Simplicity Combats Complexity

James Murphy, a former F-15 fighter jet pilot and now CEO of a team building company, notes in a recent article that “complexity is the mortal enemy of good execution, and our world is nothing if not increasingly complex.” Thus, in order to execute in an ever increasing complex word, we need to break it down in simple steps:

  • Planning: If your planning process tries to run the whole gauntlet of complexity then you will simply get beat up by it, so use short-tem timelines.
  • Briefing; Get everyone on the same page.
  • Executing: Just do it.
  • Debriefing. The purpose of the debrief is to make adjustments ... to discover lessons learned. This can best be accomplished by performing an After Action Review:
    • What were our intended results?
    • What were our actual results?
    • What caused our results?
    • What will we sustain or improve?
  • Repeat process so that you are refining and continually improving.


Col. John Boyd, USAF (Ret) has a similar process called the OODA Loop:

  • Observe: Scan the environment and gather information from it.
  • Orient: Use the information to form a mental image of the circumstances and place it into context.
  • Decide: Consider options and select a subsequent course of action.
  • Act: Just do it.
  • Repeat process so that you are refining and continually improving.

Both Murphy and Boyd say that no matter how complex the environment is, when you do this, you stay at the same rate of competitive change in the complex environment or slightly ahead of it ... thus you win. Murphy also notes that confidence leads to courage, and courage leads to a bias towards action. This planning process gives people that courage regardless of the situation.

Probe, Sense, Respond

David Snowden of Cognitive Edge also has a similar tool for dealing with complexity in his Cynefin model:

  • Probe: Make a change (prototype) in the environment in order to test it.
  • Sense: Review it by determining the impact of the probe.
  • Respond: Depending upon the result you achieve you either amplify the probe or suppress it, and then repeat.

Agile Design

And the last one for dealing with complex environments — Agile Design:

  • Select the project and develop the vision.
  • Initiate the project by obtaining stakeholder participation, funding, and build team.
  • Deliver small working iterations that meet the changing needs of the stakeholders. Continue this step until:
    • Release (End Game) by deliver the final package.
    • Production: operate, maintain and support the system.

There are four other design models beside Agile that you can use depending on the complexity of the environment.

These tools, Murphy's Process, AAR, OODA, Cynefin, and Agile Design are designed for working in complex environments. What other processes or models do you use for dealing with complexity?


Full Spectrum Learning

The U.S. Army has developed its answer to the 70-20-10 Learning model and Dan Pontefract's 3-33 Pervasive Learning model. However, they did a couple of twists by:
  • dumping the percentages
  • combining Experience with Social Learning
  • adding Education
  • adding two continuums - Responsibility and Ambiguity
Full Spectum Learning


70-20-10 has been problematic in at least two ways. As Dan Pontefract notes in his book, Flat Army, it is based on leaders who were in charge of hierarchical, command and control cultures that were prevalent in the 1980s. While the U.S. Army does have a hierarchical command and control culture due to its nature, it is also composed of flat or horizontal teams (large and small) that operate alone and with each other in complicated environments that often border on the edge of chaos. Thus, it is both a hierarchical and flat organization that not only approximates how most successful organizations operate today, but is also based on all people, rather than just senior leaders.

Secondly, the use of percentages or ratios, such as 70-20-10 and 3-33, imply that they are predictive models, rather than reference models. In fact, the creators of 70-20-10 wrote that it is a predictive model. This can be noted in dozens of blog posts in which some very smart authors note 70-20-10 is a predictive model model and then are told in the comment sections that it is a reference model. If you do a image search on Google for the term "reference model" (may NSFW as it shows a couple of nude models) you will notice that none of the images are based on percentages or ratios.

Experience has Social Learning in a Learning Environment

The Full Spectrum Learning model realizes that if you are gaining experience to learn, then it is implied that you will be using plenty of informal and social learning, along with smaller amounts of training and education. In order to build skills and knowledge via experiences, the environment must contribute to peer-based learning through blogs, wikis, micro-blogs, and other social based media. It leverage these social tools to build dynamic vertical and horizontal social networks for formal and informal information sharing in order to foster critical thinking and problem solving skills needed for operational adaptability.

The Addition of Education

In Human Resource Development, training is normally associated with learning to perform a present job or task, while education is normally associated with learning to perform a future job or task. Thus, in a rapidly changing world, education through formal and/or nonformal environments is a required component if an organization wants to remain competitive. For example, during our last recession, companies dumped thousands of people in mass layoffs. Now they are whining that they cannot find people who have the education and training that they require. Good organizations should always be building a path towards the future by educating people to walk that path.

The Responsibility and Ambiguity Continuums

Rather than build a learning model that focuses on one fixed point, the U.S. Army created the Full Spectrum Learning model on two continuums based on the degree of responsibility of the learner and the degree of ambiguity of the learning environment to give it depth.
What are your thoughts on the three models?