Vision and Psychology Safety Enable Change

Professor Amy Edmondson in 2016 wrote “Wicked-Problem Solvers” in HBR that laid out four leadership levers for collaboration that fit nicely into quality culture and nestle nicely with Kotter’s Eight Accelerators. Together they help define the leadership behaviors necessary to build quality culture, all informed by the enabler of knowledge management.

Levers and Accelerators of change

Professor Edmondson in this article is discussing cross-industry collaboration, but the central four levers apply in any organization.

Having a vision that strives for a True North of Quality is critical. Make it align to individual needs. Remember that vision grows and adapts as you go, and as others get the opportunity to shape. Vision has six criteria:

  1. Stimulus: Vision needs to include actual benefits for those affected by it. String vision brings people together as community, not as strangers. Stimulus means people see themselves in the vision and understand how they will benefit.
  2. Scale: Vision should be of great breadth and depth with potential for extension at later stages. Vision never leads to or accepts a dead end. It shows multiple potentials for expansion.
  3. Spotlight: Vision assumes responsibility, immediate and extended. The greater the vision, then the greater the responsibility for its impact on people’s lives and the legacy that will be left afterwards. This responsibility needs to bring opportunity for people who are involved. This is part of the vision that will drive the volunteer army.
  4. Scanning: A visionary sees the signs on the way to success. Pay attention to to pain points, spot trends and see where and how value can be added. Gemba walks are critical here.
  5. Simplicity: Vision is elegant thinking about complicated and complex things. A vision is not a vision unless it’s understood. Simplicity lets people believe in vision. If the vision is complicated most people will ignore it. Vision operates and makes execution possible from its simplicity. The simpler the vision in its core meaning, the easier it can be shared with employees, customers and partners and thus, easier to scale inside and outside an organization.
  6. Passion: Vision provokes strong emotions. A strong vision is always accompanied by excitement and passion. Excitement equals passion that gives an emotional power to a vision. A strong vision brings strong excitement that is difficult to contain. Strong excitement and passion are highly contagious. A simple and compelling vision excites more passion than any mere goal.

Psychological safety is the state where employees feel that there is safety in taking risks at work setting. In this safe environment employees will engage in risk-taking actions that are inherent to creative endeavors and if they perceive safety, then they are more comfortable to voice their opinions. This safety makes them more willing to take the chances to own the vision and try to experiment with making that vision a reality which motivates them to develop, promote, and implement new ideas.

This safety will enable knowledge sharing, which can come in many different styles, including combination which creates something new.

Through inclusive, democratic leaders who value the inclusion of employees in a particular work process, employees have the chance to raise their voice for generating, promoting, and implementing useful ideas
Through leveraging vision these inclusive leaders exhibit openness attributes that communicates the importance of taking innovative actions and gives employees the guarantee that in case of negative consequences they will not be punished, experiencing greater psychological safety.

Employees experience non-defensive behavior, and feel high levels of self-worth and self-identity, motivating employees not only to generate new ideas, but also to promote and implement new ideas in the organization.

The organization that is structured to accept these ideas will continue to drive iterative cycles of improvement.

Improvisation

Improvisation Takes Practice” in HBR is a great read. When I first read it, I chuckled at how it brings my gamer hobby and my quality practice together.

Employee creativity—the production of novel and useful solutions, procedures, products, and services—is critical to organizational success. I would argue, creativity drives excellence. Improvisation is a key employee behavior that drives creativity and innovation.

Improvisation is essential for navigating volatile, uncertain, and complex environments and dealing with unforeseen obstacles. Improvisation is also key to drawing distinctions, implementing new ideas, and converting knowledge and insights into action in real time. When confronted with critical and disruptive events, employees can resolve challenges by following existing protocols and procedures. In contrast, when faced with novel events, employees cannot rely on routines and conventions to respond. Rather, they will have to shift their focus to new perspectives, features, and behaviors.

