Wednesday, September 28, 2016

End of an Era: Blackberry to exit hardware business

CBC reported that Blackberry is exiting the hardware business. The news doesn't come as a surprise. As noted in this interview with CNBC in June of this year, the interviewer notes how Blackberry was steadily outsourcing the manufacturing of its devices. The CEO, John Chen, also confirmed that they were planning on exiting the business if it failed to be profitable:

Blackberry was my first smartphone, the 8900, to be exact.

However, when I saw the Torch, I remember thinking that after using the device how it was the perfect compromise between the touch screen and the classic keyboard. However, that feeling faded quite quickly after using the device. It was so under-powered compared to the competition and of course it lacked the apps that you could find in the Apple AppStore. But at the time I could never imagine giving up the physical QWERTY keyboard.

Since then I have moved onto Android and more specifically to the SwiftKey keyboard - to the point I can't go back to a physical keyboard!

How did BlackBerry fail to keep up with the times?

As noted in this article, Mike Lazaridis the founder of the CEO, was inspired to develop the BlackBerry when he recalled his teacher's advice while watching a presentation in 1987 - almost a decade before the Internet - on how Coke used wireless technology to manage the inventory at the vending machines. What was his teacher's advice? His teacher advised him not to get swept in the computer craze as the real boon lay in integrating wireless technology with computers.

BlackBerry caused a storm in the corporate introducing it's smartphones in 1998. It went on to dominate the corporate smartphone market as the gold standard in mobile communications. The following graphic from Bloomberg really captures the subsequent rise and fall quite well:

What happened how did the iPhone, unveiled in 2007, and the Android Operating System outflank the Blackberry?

This article in the New Yorker larger blames BlackBerry's inability to understand the trend of "consumerization of IT": users wanted to use their latest iPhone or Android device instead of the BlackBerry in the corporate environment - and was it just a matter of technology to make this happen.

Although luminaries, such as Clay Christensen, have written extensively on the challenge of innovation. And there's always the problem of hindsight bias.

However, is the problem more basic?

When we look at the financial crisis, some people like to blame poor modeling. But I think that is more convenient than accepting the reality that people got swept up in the wave.

Isn’t it fair to say that people knew that house of cards was going to come down (and some of the investment banks were even betting on it falling apart), but were overly optimistic that they would get out before everyone else does?

But that’s the point.

When we are in a situation where we are surrounded by people who confirm our understanding of the world – we may believe them instead of trying to see if our understanding of the situation is correct. With the housing bubble, the key players wanted to believe that those models were correct – even though models have failed the infamous Long Term Capital Management.

With BlackBerry, what I wonder is did they not even try to see within their families and those around them who were using the iPhone or Android devices? Weren’t they curious what “all the fuss was about”?

Although this is problem with many of us who want to believe that the present situation is going to continue indefinitely (especially when things are going our way), there are others who do stay on top of things. Most notably is the Encyclopedia Britannica that actually stopped issuing physical encyclopedias and moved to the digital channel instead.

Change is a challenge, but the key is to be prepared to admit that the current way of doing things can be done better, faster and in radically different way.

Thursday, August 4, 2016

FlightDelays & Contingency Planning in Real Life

Photo Credit: Trey Ratcliff

Last week, I had headed to a day long conference on Thursday in New York and was expecting to return home on the 7:20 flight back to Toronto.

However, things didn't goes as planned: La Guardia (LGA) had cancelled a number of flights due to weather delays.

I decided to haul it back renting a car through a one-way rental.

Originally, went to Hertz but they refused to rent to me because I was heading back to Toronto, Canada. If you can believe it, they advised me to rent to Buffalo and then take the bus back to Toronto. Yeah right!!!

Thank God, Avis did not give me such a ridiculous advice and instead gave me the car to  make my way back home. Ended up leaving Avis around 8:45 and made it home around 4:30 AM. One big advantage of travelling at that time of the night is that there is no traffic :)

Thinking about this after the fact, I realized it was a good lesson in "real life" contingency planning, so here's what I think I did right, could have done better and otherwise.

