Archive for category Work

2018.09.07 管理和风筝

听到一个比喻:管理和放风筝一样。回拉确实能避免风筝坠地,短时间还会升高一点,但风筝上天只能靠放线。

贴切!

Advertisements

Leave a comment

2018.06.05 ‘a’ question

部门这段时间都在忙教材的事情,20/80原则耗费了我们大量的时间和精力。今天就碰到了一个有趣的问题,为什么字母 ‘a’ 的手写体和大多数字体是不同的?

这个问题要扯的话可以扯很远,简单的答案:学校里教的手写体通俗来说是为了快速书写(一笔完成不用提笔)而演变的不正规写法,写的人多了就渐渐变成标准。下图很有意思,一来说明了大部分时间 ‘a’ 的写法是历史主流,二来 uncial 写法的 ‘a’ 也说明了大小写之间的关系。

the_history_of_a

最后放一张还未定稿的教材,字母A的自然拼读页,敬请期待。

phonics_A

Leave a comment

2018.06.01 Keep Your Clients Informed

试想以下情景:

“你看上一件衣服,询问店员是不是全棉的,她给了你一个肯定的答复。也不是因为不信任她,但你还是很自然的翻出衣服上的标签上确认了一下。”

为什么会有这个动作,事后你问自己,人与人之间的信任呢?其实你也不必太过自责,好的店员也不会把这个当回事儿。面对所见和所闻,人总是偏向于相信前者。

这当然不是我总结出来的,最近在 udemy 学习销售方面的课程,Grant Cardone 的讲解很容易产生共鸣,特别是那句 “People always believe what they see, not what they hear”,以此建议在销售的过程中尽量采用书面材料(合同)和真凭实据来赢得客户的信任。短期看来可以快速完成单笔交易提高销售效率,长期来说可以极大的降低客户的维护成本,防止后院起火的概率。

Inform_buyer.png

Credit: Learn to Sell Anything by Grant Cardone, Udemy.

肯定会有人说,客户拿着合同的话今后会让我们很被动。我说,做不到的东西当初为什么要承诺?主动权从来都在自己手中,把以后救火的精力用在先把工作做好,岂不更好?毕竟我现在聊的是销售,不是忽悠。

, ,

Leave a comment

2018.05.17 Deeply Practical Project Management

I recently took a project management course from Udemy and that was indeed a very enlightening journey.

Deeply Practical Project Management

Before taking this course, I always had this ‘mis-conception’ about Project Management to be very dry, inflexible, and unpragmatic. So I purposely picked a course that is not exam-oriented. This course delivered what it promised (to be deeply practical) and totally changed my mind towards Project Management.

I could easily relate the contents of it to what actually happened in my past project management experiences. So often I spoke to myself “Gosh! If only I knew it earlier the result of that project could be quite different!”

Leave a comment

2018.05.14 Lean Management

1 year of streamlining the operations for the company I co-founded, I can totally related to what Mike talked in this 45-mins video.

Business process improvement isn’t just about putting the “best” process in your organisation, trust me more often than not it won’t work.

It is also about understanding your staff, coaching them, designing new process so that its benefits are visible and the slope of change is not too steep, and the most importantly, leading by example.

, , ,

Leave a comment

2017.06.27 Auf Wiedersehen

拖了快五年,今天终于从博世离职了。

其实从一开始就知道那样的环境不适合我,走终究是要走的,只是时间问题。但头两年的坚持是因为一份工作至少两年的原则;第三年的延期是对德国工作环境的幻想;第四年则是为了对得起自己的时间而拼命想做出一个项目(虽然最终还是给管理层拖死了);到了今年则是对公司彻底死心,熬到年终分红后就毅然提出离职了。我在给人力资源的反馈中写道

“… no clear strategy, nor commitment to whatever shortlived ‘strategies’; making decent products is clearly not the top priority.”

回想我2012年入职的时候,还是个对未来智能方案充满幻想的青年,也做过主动跟老板要工作做的“蠢事”。五年的光阴不仅慢慢耗尽我的冲劲,也慢慢抹平我在之前的工作积累起来的大量的自信心,有时甚至开始怀疑自己的能力,再不走就真的是温水煮青蛙了。

庆幸的是,在什么都慢的博世,离职程序倒是出乎意外的顺利。

Leave a comment

2017.04.20 Data Analytics and Optimization in Virtual Power Plant

Asking 10 Smart Energy guys what Virtual Power Plant is about, you will probably end up having 10 answers – all could be different but correct at the same time, seriously, legitimately, genuinely, correct.

To take the literal meaning of its name, VPP is just about having the power plants virtually displayed online. I am not a IT guy, I would guess there is nothing fancy about it. But that’s only the start of an entirely new evolution. What you do with the “digital copies” of the plants with all the “Big” data collected afterwards is in fact what defines virtual power plant. All kinds of the VPP derivatives, such as Asset Management, Demand Response, Micro-grid Management, Load Shedding, just to name a few, are the results coming out of this process. In here, Data Analytics and Optimization are 2 mostly used methodologies.

“Data Analytics” is less of a trouble to explain – anyone can bullshit in all sorts of directions and still manage to be right, it is simply too big a target to miss. Optimization, on the other hand, can be quite challenging to grasp its essence. It is often misunderstood, underestimated, or mixed up with the concept of Data Analytics. Don’t get me wrong: optimization is probably part of Data Science in academic terms thus shares the same umbrella with Data Analytics. But if we are to look at it in the perspectives of business use cases and project deliverables, I would rather distinguish these 2 terminologies right from the beginning.

It is quite difficult to explain with pure text, so I made a table here to help me doing comparison.

VPP DA OPT

, , ,

Leave a comment