this case this is a pretty important guidance as it is the first on the subject of change management published after the draft of Q12. It also clearly builds on the concepts of Q11 and is the first time the agency has published a guidance on drug substance post approval changes.

The guidance covers changes to facility; scale and equipment changes; specification changes to starting materials; synthetic manufacturing process changes; and, changes to the container closure systems for the drug substance.

It uses the traditional breakdown of major changes (prior approval supplement category), Moderate changes (changes-being-effected-30 (CBE-30) category) and Minor changes (annual report).

The guidance provides some solid requirements for risk assessments, and requires the risk assessment be included with the filing of change. This will require some companies to improve their risk management process, and may cause some to question decision making about their internal formulas for level of effort and the formality of risk management.

The deadline for public comment on the draft is Nov. 13. Submit comments to the docket at: https://www.regulations.gov/docket?D=FDA-2018-D-3152.

Sometimes quality requires forgetting

DeHolan and Phillips introduced the concept of organizational forgetting to our concepts of knowledge management. While unintentional forgetting is something we usually want to avoid, there is a time when we want to intentionally forget.  Perhaps after a corporate merger we are combining systems or replacing systems. Perhaps it is the result of a large step forward in technology, or an out-right replacement. Some major cultural transformation comes along. And the last thing we want is for no-one to be able to forget the old. For those concepts to linger in our memory and our decisions. For that is a risk that can easily lead to deviations.

 

4529-si1-lo8

Take for example changes in document numbering. Fairly simple of the surface but remember that procedure number is the tag which we use in conversation. No-one ever gives the whole title; we throw around these tags left and right and for our own coded language (another topic worthy of a blog post). Then we change our numbering format and a year later everyone still uses the old number. And mistakes start creeping up. Or just the perception of mistakes builds. Or perhaps everyone still thinks in the manner of the old ERP’s logic, and forget to do crucial aspects of master data management when a change is made. You get the idea

This purposeful frogetting, an aspect of knowledge management (and change management) – that of the purposeful removal of knowledge — is a critical step in our systematic approach and an important part of our strategic toolkit. However, it is very difficult, as deeply embedded pieces of organizational knowledge are generally locked in place by various other pieces of organizational knowledge that depend on them, and removing one implies modifying the others as well. We need to develop the tools to dismantle the previous way of doing work — the unneeded routines and formerly dominant logics of our changed systems.

One of the best way to do this is to get rid of cues. All the little breadcrumbs left behind. If you want people to stop using old document numbers, ensure that no document folks would use on their daily basis has those numbers. However, this ideal model of radical elimination of all cues associated with the old routine seems rather unlikely in all changes from old to new . So when we are working on our change its important to select those cues that will have the biggest bang for our buck. Some general ideas to help inform this are:

  • Look for opportunities to drive out mix-messages – aim for consistency in message
  • Ensure there are positive reinforcements for use of the new routine
  • Actively constrain the to-be-forgotten activity. Reduce the time in two different processes. Do a radical transformation. Reduce the confusion.
  • Reward the individual for participating in the new way. The group can’t change faster than the sum of the individuals, so incentive the change.

When doing a change it is important to consider these as risks, and build into your change plan. Incorporate into your training. For the basis of your communications. Drive out the old, embrace the new. Otherwise you are just increasing the risks inherent in your new way of working. But like many aspects of change management, easy in concept, difficult in execution.

Document Management

Today many companies are going digital, striving for paperless, reinventing how individuals find information, record data and make decisions. It is often good when undergoing these decisions to go back to basics and make sure we are all on the same page before we proceed.

When talking about document management we are really discussing three major types or functions:

  • 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.

Often times these types are all engaged in a lifecycle. An SOP directs us to write a protocol (two documents), we execute the protocol (a record) and then write a report. This fluidity allows us to combine the types.

Throughout these types we need to apply good change management and data integrity practices (ALCOA).

All of these types follow a very similar path for their lifecycle.

document lifecycle

Everything we do is risk based. Some questions to ask when developing and improving this system include:

  • What are the risks of writing procedures at a “low level of detail versus a high level of detail) how much variability do we allow individuals performing a task?) – Both have advantages, both have disadvantages and it is not a one-sized fits all approach.
  • What are the risks in verifying (witnessing) non-critical tasks? How do we identify critical tasks?
  • What are the risks in not having evidence that a procedure-defined task was completed?
  • What are the risks in relation to archiving and documentation retrieval?

There is very little difference between paper records and documents and electronic records and documents as far as what is given above. Electronic records require the same concerns around generation, distribution and maintenance. Just now you are looking at a different set of safeguards and activities to make it happen.

