Out of the second book I read on Talent and High-Level Performance, I rescue a very significant corner stone which is better positioned with respect to what I seek; this corner stone is the concept around the ability to engage in cognitively complex forms of multi-variate reasoning.
Under this definition, do we need to be very talented to achieve high-level (great) performance? Let us see.
a. Reasoning is something that you do every day. The key is how you do it.
b. Good performers do their reasoning beyond and above the norm.
c. You do not have to be precisely smart to practice good reasoning.
If we want to build expertise as the vehicle to make good decisions and to expand knowledge, we need to get good at reasoning. From my formation as an engineer, I see that math training (say) is an exercise that contributes to this goal; it is practice to promote good reasoning. BUT math training is not going to create experience in itself. You are not going to become talented by being good at math; although someone may tag you as a “talented mathematician”. Here you have to check your “ego budget” and verify that such a tag serves any purpose.
So here you may get a few ideas as to what to do with the famous IQ as a talent-metric. How solid can it be when it cannot account for other skills such as social interaction, thinking abilities, honesty, tolerance, wisdom, inclusiveness, etc.? As the author suggests, a high IQ is a good performance-predictor for an unfamiliar task; but after a few years, its validity washes out and can no longer be considered as a trait for high performance.
So in the search for Talent and High-Performance, it seems desirable to reach out for cognitive abilities rather than “brainiacs”. The quest is now for cognitive abilities relevant to our specific environment and ways to promote them effectively.
Confession: Being an engineer, I was uncertain as to the formal meaning of the expression “cognitive abilities”. I sought help in Wikipedia and now I feel better informed; simply typing the expression in Google will produce several references. Also, our friends at SharpBrains have a relevant entry in their blog: what are cognitive abilities.
Talking about promoting cognitive abilities as the means to enhance multi-variable reasoning, it becomes important to identify what is a “promoter” and what is a “detractor”. The book presents a few ideas about what could act as a constraint (personality as an indirect agent for example) and what could be implemented as an improver (memory games, knowledge enhancing, etc.). I consider these ideas as stepping stones to create your own set. We want to implement two active principles: a) eliminate constraints and b) increase promoters. We had better identify these clearly to make sure we apply the right action (eliminate/increase) to the correct stream (constraints/promoters).
The author conveniently explicitly writes down what does not drive great performance: a) it is not experience; b) it is not inborn abilities; and c) it is not general abilities such as memory and intelligence. So what does?
The author sets the stage to look for more profitable ideas identifying the fact that American football players spend a small amount of their football-related work actually playing football; instead, the majority of their time is concentrated in practices. He uses Jerry Rice (anyone in my age range will at least have heard of this fantastic character) as an extreme example; Jerry Rice designed his practice to work on HIS specific needs rather than other goals that might have seemed more generally desirable, like speed.
Here I can start to see where actors of the engineering world may encounter the first few stumbling blocks to march towards high-performance consistently. How often do we identify what WE require and practice towards those needs persistently? Is it not the case that “engineering is finding solutions to novice situations that pose specific challenges”? How often do we engage on a specific task?
We have to deal with the Hard Work Paradox (named here, but described elsewhere including this book); people that spend a long time practicing a specific activity (golf, bowling, computer games, etc.) get to a peak to then level off. However, we also see that the masters of specific disciplines (Jerry Rice among many others), did work solid hard for more than ten years to excel at the level they did. So, hard work produces high-performance or not?
The answer apparently resides in the way we do the hard work required. The author develops this concept under the term Deliberate Practice comprising 6 elements:
Those that practice any sport requiring coordination (I do bowling myself), know that practice generates muscle memory; it basically trains your muscles to act in automatic mode without having to pay attention so that your brain power can be devoted to other more subtle details. But what happens when you over-do your muscle memory? When does this automatic mode of operating transforms into a liability for the performance level you seek?
The author centers his argument about Deliberate Practice avoiding this automaticity. Great performers always keep significant parts of their actions under control and permit no level of automatic reaction.
Automatic reaction requires no effort and therefore lives in the so-called comfort zone where automaticity gets reinforced but no learning takes place. Out and adjacent to the comfort zone, you find the most-convenient learning zone where errors may happen; therefore a clear target for correction and learning appears. Further out you would find yourself in a high-risk zone where so many errors take place that feedback gets confusing as to what to correct next. You definitively want to learn in the Learning Zone.
Transporting this concept into the engineering world and even into a further extension to the business world, portraits a simple reality: we do not practice much of anything. We therefore permit way too much automaticity and as a consequence, great-performance is compromised; average automatic performance is of course there and is used as a reference metric.
Do we have any doubts of this being the case? Have you ever heard of the ANNUAL Performance Review? Even our reviews are done once a year; how do we aspire to get any better doing critically important exercise every 12 months?
Automaticity must be identified and fostered/eliminated as needed. But we need to be in control of this important maneuvering.
Deliberate Practice develops abilities that permit performers to perceive more, know more and remember more. The interaction among these three traits (perception, knowledge and memory) is clearly described as the differentiation from regular performers. Great performers excel at these three by developing a beyond-average set of senses, by integrating their knowledge to higher-level principles and by hanging huge quantities of information in the structure provided by this knowledge.
Here the author provides a rather unexpected one-page jump to describe how the brain gets modified by profound training; he lands in the concept of MYELIN as the agent that hosts the traits described. This jump can be bridged if you check the summary of the first book I read on Talent: The Talent Code (Daniel Coyle). This book provides a very good account of the neurological process around myelin build-up as a performance-enhancer.
