Hire a Know-* Team to build a great Customer Experience

Created by Chris Shayan
Oct 19, 2019
6 min read

In my previous posts, I have shared blogs on mental models (gentle warning, it is a pretty long article) that has helped my to think better and also shared an article on how to engineer and architect an experience for customers, users, and employees. However, before engineering a great experience, you will need to build a great internal team. In this blog post, I am talking more on what kind of team is needed in your back office in order to engineer and architect an experience successfully.

If you are looking for a shortcut, here you are; these are the 10 traits that your team should have in common but if you are interested in deep thinking of this model continue to read the whole article:

  1. curiosity about wide variety of subjects

  2. being aware of situations where they can use systematic/critical thinking

  3. confidence in their own reasoning

  4. commitment to being well-informed

  5. understanding other's opinions

  6. openness to revisit beliefs

  7. objectivity in assessing reasoning

  8. self-aware of own cognitive biases and thinking flaws

  9. careful judgement when changing opinions and

  10. changing when an argument is well-reasoned enough

Ok now, how to build a team. This is not a post about recruitment or how to interview or any of those HR related topics. This is a bit more strategic article focusing on knowledge of know-what, know-why and know-how.

The majority of managers simply do not understand the variables that influence organization and individual performance. They are not aware of the 'performance levers' that they should be pulling and encouraging others to pull. — Geary Rummler and Alan Brache

In order to improve a performance (in here it can be about engineering an experience), what is observed, three layers of work needs to be done which are: organizational level, process level and performer level (employees, managers, c-levels). Each of these layers must be met at each of these dimensions: goals, designs, and management.

  • Goals are specific standards or expectations that customers have for products or services

  • Design is configurations that enables goals to be met efficiently

  • Management is practices that ensure goals are up-to-date and are achieved or achievable

Combining the three levels with the three performance needs results in nine performance variables. Failure to manage these nine performance variables will lead to a failure to manage the business holistically. Thus, every performance improvement effort must be viewed through matrix. There are many other dimensions that impacts performance and it has a complex typology as you can see in following figure:

Rummler, G. & Brache, A., (1990). Improving Performance: How to Manage the White Space on the Organization Chart. San Francisco: Jossey-Bass.

In this article, I'm fully focused on "knowledge" in terms of know-what, know-why and know-how. We gain knowledge through context (experiences) and understanding. Whenever we've a context, we can weave the various relationships of the experiences. The greater the context, the greater the variety of experiences that one is able to pull from (and this is why mental models are very crucial for success. The more models you have—the bigger your toolbox—the more likely you are to have the right models to see reality). The greater we understand the subject matter, the more we are able to weave past experiences (context) into new knowledge by absorbing, doing, interacting, and reflecting. Thus, understanding is a continuum (Cleveland, 1982). Often, the distinctions between data, information, knowledge, and wisdom continuum are not very discrete, thus the distinctions between each term often seem more like shades of gray, rather than black and white (Shedroff, 2001) which if you are interested in how to use this concept and build your Business Intelligence department read my other article called: Business Intelligence Maturity Model.

  • Data comes about through research, building, gathering, experimenting, and discovery. This is where agile/lean methods help to capture more data faster.

  • Information has context. Data is turned into information by organizing it so that we can easily draw conclusions. Data is also turned into information by "presenting" it, such as making it visual or auditory. This is "intuition and insight levels" in Business Intelligence Maturity Model.

  • Knowledge has the complexity of experience, which come about by seeing it from different perspectives. This is why training and education is difficult - one cannot count on one person's knowledge transferring to another. This is why I strongly disagree with the term called "Knowledge Transfer" when new employee is replacing an old ones and this is why I believe it is better to pay more to keep turnover low because knowledge transfer is impossible. Knowledge is built from scratch by the learner through experience. Information is static, but knowledge is dynamic as it lives within us. This is "insight and prediction levels" in Business Intelligence Maturity Model and heavily relies on your management and key employees. This section is the focus of this article as well.

  • Wisdom is the ultimate level of understanding. As with knowledge, wisdom operates within us. We can share our experiences that create the building blocks for wisdom, however, it need to be communicated with even more understanding of the personal contexts of our audience than with knowledge sharing. This is why I love quotes like: Simplicity has been difficult to implement in modern life because it is against the spirit of a certain brand of people who seek sophistication so they can justify their profession.

Knowledge is information that changes something or somebody—either by becoming grounds for actions, or by making an individual (or an institution) capable of different or more effective action." - Peter F. Drucker in The New Realities

Data and information deal with the past. They are based on the gathering of facts and adding context. Knowledge deals with the present. It becomes a part of us and enables to perform and deliver performance (in here it can be about engineering an experience). However, when we gain wisdom, we start dealing with the future as we are now able to vision and design for what will be, rather than for what is or was (This is "insight and prediction levels" in Business Intelligence Maturity Model).

Level 1. Know-What. Concepts.

We deal with one concept, are written in a known context and require one known strategy for solving them (closed solution, convergent thinking). Examples for interview questions: true-false questions, multiple choice questions, and short-answer questions. This is the gathering of parts in above picture, to form a structure or meaning, there must be parts. These parts are composed of bits of data. The only context in data, are other relationships with other bits of data.

Level 2. Know-Why. Competencies.

We deal with one concept and method, are written in an unknown context and require many known strategies (multiple solutions, divergent thinking). Examples for interview questions: exercises and conceptual derivations. This is Connection of parts, to start giving meaning to the parts (data), we arrange them into a presentation, such as text, speech, visualization or story. Generally, the only context of information is its presentation.

Level 3. Know-How. Skills.

We deal with many concepts and methods, are written in an unknown context and require many unknown strategies (open solution, creative thinking). Examples for interview questions: open-ended problems and projects. This is:

  • Formation of a whole, to become whole, deeper contexts or complexity are added to it. This addition provides the person with experience. Thus, knowledge is gained through experience.

  • Joining of wholes: Wisdom has a number or wholes or patterns. These patterns allow the person to join the various wholes that can be used in novel ways.



Velocity — the speed with which knowledge moves through an organization.

Viscosity — the richness or thickness of the knowledge transferred.

Explicit knowledge can be articulated into formal language, including grammatical statements, mathematical expressions, specifications, manuals, etc. Explicit knowledge can be readily transmitted others. Also, it can easily be processed by a computer, transmitted electronically, or stored in databases. This is "intuition, insight and prediction levels" in Business Intelligence Maturity Model.

Tacit knowledge is personal knowledge embedded in individual experience and involves intangible factors, such as personal beliefs, perspective, and the value system. Tacit knowledge is hard to articulate with formal language (hard, but not impossible). It contains subjective insights, intuitions, and hunches. Before tacit knowledge can be communicated, it must be converted into words, models, or numbers that can be understand. In addition, there are two dimensions to tacit knowledge:

  • Technical Dimension: This encompasses the kind of informal and skills often captured in the term know-how. For example, a craftsperson develops a wealth of expertise after years of experience. But a craftsperson often has difficulty articulating the technical or scientific principles of his or her craft. Highly subjective and personal insights, intuitions, hunches and inspirations derived from bodily experience fall into this dimension.

  • Cognitive Dimension: This consists of beliefs, perceptions, ideals, values, emotions and mental models so ingrained in us that we take them for granted. Though they cannot be articulated very easily, this dimension of tacit knowledge shapes the way we perceive the world around us

In order to engineer and architect an experience, you must have a management team that can articulate well the what, how and why. A management team who has capability on understanding of Know-What (has a big tool-box of Concepts), Know-Why ( has Competencies to perform), and Know-How (has skills).