What Closing A Government Radio Station Would Mean For Your Clocks – Start contingency planning

Many clocks sync with a government radio station that’s been proposed to be closed. Scott Simon talks with Thomas Witherspoon of the website The SWLing Post.
— Read on www.npr.org/2018/08/25/641835302/what-closing-a-government-radio-station-would-mean-for-your-clocks

NIST’s full Fiscal Year (FY) 2019 budget request to Congress calls for the agency to “discontinue the dissemination of the US time and frequency via the NIST radio stations in Hawaii and Fort Collins, Colorado.” The agency noted, “These radio stations transmit signals that are used to synchronize consumer electronic products like wall clocks, clock radios, and wristwatches, and may be used in other applications like appliances, cameras, and irrigation controllers.” The specific cut, which would come from the NIST Fundamental Measurement, Quantum Science, and Measurement Dissemination budget, would amount to $6.3 million.

This is the type of thing to add to your SWOTs and other risk management/contingency planning activities. I, too, would like to have confidence it will not be in the final bill, but now is the time to take appropriate actions for your organization.

Knowledge management as continuous improvement

An effective change management system includes active knowledge management, leveraging existing process and product knowledge; capturing new knowledge gained during implementation of the change; and, transferring that knowledge in appropriate ways to all stakeholders.

Any quality system (any system) has as part of it’s major function transforming data into information; the acquisition and creation of knowledge; and the dissemination and using information and knowledge. A main pipe of process improvement is how to implicit knowledge and make it explicit. This is one of the reasons we spend so much time developing standardized work.

And yet I, like many quality professionals, have found myself sitting at a table or standing in front of a visual management board, and have some type of leader ask why we spend so much time training when we should be able to hire anyone with an appropriate level of experience and have them just do the job.

Systems are made up of four things – process, organization, people and technology. When folks think of change management, or root cause analysis, or similar quality processes and tools they tend to think the system is only about the activity we are engaging in. But change management (or root cause analysis or data integrity) is not that simple.

This is really two-fold. A person assessing a change is not just needing to be knowledgeable about how the change control process works, they need to be able to analyze the change to each and every process within the systems they represent, to understand how moving the levers and adjusting the buffers within this change influences each and everything they do, even it that’s to be able to make a concrete and definitive no impact statement.

So when we process improve our change management system (or similar quality processes) we are both improving how we manage change and how folks apply that thinking to all their other activities.

In less mature systems we end up having a lot of tacit knowledge in one person. You have that great SME who understands master data in the ERP and how changes impact it. In way to transfer that tacit knowledge to another person is a lot of socialization. It is experiential, active and a “living thing,” involving capturing knowledge by spending a lot of time with that person and having shared experience, which results in acquired skills and common mental models.

For example, my master-data guru needs to be involved in each and every change that might possibly involve the ERP or master-data. I might have reached the point where the procedure has large sections that give detailed instructions on when to involve the master-data guru in a change. The master-data guru spends a lot of time justifying no-impact. Otherwise I might be having change after change forget to update master data. Which leads to deviations.

At this stage of maturity I’ve recognized I need a master data guru. I’ve identified the individual(s). Depending on maturity I either involve the master-data guru on every change or I’ve advanced enough that I have a decision tool that drives changes to the master-data guru.

So now either the master-data guru is becoming a pain point or we’ve had one too many changes that led to deviations because we failed to change master data in the ERP correctly. So we enter a process improvement cycle.

What we need to do here is make the master-data guru’s tacit knowledge explicit; we need to externalize this knowledge. We start building the tools that better define what never has impact, what always has impact, and what might have impact or be really unique. When a change has no impact, the change owner is able to note that and move on (no master-data guru involvement necessary). When it has definite impact the change owner is able to identify the actions required, knowing exactly what procedures to follow and how to execute those within a change. We still have a set of changes that will trigger the master-data guru’s involvement, but those are smaller in number and more complex in scope.

The steps we took to get here also allow us to more easily develop and train master-data gurus. Maybe we have a skills matrix and it is on development plans. Our training program now has the tools to allow internalization, the process of understanding and absorbing explicit knowledge into tacit knowledge held by the individual.

At this point I have the tools for my average change owner to know when to change master data and how-to-do it (this might not involve them actually doing master data management it is really knowing when to execute, and the outputs from and inputs back into the change management system) AND I have better mechanisms for producing master data experts. That’s the beauty here, the knowledge level required to execute change management properly is usually an expert level competency. By making that knowledge explicit I am serving multiple processes and interrelated systems.

Knowledge management Circular_Process_6_Stages (for expansion)

To breakdown the process:

  1. Capture all the knowledge. Interview the SME(s), evaluate the use of the system, gather together all the procedures and training and user manuals and power point slides
  2. Assess what is valuable, what needs to be transferred
  3. Share this knowledge, make sure others can understand it
  4. Contextualize into standard tools (job aids, user guides, checklists, templates, etc.)
  5. Apply the knowledge. Train others and also update your system processes (and maybe technology) to make sure the knowledge is used.
  6. Update – make sure the knowledge is sustained and regularly updated.

Change management has lots of inputs and outputs. As does data integrity and may other quality systems. Understanding these interrelationships, ensuring knowledge is appropriate captured and utilized, is a big way we improve and thrive.