Office Speak: Skate to where the puck is going to be

Imagine that you are sitting in your team meeting and you are in mid flow pontificating about your favourite subject, but you have a problem, you know that at the end of this sentence you have nothing left to say. There’s a real danger that you are going to fall off the cliff and into a dark void of silence. You need something to say and you need it soon. Fortunately you have a stock of cliches ready for this very occasion. Which one will you use? Which of the many are you going to leap to? Are any of them appropriate to this meeting? You flash through the memory cards in your head and settle on an old favourite:

“We need to skate to where the puck is going to be.”

And with that you conclude.

The team nod in agreement as your timely words, everyone apart from the young graduate who has just joined the team. She looks at you blankly:

“I’m sorry, but what does that mean.”

You open your mouth to explain and then realise that you don’t have a sensible explanation. You’ve used this term so many times before, but you’ve never really thought about what it really means, you can’t even remember where you first heard it. You’ve heard it used so many times that it’s become embedded in your psyche.

The reality is, this cliche is a quote:

I skate to where the puck is going to be, not where it has been.

Wayne Gretzky

As you may have already guessed, it’s an ice hockey reference. Wayne Gretsky was apparently quite good at it, not that I would know, I’m trusting Wikipedia.

The basic idea of the quote is that if you are going to intercept a puck your only hope is to go to where it is going to be by the time you get there. There’s no point in trying to intercept it by going to where it has already been.

The term is regularly used in the technology arena to describe the plans of organisations and their latest innovations. Steve Jobs used the term to describe the approach at Apple:

“There’s an old Wayne Gretzky quote that I love. I skate to where the puck is going to be, not to where it has been. And we’ve always tried to do that at Apple.”

Quotes from Steve Jobs tend to hit management-speak over-use in no time at all. Every manager dreams of being Steve Jobs after all.

How often the term is relevant in day-to-day business is debatable. There are times when it is very appropriate, but all too often it’s just being used as a filler and not got any authentic meaning.

The blog was brought to you by the word “puck” and the letter “w”.

Because it’s Friday: “Detour” a film by Michel Gondry

I’m feeling a little bit surreal today and this film by Michel Gondry fit the criteria.

The tricycle is definitely the star of the show, nut the singing fish are quite good too.

From a technical perspective, it’s shot entirely on an iPhone 7 (which is why it’s been published by Apple). Film making used to require equipment worth millions of pounds, there are clearly limitations to using a mobile device, but this video shows that film making can now be done an a very reasonable budget:

The Huge Failure | Dilbert on Open Plan Offices

I’ve really enjoyed the recent series of cartoon from Scott Adams on open-plan offices:

Some of the comments on these cartoons are just as fabulous:

Let’s not forget that cubicles were a massive failure before open plans managed to out-fail them.

Open spaces are supposed to invite the open flow and exchanges of Ideas. And they do, ideas like……”How bad traffic was this morning?….Did you catch the game last night?….how was your weekend?…..etc” Maybe some work topics might get discussed

Working environments is a very emotive subject and rightly so. Many of us spend more time at work than we do at home and we want to be productive.

What fascinates me is that many organisations spend huge amounts of money creating something that people don’t want.

Here’s something I wrote earlier: Productivity and place: Where are you most productive?

Because it’s Friday: Deeper Underground

Love it, or hate it, there’s no denying that the style and architecture of the London Underground is iconic. In this video take a walk down the middle of the tunnels, platforms, escalators and stairs. Someone had some very late nights to get all of these places with so few people in them.

We have a thing with tunnels. The underground of London is one of the most impressive infrastructures of the world. It’s a network that transports millions of people every day. Some call it hell. We see beauty.

The infinite tunnels pull us in with their symmetry. The ceiling lights guide our eyes to the horizon. The tiles and posters form patterns that please the eye. The echoes of rushing crowds, a flickering light, a train zooming by.

Humans and Robots: The AI Over-hype and Sorting Lego

Last week I was on a remote island in the Outer Hebrides, we had WiFi at our cottage but it was slow, we didn’t have any mobile signal. There was a mobile signal in the nearby town, 3 miles away, but again, that was slow and covered a small portion of the island. It was a great reminder of how much we take connectivity for granted and that for much of the world that assumption is invalid.

Whilst I was away though there have been a number of AI, Machine Learning and Robotics related things happening:

As seems to be the case for all technologies a point is reached where people need to talk about the negative aspects including the hype-levels of the current hot tech. That has been the case this last week with MIT and others running stories. The MIT Technology Review one is looking specifically at IBM Watson and the perceived rate of progress it is making in healthcare. Progress in any technology is rarely a smooth ride and some high visibility failures are normal.

The MIT Technology Review has also been looking at the progress GE are making by using AI and Machine Learning. GE is going through a huge transformation that will embed advanced technologies and robotics into many of its products. This transformation is also radically changing the way people work with people taking on what would have previously been two separate roles. The role change is one that is already happening and I’ve got an post brewing on that.

