Performance, Enjoyment, Care, and Learning

Those who perform at a high-level and consistently seems to enjoy what they do, when they were asked.

No, they do not necessarily see what they do as a passion. Rather, their performance seems to be driven by the will of wanting to be good at a something.

Also, they do not necessarily enjoy every single aspect of what they do.

Professionals practice their craft daily, and every craft has some element of drudgery involved that the professional must deal with daily.

It is not always fun and game.

But those professionals see past the drudgery and strive to be immersed and at their best every single moment.

While they strive to be their best, they express the care by paying attention to details and learning from the performance.

If it must be done, I see to it because I care about how it gets done.

For those who excel, performance, enjoyment, and even more so, the sense of care and learning all seem to feed off one another.

聆聽與溝通

(從我的一個喜歡與尊敬的作家,賽斯 高汀)

很多人會說,要溝通好,基本的要在聆聽上做好工作。

當與人溝通,我大部份花的時間是在聽多於說話。僅管如此,我還是在想可能我溝通失誤的次數比我能感覺到的要多。

然後,我突然意識到,如果我擔心沒溝通好,我應該專注於一件事。

我們大多數在聽的時間,同時我們腦子裡也在想如何去應付所討論的話題。

然而,這時候我們就喪失去一個真正聆聽的機會,那就是排除應付的念頭,而是專心的去了解對方。

有了解就有希望能夠溝通,那就在聆聽上做得更好。

What rope is pulling on you?

The most popular stars in the traveling circus are their elephants, and the tour is always attracting countless children’s attention. One day a teenager, who wanted to take a closer look of the elephant, went to the circus backstage. He was surprised to find that the elephant was tied to a piece of wood by an ordinary rope.

The young man curiously asked the trainer: “Sir, why do you only need a rope to be able to subdue such a huge elephant? Won’t they just pull hard on the rope and escape?”

The trainer smiled and replied. “When these animals were still young and small, we lock them up with a large metal chain. Every time the animal tried to escape, they would pull the chain very hard and that caused a lot of pain. After a long time and many tries later, the animal learned it is useless to pull hard and try to escape. Now we only have to use a simple rope because they no longer believe they can escape.”

In our life, we are often our own worst enemy. We were taught to be compliant and to rely heavily on past ideas and experience.

When the world changes, we were still bonded by following the system that no longer works and trying to hang on to the status quo.

Breaking free from the old system is never easy but necessary. What rope is tying you up and keeping you from exploring the new frontier?

Analytics Alone is not Enough

We talked about how Analytics can be the next logical step beyond just simple measurements and metrics.

Analytics can help by highlighting potential correlations between data and giving us more opportunities in connecting the dots and reaching insights.

While analytics can move things forward in the positive direction, reaching an insight is nowhere guaranteed or assured.

Often, human decisions can be complex. Analytics is not the be-all and end-all mechanism for decision-making.

Machine learning tools can do many data wrangling, cleaning, transformation, and hyper parameter tuning tasks that are complex but not particularly creative.

It would be foolish to simply throw tons of data at the algorithms and just do what the machine learning application tells you to do.

This means leaders and managers need to understand how their organizations really work, from both quantitative and qualitative perspectives.

The qualitative perspective often provides additional context for the quantitative perspective.

Insights with the balanced quantitative and qualitative perspectives will likely be the most actionable.

Analytics as the New Metrics

For many organizations, measurements are just data. Metrics are mostly ratios or simple manipulation of the measurements.

Measurements and metric may say something about what had happened, but they do not explain why.

For example, a popular service desk (SD) metric “First Call Resolution” was down 5 percentage points this month versus last. Was it because…

Did we have a major outage so the call volume went way up?

Did the end-users suddenly got to be more sophisticated and asked harder questions?

Did the SD analysts grow more lazy or dumber?

IT is a complex business and often there could be multiple factors in play when metric moves in the certain direction.

This means we need a more sophisticated mechanism than just simple metrics to help analyze and evaluate root causes.

Analytics can help.