To patch up this gap, the author here provides a great description of deliberate practice models and how we can apply them to our lives and our organizations. Recommendations are provided to practice under various schemes and models.
Before the schemes however, the author points out what I consider to be a very strong element: the direction you want to go in. People often say that it is important to know what you want to do. Under the new global and competitive landscape where social forces are developing significant components, the know becomes far more important than the what. I will write separately about this.
Now, to the practicing schemes.
A. Direct Practice. Practice a specific and well-defined skill away from the actual use of the skill. You concentrate on the use of the skill and ignore other external factors. Examples appear in the various models below.
The Music Model. A musician know what he or she is going to play; the music is written down. The musician practices to play this one piece to his/her best. Note that the objective (play the music) does not change regardless of the conditions around it. So you may identify a skill that you need to develop which is always the same; that does not change with the surrounding landscape; you develop this skill by practing it directly. Examples are presentations, writing techniques, fast reading, etc.
The Chess Model. Excellent chess players practice by studying positions from real games between top-level players. The practice consists in studying a particular position and choose the moves you would make; then compare those with the moves chosen by the masters and if different, understand why and which one is better. You may decide to develop a skill to meet the central demands of a specific field and to react accordingly. The typical examples are the so-called case-studies. Business has embarked in this practice model for a long time; a good representation of these is the famous series known as Harvard Business School Case Studies. You can get ten (or more) case-studies to practice the skill you seek to develop; and get immediate feedback and repeatability.
The Sports Model. World-class athletes practice two large categories:
a) conditioning - building the strengths and capacities that are most useful in a critical sport. For non-athletes, this means getting stronger with the underlying cognitive skills that you probably already have (math in financial jobs, basic science in engineering jobs, basic language skills in editorial jobs, etc.). These strengths like physical strengths decay if they are not maintained.
b) specific-skills development - building the capacity to deliver a skill under unpredictable conditions. Printed music is always the same; but no two passing situations are the same for a quarterback. This requires focused stimulation as typically the response is required in a short period of time; therefore it must be fluid and dynamic.
B. Practicing at Work. Deliberate Practice possess properties that are key components of self-regulation; which from my perspective constitutes a high-level trait to be searched for when hunting for Talent.
Before the Work. Set goals about the process and not the outcome alone. Planning to reach the goal with specific and technique-oriented actions. Think exactly and not vaguely. Center on attitudes and beliefs. Self-efficacy and ability to perform.
During the Work. Self-observation. Applicable to both physical and mental work. Metacognition: knowledge about your own knowledge and thinking about your own thinking. Adapt to changing conditions. Never hijacked by emotions. Use metacognition as the immediate feedback required for deliberate practice. Do what you do and practice what you are doing.
After the Work. Self-evaluation. Extend practice to the outside of your mind. Decide what caused errors. Take reponsability and do not attribute them to factors outside your control. Relate failure to specific elements of your practice and performance that may have misfired. Focus relentlessly on your performance. Upon failure, confront and adapt; do not avoid the situation. Train yourself as to how to adapt. Establish more specific goals and strategies to improve focus and efficacy. Power up a self-reinforcing cycle.
Of course, no level of practice would suffice if your domain knowledge is short of the average (self-average or market-imposed average). Many people go along their lives by picking up the knowledge they require at work. In many cases it may be enough for standard performance; but in general, others will surpass these mediocre players. Those that make domain knowledge a direct objective as opposed to a byproduct of work will take the driving seat. Possessing more knowledge than others will always be a competitive advantage.
The author introduces the concept of a Mental Model. You are not accumulating information, you are building a Mental Model which portraits how your domain functions as a system. You want to have a highly-developed (not improvised), intricate (not simplistic) Mental Model of your domain. This Mental Model:
a) is the framework on which you hang your growing knowledge of your domain; this also enhances your memory as one thing relates to others in a continuum that you understand;
b) is the tool that permits you to distinguish relevant information from trivial rubish and irrelevant information; in a world so saturated with sources of information this is a highly-welcomed tool;
c) once constructed, enables you to predict what will happen next. This very much resembles what happens in mathematical models. Once you understand the physics, you may represent those laws in a model that produces answers for specific operating conditions. Of course, the reliability of the model is as good as the representation of these laws. So your model must be continually fed back from your experiences to fine-tune your representation of your reality.
The book concludes with four spin-off topics that I will not document here; not because they are not valuable, quite the contrary. They have enough weight to be documented independently. These are:
a) Applying these principles in our Organizations. Assembling the Teams.
b) Performing great at Innovation. Innovation does not strike; it grows.
c) Performing great in youth and age. Supporting environments and brain plasticity.
d) Where does the passion come from? Drivers, Pitfalls, Effects and Beliefs.
After having documented this book, it is alarmingly obvious that Organizations do not embark often in even a small fraction of what would be required to promote great performance. The author identifies a passion requirement as a driver and I concur. However, passion may not be enough and more substantive knowledge may be required to identify tools that can be used in marching towards better performance, if not excellent.
The book concludes with an extremely elegant statement which summarizes my purpose of the book: "Evidence shows that the price of top-level achievement is extraordinarily high. Perhaps it is inevitable that not many people will choose to pay it. But the evidence shows also that by understanding how a few become great, anyone can become better".
... anyone can become better. I thoroughly enjoyed reading this book and will highly recommend that others read it too if for nothing else, to find some elements to become better; the possibility is there for all of us.
Web Page for the book: http://www.talentisoverrated.com/