Seven elements of good problem-solving

Logic

Perhaps more than anything else, we want our people to be able to think and then act rationally in decision making and problem-solving. The basic structure and technique embodied in problem solving is a combination of discipline when executing PDCA mixed with a heavy dose of the scientific method of investigation.

Logical thinking is tremendously powerful because it creates consistent, socially constructed approaches to problems, so that members within the organization spend less time spinning their wheels or trying to figure out how another person is approaching a given situation. This is an important dynamic necessary for quality culture.

The right processes and tools reinforce this as the underlying thinking pattern, helping to promote and reinforce logical thought processes that are thorough and address all important details, consider numerous potential avenues, take into account the effects of implementation, anticipate possible stumbling blocks, and incorporate contingencies. The processes apply to issues of goal setting, policymaking, and daily decision making just as much as they do to problem-solving.

Objectivity

Because human observation is inherently subjective, every person sees the world a little bit differently. The mental representations of the reality people experience can be quite different, and each tends to believe their representation is the “right” one. Individuals within an organization usually have enough common understanding that they can communicate and work together to get things done. But quite often, when they get into the details of the situation, the common understanding starts to break down, and the differences in how we see reality become apparent.

Problem-solving involves reconciling those multiple viewpoints – a view of the situation that includes multiple perspectives tends to be more objective than any single viewpoint. We start with one picture of the situation and make it explicit so that we can better share it with others and test it. Collecting quantitative (that is, objective) facts and discussing this picture with others is a key way in verifying that the picture is accurate. If it is not, appropriate adjustments are made until it is an accurate representation of a co-constructed reality. In other words, it is a co-constructed representation of a co-constructed reality.

Objectivity is a central component to the problem solving mindset. Effective problem-solvers continually test their understanding of a situation for assumptions, biases, and misconceptions. The process begins by framing the problem with relevant facts and details, as objectively as possible. Furthermore, suggested remedies or recommended courses of action should promote the organizational good, not (even if subconsciously) personal agendas.

Results and Process

Results are not favored over the process used to achieve them, nor is process elevated above results. Both are necessary and critical to an effective organization.

Synthesis, Distillation and and Visualization

We want to drive synthesis of the learning acquired in the course of understanding a problem or opportunity and discussing it with others. Through this multiple pieces of information from different sources are integrated into a coherent picture of the situation and recommended future action.

Visual thinking plays a vital role in conveying information and the act of creating the visualization aids the synthesis and distillation process.

Alignment

Effective implementation of a change often hinges on obtaining prior consensus among the parties involved. With consensus, everyone pulls together to overcome obstacles and make the change happen. Problem-solving teams communicates horizontally with other groups in the organization possibly affected by the proposed change and incorporates their concerns into the solution. The team also communicates vertically with individuals who are on the front lines to see how they may be affected, and with managers up the hierarchy to determine whether any broader issues have not been addressed. Finally, it is important that the history of the situation be taken into account, including past remedies, and that recommendations for action consider possible exigencies that may occur in the future. Taking all these into consideration will result in mutually agreeable, innovative solutions.

Coherency and Consistency

Problem-solving efforts are sometimes ineffective simply because the problem-solvers do not maintain coherency. They tackle problems that are not important to the organization’s goals, propose solutions that do not address the root causes, or even outline implementation plans that leave out key pieces of the proposed solution. So coherency within the problem-solving approach is paramount to effective problem resolution.

Consistent approaches to problem-solving speed up communication and aid in establishing shared understanding. Organizational members understand the implicit logic of the approach, so they can anticipate and offer information that will be helpful to the problem-solvers as they move through the process.

Systems Thinking

Good system thinking means good problem-solving.

Coherence and Quality

Sonja Blignaut on More Beyond wrote a good post “All that jazz … making coherence coherent” on coherence where she states at the end “In order to remain competitive and thrive in the new world of work, we need to focus our organisation design, leadership and strategic efforts on the complex contexts and create the conditions for coherence. “

Ms. Blignaut defines coherence mainly through analogy and metaphor, so I strongly recommend reading the original post.

In my post “Forget the technology, Quality 4.0 is all about thinking” I spelled out some principles of system design.

PrincipleDescription
BalanceThe 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.
CongruenceThe 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.
ConvenienceThe 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.
CoordinationSystem 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.
EleganceComplexity 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.
HumanParticipants in the system are able to find joy, purpose and meaning in their work.
LearningKnowledge 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.
SustainabilityThe 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.

I used the term congruence to summarize the point Ms. Blignaut is reaching with alignment and coherence. I love her putting these against the Cynefin framework, it makes a great of sense to see alignment for the obvious domain and the need for coherence driving from complexity.

So what might driving for coherence look like? Well if we start with coherence being the long range order (the jazz analogy) we are building systems that build order through their function – they learn and are sustainable.

To apply this in the framework of ICHQ10 or the US FDA’s “Guidance for Industry Quality Systems Approach to Pharmaceutical CGMP Regulations” one way to drive for coherence is to use similar building blocks across our systems: risk management, data integrity and knowledge management are all examples of that.