Descriptive analytics, even with the basic statistics-based techniques, can help point out correlations that might exist within the data. Correlations, as we all know, do not prove causation but it can still be helpful.

Predictive Analytics, along with machine learning techniques, can help create models that might point out future behaviors. The predictive models are only as good as the quality and quantity of the data you use to train the models. Still, the models are a lot more actionable than simply relying on gut-feel alone.

Moving forward, finding the necessary data and applying the analytics will be essential for managing IT.

Human Dignity and Social Status

Peter Drucker talked about this in “Concept of the Corporation.”

“It is perhaps the biggest job of the modern corporation — to find a synthesis between justice and dignity, between equality of opportunities and social status and function.”

One of the thesis discussed by Andrew McAfee and Erik Brynjolfsson in their books was the hollowing out of the middle class primarily because the jobs and careers have been immensely transformed by technology.

What is technology doing to us? Perhaps that is the wrong question to ask. Technology is just a tool. People can use tools for both constructive purposes or un-constructive outcomes.

Is it possible to improve the situation? Leaving machine and AI progress unchecked, we might approach a situation where prosperity (wealth and power) will be reaped by just the precious few, while everyone else endures the hardship.

Some might say this is just natural selection at work. Survival of the fittest.

Many of us in my age group was brought up to be good corporate citizens, to contribute, and to grow with the organizations. In turn, the organization will share the success and prosperity with its employees.

I am not sure that is how the system works anymore. There are still some companies operating with that philosophy, but most organizations treat their people just as a line item in the budget spreadsheet.

I am in the camp of McAfee and Brynjolfsson where we, as a society, need to make some hard choices so the prosperity can be shared. With the participation of its citizens, the policy makers can do more in the areas of education reform, infrastructure investment, flexible immigration, and basic research.

Furthermore, I agree with Drucker… Provide dignity to everyone you work with simply because they are human beings.

Creating Our Digital World

Watched this informative video “Creating Our Digital World with Erik Brynjolfsson and Andrew McAfee” on YouTube and produced by The Commonwealth Club of California.

The discussion over a bit over an hour long, but there were a few key points that I took away from the initial viewing.

  1. The world is undergoing three major digital trends: from “Mind” to “Machine,” from “Product” to “Platform,” and from “Core” to “Crowd.”
  2. What will technology do to us? It is important not lose sight of the fact that technologies have made us a more prosperous world overall. However, a challenge we should be cognizant of is that the wealth generated by technologies might not be fairly or equitably distributed.
  3. Human minds are biased and glitchy. Instead of worrying about the machines taking over the minds, leverage machines to support the human to make better decisions.
  4. Companies with large market share are not necessarily wrong or evil. Concentrated power deserves vigilance. We should act if the concentration of the power leads to consumer harm and stifling of innovation.
  5. The American middle-class has been left to its own device. Shared prosperity can still come from major policy choices we will be making on education reform, infrastructure investment, flexible immigration, and basic research.
  6. Work is meaning for many people. We should do everything we can to identify the new kind of work and retrain people to get into those work. The society should provide avenues that encourage people to change and to thrive in the new environment, rather than just living in the past.

News media and pundits love to discuss the pending doom that technologies and AI are about to bring onto the society. Instead of worrying about or resisting the coming changes that will happen regardless, how about we channel the AI energy to create positive societal changes for everyone?

測量和管理

(從我的一個喜歡與尊敬的作家,賽斯 高汀)

在強調使用數據在管理方面的重要性時後,有一句話經常會被引用,如果你無法測量,你將無法有效的管理。

有些人拿著這個念頭就聯想,只要有足夠的數據就可以解決問題。當收集與積累大量的數據以後,希望就可以找到關鍵的洞察力,而我們也能明確的知道在下一步該做什麼。

不過也許我們首先該作的是問一個這個問題,我們最終最希望看到什麼結果?以及我們需要在什麼樣的環境/現實中使用?

在確定所要的管理結果之後,我們再問需要的是什麼數據,以及收集數據的投資是否會超過了收益。

在測量之前,先問問適合的問題。所收集的數據將會更有意義。