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Motivational speaker Michael Clark delivers power tools and real-world strategies in high-energy keynotes and trainings. Michael teaches business and education professionals the most essential 21st century skill: How to transform productivity and performance in the midst of intense situations, persistent challenges and difficult people. Michael’s entertaining and engaging delivery brings the direct experience of performance transformation to your audience and event. He teaches people how to think and communicate better, manage emotions more effectively, and make creative choices within the context of daily professional and personal challenges and opportunities.

Michael Clark

Transforming employee engagement and performance are some of the most essential skills for managers and executives. Creating continuous performance improvement is the solution to seizing opportunities, overcoming challenges, boosting productivity and realizing goals. This real-business world presentation centers on transforming the capacity to engage-perform-produce better and faster in the midst of intense situations, persistent challenges and difficult people.

You will learn how to:

Leverage two types of engagement and performance happening every moment.
Communicate more clearly and effectively.
Think better, transform negative reactions faster and make creative decisions.
Strengthen your capacity to focus, listen, comprehend and connect.
Seize opportunities, overcome challenges and realize goals.
Overcome distraction, procrastination and wasted time.
Connect and collaborate better, faster, now.


ReCentering Engagement & Performance

Connection Culture: Restoring Navy Pride

New Era of E-Learning Begins March 13

Fall 2012 - The Public Manager

Great Leaders Connect With the People They Lead

At the beginning of the past two years, I’ve written a post on important points I think you should know. In 2021 I mentioned the importance of context, emotion, and learning to learn. In 2022 I discussed some of the newer cognitive science models of cognition—including distributed, social, and embodied cognition—as well as the role of mental models. This year, I’d like to focus on a trend that we should extinguish: the belief that we are formal, logical, reasoning beings.The cognitive revolution transcended the view of behavioral psychology; we couldn’t talk about what went on in the brain. While many valuable insights were generated by that scientific paradigm, including the role of performance objectives, the move to thinking we could isolate necessary components provided further advances. Results that have stood the test of time—the recognition of sensory, working, and long-term memory as well as core cognitive processes like attention, elaboration, and retrieval—were identified.We tend to adopt existing models as frameworks for thinking about the brain, and the cognitive revolution was no exception. For example, consider the computer as a general-purpose information processing system. It made sense to adopt that model to reflect our abilities to process information and complete a variety of tasks. Thus, the dominant framework for thinking about thinking was to view our brains as formal, logical, reasoning machines.Such models, with some assumptions like mapping the world into formal representations, accomplished impressive tasks. Systems built upon that model could break down problems into components and solve them. They could even learn. Artificial intelligence (AI) advanced as a result. So-called “expert systems” were built upon interviews with the best practitioners. Sadly, these models failed in practical situations, leading to an AI winter. This was a disconcerting time, when behavior naturally observed in humans did not reflect these symbolic systems.The Postcognitive RevolutionOne of the most impressive capabilities of our thinking is the ability to organize the world into flexible frameworks. What David Rumelhart called schemas, Marvin Minsky called frames, and Roger Schank called scripts all reflect our ability to infer knowledge about the world. Thus, we had representations such as wheels that scaled up to vehicles but differently for automobiles versus bicycles. Symbolic logic struggles with this, however. Attempts were made to adapt, such as Lofti Zadeh’s Fuzzy Logic and Douglas Hofstedter’s Slipnets, but suffered in practice.An alternative framework emerged that could be characterized as “subsymbolic,” operating below the symbolic level. John Holland, Keith Holyoak, Richard Nisbett, and Paul Thagard created a genetic algorithm approach in Induction, which borrowed mutation from biology, but wasn’t aligned with neuroscience. Rumelhart, along with Jay McClelland, proposed connectionist models instead in their two-volume set Parallel Distributed Processing with a neuroscientific inspiration. These models were found to exhibit rational behavior similar to humans. They represented the same types of behaviors, including errors, that were empirically obtained from psychology research.These neural net models created not only a psychological revolution, capturing elements of cognition, but also a renewed basis for artificial intelligence, underpinning