The process of building expertise, when practices are assimilated, embodied, and rendered tacit, creates improvisational competence. Improvisation is an important source of action generating learning: people act to make events meaningful and situations understandable and, in the process, deepen their expertise through further learning, becoming reflective practitioners.

As part of knowledge management, today’s improvisations are absorbed and embedded into tomorrow’s routines.

Improvisation leads to better decision making, as I discussed in the post “Yes…but….and

Tacit and Explicit Knowledge

Nonaka classified knowledge as explicit and tacit. This concept has become the center piece of knowledge management and fundamental concept in process improvement.

Explicit knowledge is documented and accepted knowledge. Tacit knowledge stems more from experience and is more undocumented in nature. In spite of being difficult to interpret and transfer, tacit knowledge is regarded as the root of all organizational knowledge.

Tacit knowledge, unlike its explicit counterpart, mostly consists of perceptions and is often unstructured and non-documented in nature. Therefore, mental models, justification of beliefs, heuristics, judgments, “gut feelings” and the communication skills of the individual can influence the quality of tacit knowledge.

The process of creation of knowledge begins with the creation and sharing of tacit knowledge, which stems from socialization, facilitation of experience and interactive capacity of individuals with their coworkers.

Creation and Sharing of Knowledge

Knowledge creation involved organizations and it’s individual transcending the boundaries of the old to the new by acquiring new knowledge, which is considered to be mostly tacit in nature. The key to tacit knowledge sharing lies in the willingness and capacity of individuals to share what they know (knowledge donation) and to use what they learn (knowledge collection).

Knowledge quality is the acquisition of useful and innovative knowledge and is the degree to which people are satisfied with the quality of the shared knowledge and find it useful in accomplishing their activities. The quality of knowledge can be measured by frequency, usefulness and innovativeness, and can be innovative or new for the system or organization. However, if the knowledge is not beneficial to achieving the objective of the objective of the organization then it does not fulfill the criteria of knowledge quality. There are six attributes to knowledge quality: adaptability, innovativeness, applicability, expandability, justifiability and authenticity,

Sources

  • Kaser, P.A. and Miles, R.E. (2002), “Understanding knowledge activists’ successes and failures”, Long Range Planning, Vol. 35 No. 1, pp. 9-28.
  • Kucharska, W. and Dabrowski, J. (2016), “Tacit knowledge sharing and personal branding: how to derive innovation from project teams”, in Proceedings of the11th European Conference on Innovation and Entrepreneurship ECIE, pp. 435-443.
  • Nonaka, I. (1994), “A dynamic theory of organizational knowledge creation”, Organizational Science, Vol. 5 No. 1, pp. 14-37.
  • Nonaka, I. and Takeuchi, H. (1995), The Knowledge-Creating Company, Oxford University Press, New York, NY.
  • Nonaka, I. and Toyama, R. (2003), “The knowledge-creating theory revisited: knowledge creation as a synthesizing process”, Knowledge Management Research and Practice, Vol. 1 No. 1, pp. 2-10.
  • Nonaka, I. and Von Krogh, G. (2009), “Perspective—tacit knowledge and knowledge conversion: controversy and advancement in organizational knowledge creation theory”, Organization Science, Vol. 20 No. 3, pp. 635-652
  • Riege, A. (2005), “Three-dozen knowledge-sharing barriers managers must consider”, Journal of Knowledge Management, Vol. 9 No. 3, pp. 18-35.
  • Smedlund, A. (2008), “The knowledge system of a firm: social capital for explicit, tacit and potential knowledge”, Journal of Knowledge Management, Vol. 12 No. 1, pp. 63-77.
  • Spender, J.C. (1996), “Making knowledge the basis of a dynamic theory of the firm”, Strategic Management Journal, Vol. 17 No. S2, pp. 45-62.
  • Soo, C.W., Devinney, T.M. and Midgley, D.F. (2004), “The role of knowledge quality in firm performance”, In Tsoukas, H. and Mylonopoulus, N. (Eds), Organizations as Knowledge Systems. Knowledge, Learning and Dynamic Capabilities, Palgrave Macmillan, London, pp. 252-275.
  • Sorenson, O., Rivkin, J.W. and Fleming, L. (2006), “Complexity, networks and knowledge flow”, Research Policy, Vol. 35 No. 7, pp. 994-1017.
  • Waheed, M. and Kaur, K. (2016), “Knowledge quality: a review and a revised conceptual model”, Information Development, Vol. 32 No. 3, pp. 271-284.
  • Wang, Z. and Wang, N. (2012), “Knowledge sharing, innovation and firm performance”, Expert Systems with Applications, Vol. 39 No. 10, pp. 8899-8908.

