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Michael Arena of Amazon Web Services Joins ATD’s 2021 Board of Directors

Michael Arena of Amazon Web Services Joins ATD’s Board of Directors

Michael Arena is vice president of Talent Development at Amazon Web Services. Contact him at arenamic@amazon.com.

Michael Arena

我们生活在一个万物互联的时代。任何产业的发展都离不开技术的支持，人才发展也绝对不会例外。2020年疫情的爆发对于技术的发展更是起到了一次推进。如今的后疫情时代注定是数字化转型加速的时代。埃森哲在其《2020中国企业数字转型指数研究报告》中指出，去年仅有11%的受访企业凭借完备的数字能力，在疫情中应对有方，甚至转危为机，成为了数字化转型领军者。都说数字化转型始于人，但想要最终取得成功，“技术”是不可避免的话题。在当今社会，了解并能够选择适合的技术，有针对性的应用到人才发展项目中，是对于所有人才发展从业者的考验。基于此，ATD中国将本年度峰会主题与技术相关联：技术助力腾飞。我们深知，对于人才的发展、技术的应用等都是全球的普遍性问题，且各国各地都存在着优秀的实践。ATD此次特别邀请到六位国际嘉宾，为本届中国峰会带来主题演讲。这六位嘉宾的演讲角度各不相同，且互为补充。对于全球数字化整体发展的认识作为未来学家，战略数字顾问的David Shing将跨界前来，为参会者揭示数字化发展的大趋势。作为人才发展从业者，我们清楚地认识到很少有技术是专程为人才发展而诞生。因此，我们需要了解数字化发展的大趋势，从中抓取到适合我们自身行业的发展方向。对于人才发展行业的认识了解过全球性的数字化趋势，接下来一起聚焦到我们的人才发展行业。本次，ATD总裁兼首席执行官将结合目前动荡发展的社会与人才发展领域的快速变化，与从业者们探讨全球人才发展行业的未来。将理论认知与实际相结合经历行业性趋势的分析，参会者们一定更想要将理论与实际相结合。具体怎样才能良好的运用技术，实现自己公司内部的人才发展？亚马逊云科技（AWS），人才与发展副总裁Michael Arena将为大家总结他的工作策略。人才发展是一条双行道在作为人才发展人士的我们不断探求更新的技术与学习方式时，不要忘记被培养的群体特征与诉求。全球知名学者，ATD新版能力模型一书的作者之一Patricia McLagan将与我们探讨“智慧学习者”这一话题。具体学习技术的介绍除以上主题演讲内容外，ATD特别邀请到国际知名的两位主题内容专家由浅入深的为大家介绍具体的学习技术的应用。除以上六位主题演讲嘉宾的内容外，更多演讲信息已陆续在官网上公布，欢迎大家点击此处进行查看。或许“技术”一词早已出现早许多活动、课程当中，如何在多样信息中提取精华，直接找到关键？本年度的中国峰会将带领各位知其然，更知其所以然。本年度ATD中国峰会将以混合式学习形式展开，在特别打造的虚拟学习平台与北上深三地的线下活动形结合的学习中，为大家营造“**用技术谈技术，用技术学技术”**的体验。

ATD2021中国峰会“六大”主题演讲内容正式公布

Winter 2018 - CTDO Magazine

Chief Talent Officer Michael Arena is helping build adaptability into General Motors’ workforce.

GM’s Internal Disruption Engine

Winter 2022 - CTDO Magazine

Social connections and productivity in remote work are waning—that's where an adaptive hybrid model can help.

Don't Leave Connections to Chance

September 2021 - TD Magazine

Tap into the science of executive function to get to the root of an employee’s underperformance.

Problem Behaviors Aren’t Always Surface-Level Issues

An author, entrepreneur, and award-winning educator, Michael Delman is a pioneer and leader in the area of executive function coaching. He has served as CEO and founder of Beyond BookSmart, an executive function coaching company, since 2006. In 2020, the company expanded with a second division, WorkSmart Coaching, that solely focuses on executive function coaching for adults.Delman has been featured in The Times of London, CBS Boston affiliate WBZ TV, and dozens of media outlets across the US. In 2018, he published his first book, Your Kid’s Gonna Be Okay: Building the Executive Function Skills Your Child Needs in the Age of Attention, which earned critical acclaim.Delman also has released his second book, Your Trail Map for Success: Mastering Executive Function Skills in Challenging Times, which is catered to adults seeking to become more effective and successful in their personal and professional lives. He brings his unique combination of business acumen and an educator’s perspective to his visionary work. His passion is helping people discover their strengths, develop their confidence, and become more effective at whatever challenges they face.

Michael Delman

December 2025 - TD Magazine

The best learning experiences aren't about content alone; they're about people. 

5 Methods to Bring Human Connection to Online Learning

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.

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