much of today’s work in machine learning.A Cognitive LegacyOne small legacy of the formal, logical, reasoning model of cognition, however, seems to linger. It appears that many of our practices in learning and development (and business in general), still seem to be based on this idea. This is a potential problem.If we’re formal logical beings, there are several things we should be able to assume. For one, if we give people new information, they’ll appropriately adjust their behavior. Moreover, the person with the greatest access to information should be the one to make a decision, and that decision will be the best one possible. We see this manifest in several ways.For one, our training frequently resembles the presentation of new information with an expectation of behavior change. Too often, we see bullet points of information extracted from (and even presented by) experts. After this, there’s an expectation that we’ll do something differently. Similarly with annual or quarterly reviews. People need feedback at the appropriate time and support for change. We don’t just change when we wish to; it takes time and practice.We also see decisions made by individuals without consultation. Folks will decree a new approach because it’s been determined by the person at the appropriate decision point. Yet the evidence suggests that we get better outcomes when we bring more people into the decision-making process, such as in Keith Sawyer’s Group Genius. When we follow practices that help us suitably explore a problem individually, and then collectively brainstorm solutions, test, and adapt, the outcomes are better.A Problematic LegacySadly, there is also evidence that this approach to work isn’t working. We see it in the outcomes of learning investments, and when we evaluate organizational success as an outcome of our approaches, we see that more informed ones work better.In the 2012 Harvard Business School working paper The Great Training Robbery, Michael Beer, Magnus Finnstrom, and Derek Schrader cite metanalyses that suggest only 10 percent of training investment has an impact. There may be multiple causes for this, but it does suggest that we’re wasting money with our approaches. The Serious eLearning Manifesto suggests that much of traditional learning is based on information presentation, so it’s safe to say that we’re not doing as well as we could.Similarly, efforts like Laura Overton’s Toward Maturity and Lauri Bassi’s Human Capital Capability Scorecard suggest that organizations do better when they’re better aligned with how people think, work, and learn. Organizational performance reliably improves with better employee approaches.Overall, the continued use of ineffective practices undermines our organizational success. We need to effectively achieve our organizational goals, which includes ensuring we can optimally execute what we know we need to do and continually innovate when we have to invent or adapt.Moving ForwardWhat should you do differently?Truly understand how your brain actually operates. Know the basics of the human information processing loop and extensions for learning and performance.Avoid the myths that continue to hinder our industry.Conduct deep needs analyses to find important performance gaps and their root causes. There are many causes of problems besides a lack of knowledge or skills. Stop thinking that if you give people knowledge, behavior will change.Leverage external resources. Decision making is best done collectively and iteratively. To do otherwise is to minimize your potential.Move from legacy practices to evidence-based practices. There are vested interests that continue to exist based on perpetuating approaches that aren’t effective. Many products that are quite lucrative—profiling instruments and development programs —aren’t effective.Start measuring impact. This doesn’t mean what people prefer (there’s no correlation with what people think of a program and its impact). Instead, assess the actual change in the organization. You can’t collect this yourself; you must partner with the business units that require change.Align programs to demonstrable gaps, and then measure until they’ve improved.Ultimately, L&D should be the folks that are responsible for not only optimal execution but also continual innovation. When you’re innovating (problem solving, designing, or researching), you don’t know the answer when you start, so inherently it is learning. It’s informal learning, and no one knows the answer (yet)! Still, it’s an opportunity for L&D to attain a more valuable role in the organization.To make this strategic move and start bringing evidence-based practices from formal to informal learning, take ownership of these practices within your teams. Make it safe to fail; share stories of what you tried; and learn together. Create and understand a learning microculture before taking it to the rest of the organization.Last, identify the organizational legacies that are holding you, and your organizations, back. Then, find alternatives, and implement them. When you’re free of your unexamined past, you can move forward to an evidence-based future that means better outcomes. That’s a trend I’d like to see and encourage you to undertake.