Knowledge Transfer

Our organizations are based on the interactions of individuals, teams and other organizations into a complex adaptive environment. We need to manage productive relationships as part of a complex system and interactions among parts can produce valuable, new, and unpredictable capabilities that are not inherent in any of the parts acting alone. This is why knowledge management, having a learning culture, is such a fundamental part of the work we do.

There are seven major categories we engage in when we manage, maintain, and create knowledge.

ActivityConvertsInvolvingMeaning
SocializationTacit-to-Tacitdifferent agentsSharing of tacit knowledge between individuals
IntrospectionTacit-to-Tacit same agentThe conscious or unconscious examination of one’s own tacit knowledge, as taken at an individual level
ExternalizationTacit-to-Explicitagent to knowledge managementThe expression of tacit knowledge and its translation into comprehensible forms interpretable by external agents
CombinationExplicit-to-ExplicitAll usersThe conversion of explicit knowledge into other variants of explicit knowledge
InternalizationExplicit-to-TacitTraining and deliberate practiceThe conversion of explicit knowledge into tacit knowledge
ConceptualizationAction-to-TacitContinuous ImprovementThe creation of tacit knowledge from aspects related to real work actions.
ReificationTacit-to-ActionProcess/ProcedureThe activity of bringing tacit knowledge into action (e.g. translating a mental model of a process activity into the actual operating tasks)
Knowledge Work Activities

As can be seen in the table above these seven activities involve moving between tacit and explicit knowledge. The apply to both declarative and procedural knowledge.

Examples of tacit and explicit knowledge

Socialization

Socialization is the level of interaction between, and communication of, various actors within an organization, which leads to the building of personal familiarity, improved communication, and problem solving. Often called learning the roles, this is the the process by which an individual acquires the social knowledge and skills necessary to assume an organizational role. Socialization encourages two-way information exchange, builds and establishes relationship trust, and enable transparency of information.

Socialization creates an operating style, enabling people to communicate with each other, have a language that they all understand and behavioral styles that are compatible. It reinforces basic assumptions and shares espoused values by helping create common norms and compatible cultures.

Socialization enables many influencing tactics which makes it critical for change management activities.

Introspection

The exploration of our experiences. Introspection can arise naturally but it can also arise deliberatively, for example journaling.

Introspection can also include retrospection, especially as a group activity. This is the strength of lessons learned.

Externalization

The work of making the tacit explicit. Knowledge management as continuous improvement.

Combination

The combination of knowledge drives innovation and a learning culture. This includes the ability to identify different sources of knowledge, understand different learning processes, and combine internal and external knowledge effectively.

Knowledge combination capability generates through exchange of knowledge between individuals and work teams is a process that allows the transfer of knowledge to the organization and that can be applied to develop and improve products and processes.

Internalization

As we move towards qualification we internalize knowledge.

Conceptualization

The insights gained from doing and observing work. Deliberative learning.

Reification

The process of translating work-as-imagined into work-as-done through work-as-prescribed on a continuous loop of improvement. The realm of transformative learning.

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 other quality systems. Understanding these interrelationships, ensuring knowledge is appropriate, captured, and utilized, is a big way we improve and thrive.