The Guardian is the latest organisation to do a round up of the research and current thinking into the impact of automation on jobs:

“in the last 60 years automation has only eliminated one occupation: elevator operators.”

I’m not sure that’s really true, but I get the point. Aside from the statistics the core question people want to know the answer to is: “what can I do to prepare?” It’s not an easy question to answer, the only sure thing is that change is going to happen and humans have adapted to change for hundreds of thousands of years. That ability to adapt is what’s going to be key in the future, one way of being adaptable is to diversify and be able to take on multiple roles.

If you want to know more about Machine Learning then this nice Visual Introduction from R2D3 will get you started.

Jacques Mattheij had a dilemma, how to sort 2 metric tonnes of Lego which he did with some Lego (what else?), some hardware, python and a neural network. Although there won’t be many people with 2 metric tonnes of Lego I’m sure that many of us would love to be able to sort the boxes that do exist.


A Reality Check for IBM’s AI Ambitions via MIT Technology Review

None of those companies has garnered anywhere near the attention that Watson has, thanks to its victory on the television quiz show Jeopardy! in 2011 and zealous marketing by IBM ever since. But lately, much of the press for Watson has been bad. A heavily promoted collaboration with the M.D. Anderson Cancer Center in Houston fell apart this year. As IBM’s revenue has swooned and its stock price has seesawed, analysts have been questioning when Watson will actually deliver much value. “Watson is a joke,” Chamath Palihapitiya, an influential tech investor who founded the VC firm Social Capital, said on CNBC in May.


General Electric Builds an AI Workforce via MIT Technology Review

When Jason Nichols joined GE Global Research in 2011, soon after completing postdoctoral work in organic chemistry at the University of California, Berkeley, he anticipated a long career in chemical research. But after four years creating materials and systems to treat industrial wastewater, Nichols moved to the company’s machine-learning lab. This year he began working with augmented reality. Part chemist, part data scientist, Nichols is now exactly the type of hybrid employee crucial to the future of a company working to inject artificial intelligence into its machines and industrial processes.


What jobs will still be around in 20 years? Read this to prepare your future by The Guardian.

Today’s technological revolution is an entirely different beast from the industrial revolution. The pace of change is exponentially faster and far wider in scope. As Stanford University academic Jerry Kaplan writes in Humans Need Not Apply: today, automation is “blind to the color of your collar.” It doesn’t matter whether you’re a factory worker, a financial advisor or a professional flute-player: automation is coming for you.


A visual introduction to machine learning by R2D3

In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.


Sorting 2 Metric Tons of Lego by Jacques Mattheij

Computer skills to the rescue! A first proof of concept was built of – what else – lego. This was hacked together with some python code and a bunch of hardware to handle the parts. After playing around with that for a while it appeared there were several basic problems that needed to be solved, some obvious, some not so obvious. A small collection:

Concept of the Day: Campbell’s Law

Campbell’s law is defined by the following quote from Donald T. Campbell:

“The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.”

In other words: the higher the stakes associated with a measure, the more likely it is that the measure is corrupt and in so doing that the system being measured becomes corrupt.

If you put high stakes against a school exam the more likely it is that people teach to get a high pass mark and in so doing teaching become corrupt.

If you put high stakes against a business measure the more likely it is that people manage to the measure, or even falsify the measure, and in so doing corrupt the business.

There are numerous places where you can see this being worked out historically; the more important question, though, is where is this happening today?

What effect does it have if you stop people’s benefits if they don’t fill out a defined number of job applications?

What effect does it have if you pay a traffic warden on the basis of the number of fines they manage to issue?

What effect does it have if you fine rail operators for late trains?

What effect does it have if you pay doctors on the basis of the number of appointments they complete?

I’m sure there are many, many more.

This little video does a really nice job of explaining Campbell’s Law:

Office Speak: Sunsetting

The other day I received an email along the lines of:

On the first of the month after next we will be sunsetting the whatamI4 system.

I knew what it meant, but it struck me as a strange phrase to use.

I suppose I ought to explain what it meant for those of you who don’t understand the meaning. I’ll replace the word sunsetting with something else to see if that helps:

On the first of the month after next we will be turning off the whatamI4 system

That’s right sunsetting = turning off.

Sunsetting with 10 characters = turning off with 10 characters.

Sunsetting with 3 syllables = turning off with 3 syllables.

I suppose that’s my question, why not just say that it’s being turned off.

Returning to the original sentence, why not say:

On the first of the month after next whatamI4 will be turned off.

There you go, that’s shorter and simpler than either of the previous ones.

Or even:

whatamI4 will be turned off on the first of the month after next

I prefer this because it gives a much better call to action.

I’m not objecting to sunsetting it just feels like redundant complexity.

Perhaps I’m not being entirely fair though. There is a picture being drawn here and there is a difference between turning off and sunsetting. The term sunsetting is trying to communicate that the light is drawing in on a the application and that it’s time to move over to something else. Turning something off happens quite quickly, even instantaneously; sunsetting may happen over an extended period.

It’s not a word I hear people use in normal life though – it’s office speak.