A Trend to Supersede

ATD Blog

While facilitating leadership development workshops at Emerson (a Fortune 125 company with 90,000 employees in 140 countries), there is an interesting comment I frequently hear: “I did not realize how much time you would give me in this workshop to think!”Is that a compliment or a complaint? I believe most people mean it as a compliment because they are surprised. Most of them haven’t had enough time to think in prior trainings.I’ve heard this comment many times, and it never takes me by surprise. In fact, I would be disappointed if I did not hear it. Most learners aren’t given adequate time to think and reflect when they attend training sessions.Far too many training programs rely on content rather than application and do not offer learners time for intentional reflection. In my 28-year learning and development career, I’ve seen too many programs approach learning by telling learners as much as possible in the time provided. Many of us in L&D call that strategy “ten pounds of training in a five-pound sack.”Fred Harburg, former chief learning officer at Fidelity Investments, sums it up well: “If there is no time for reflection, there is almost no chance for improvement.”L&D professionals want to create value for learners. One of the most valuable activities we can build into the design and delivery of our courses is intentional reflection and implementation planning. To improve our training programs, we must stop talking and pushing content, and let learners think.This represents a paradigm shift for many L&D practitioners. Spend less time on content and more time on intentional thinking and reflection.L&D thought leaders Roy Pollock, Cal Wick, and Andy Jefferson (authors of The Six Disciplines of Breakthrough Learning) popularized the term “learning scrap.” Learning scrap refers to content covered in a workshop that is never applied. Most L&D programs have a typical learning scrap rate of 85 percent. At best, most learners apply 15 percent of what’s taught in a workshop on the job. If you want to decrease learning scrap and increase learning transfer, build more deliberate thinking and reflection activities into your courses.In his classic book, Learning and Memory, Donald A. Norman writes, “To remember is to have managed three things successfully: the acquisition, the retention, and the retrieval of information. Failure to remember means failure at managing one of these three things.” I argue failure usually occurs at the retention level. If there is no reflection, there is no retrieval. If there is no reflection and retention, do not expect retrieval to follow.This issue is well-documented by Ruth C. Clark, Frank Nguyen, and John Sweller in another classic book, Efficiency in Learning. They refer to this concept as “information fatigue.” We need to give learners more time to process during a training program. The authors’ research shows a lack of time for reflection leads to cognitive overload. Overload implies a malfunction; learning is short-circuited. If a person attends a program to learn, and we cram it full of content without giving them time to think, it’s no wonder learning scrap occurs.Several years ago, I codeveloped a workshop with Michael Watkins (a former faculty member at Harvard Business School and founder of Genesis Advisers) to create a workshop based on his bestselling book, The First 90 Days. Our workshop designed intentional thinking activities that asked participants a series of questions at the end of each module. The reflection activities took between 20 and 30 minutes to complete and consisted of five or six questions. These were not simply recall or comprehension questions, but rather synthesis and evaluation questions (the higher levels of cognitive thinking).Some of the top executives who attended this workshop told me that if I had not built in deliberate time to think, their goal would have been to rush through the course so they could move on to the next thing on their list.Here are some ways to build time for reflection into your programs:
Build thinking time into the design and delivery of every learning program you create, no matter the delivery method (in person or virtual).Resist the temptation to add more content to your courses. Do not fall prey to the “myth of more.” More content at the expense of intentional time for reflection will not improve learner performance. It will diminish it.Remember, the goal is not to give the content. The goal is for learners to get it, which will only happen through the discipline of quiet reflection.If trainers are given the option to talk or let their learners think, many would choose to fill the silence with their own voices, but the greatest value trainers bring to a workshop is knowing when to stop speaking and give learners time to reflect.

Want Them to Learn? Give Them Time to Think

Jody Michael, MCC, BCC, LCSW, is CEO of Jody Michael Associates, a coaching company specializing in executive coaching, career coaching, and leadership development. She is an internationally credentialed Master Certified Coach, Board Certified Coach, trained psychotherapist, and licensed clinical social worker. She is author of the Wall Street Journal bestselling book Leading Lightly: Lower Your Stress, Think with Clarity, and Lead with Ease.Michael brings to her work a rare combination of global SVP leadership and theoretical knowledge, plus extensive field experience. She has built her expertise through 40,000+ hours of individual sessions across more than 25 years of coaching; adjunct education in human behavior, neuroscience, and psychology; and 15 years of experience in corporate leadership with Goldman Sachs, Chicago Research and Trading (CRT)/Nations Bank, and Kidder-Peabody. Based on her applied research, Michael pioneered the use of technology in coaching by creating one of the first mobile apps to accelerate the building of self-awareness, mindfulness, resilience, and emotional intelligence.Michael has coached some of the top-performing leaders and teams In the US across diverse industries and organizations from hypergrowth tech companies to global Fortune 100 organizations. She has a special affinity for partnering with tech, finance, and healthcare.She’s a renowned keynote speaker, author, and thought leader in her field who has been featured in the Wall Street Journal, New York Times, Forbes, Oprah Magazine, Huffington Post, Crain’s Chicago, and more. She also has appeared as an expert on MSNBC, CNN, the Today Show, and NPR.

Jody Michael

Simulation learning is a growing player in the healthcare talent development industry. Clara Von Ins reviews advantages, challenges, and factors for success.

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