What I did right:
  • Call the travel agent instead of waiting in line to talk to the airline: I had already cleared customs and was lining up at the Air Canada desk inside LGA realizing that my flight was cancelled. However, I decided to call the travel agent (while in line)  to see what the situation was at other airports (JFK, Newark) and to see what my options were. That's where I learned that I would be flying out at 11:30 am on Friday (i.e. the next day). 
  • Avoided flying out on Friday: Didn't realize this at the time, but my chiropractor told me that after a major flight cancellation the airport is dealing with at least twice the volume the next day - especially since it was Friday and everyone would want to get home for the weekend. Consequently, how much rest would I get if I had to be back 3 to 4 hours earlier the next day to make sure I got on the plane? My fear at that time is that either the weather delays would continue or something else would force me on a later flight. 
  • Would any hotels be available? Given that many people had their flight cancelled, the hotels would likely be booked. Also, if I had to book outside the airport then I would have to battle morning traffic on the way back in. So it didn't seem like an appealing option. 
  • What's crazy to most, may be open to you: The 8 hour drive back did seem daunting. However, most wouldn't do such a crazy thing thereby making it a viable option - since everyone else would be trying to get on a plane there would be plenty of supply for me in terms of getting the rental. Or at least that's what I expected and it turned out to be right. Also, when I spoke to the travel agent she told me that someone else from Deloitte was looking to carpool back to Toronto. Unfortunately, I just missed him. However, realizing someone else is doing made it seem less crazy. And truth be told those cars were getting booked fast when I got to the car rental companies - many people were driving to Boston, Pittsburgh, etc. 
What I could have done better:
  • Monitoring for weather: When my flight got delayed on the way in on Wednesday that should have been a clue that there could be problems the next day. In the future, I should keep track of weather conditions and been mindful. 
  • Monitoring for cancellations: Although I had checked in via my mobile app, I had been using a low power mode for the iPhone. This prevent me from being alerted right away. The reason I was on lower power mode is that the conference organizers didn't have outlets at the table and so I wanted to make sure I had battery power to call/email/etc. at the airport. Next time, I should sit near an outlet or have portable power source to make sure that I can charge my phone at the airport or on the plane. 
  • Book a car sooner: If I had learned about the cancellation sooner, I could have made alternative arrangements sooner. At least I could have booked the car and procured it closer to where I was at, instead of wasting that time driving into the airport. 
  • Noticed airport irregularities: There were more people queuing up at the Air Canada counter outside the security area. However, I just dismissed this as volume. However, the lower volume in the security area should have been my second clue that something was awry. 
  • Check the rental for damage:  I was so focused on getting on my way, I didn't check. As it turns out, the car was damaged massively on the front. Fortunately, the guy letting me out noticed that and wrote it on the form. It's hard, but in an emergency situation it is important to make sure to keep a cool head and not make such errors. 
Otherwise: One thing that stuck in my mind is missing the fellow Deloitte colleague on the way back to Toronto. Was there a better of organizing ourselves so if something like this were to happen again, we could car pool? How can we trust each other if we don't work at the same company? I think that setting up an app and getting subscribers to sign-up ahead of time wouldn't be feasible because most people don't think about getting stranded at the airport - let alone finding a way to trust each other using user reviews. 

Contingency plans: test, test, test.

My biggest takeaway from this experience is that you can't know how good a contingency plan is until you actual do a real live test. 

And unfortunately most companies overall don't test their plans. 

As noted in this Business Continuity survey, Deloitte categorized managers as "aware" (i.e. those who know there's a problem) and "committed" (i.e. those that are willing to take action to resolve it). Out of the Committed group basically only 50% had tested their plans, while the aware group only 17% had tested their plans. 

With real estate it's location, location, location, but with business continuity plans it's test, test, test. As noted above, I realized a number of gaps in my contingency plan that I never would have known until I experienced this real-life emergency.

Wednesday, July 27, 2016

Reflections on the demise of Yahoo!

By now we've all heard that Yahoo!'s web assets were bought by Verizon. According to the Wall Street Journal, Verizon paid $4.83 billion in cash for the assets. Yahoo itself will continue to hold the remaining assets but will eventually change its name and become an investment company. In total, the company was rumoured to be worth $6 billion.

For us Gen Xers this is an interesting day: we witnessed the end of a company we saw as innovative and fresh just a "few" (i.e. read ~20) years ago.

I was recently explaining to a young lad in his early 20s about life before the Internet: you had to find books at the library and it was almost impossible to connect socially with people beyond your classmates. So to use Yahoo or other search engines to access information or people was a completely new and mind-blowing concept.

As I noted in this post commemorating Google's 17th anniversary:

"It's especially memorable for those of us who were in university in the late 90s because we had access to high speed internet on campus unlike the painfully slow dial-up at home. 

I remember my first job as a coop student at the UW Federation of Students (I can't believe this quote is still hanging around from that time!) when a co-worker was explaining to me how OpenText was the best search engine (of course using my NetScape Browser). Of course back then there was a number of search engines including, Yahoo, Lyco, Alta Vista, etc. However, I stuck to OpenText for a while then eventually switched, along with everyone else, to Google...Well Lycos, OpenText (as a search engine) and AltaVista may be long gone, but it looks like plaid is back!"

So now we can add Yahoo! to the pile of "has beens" search engine.

Beyond nostalgia, I had the following reflections on the Verizon of Yahoo based on the WSJ article above:
  • Verizon is no longer just pipes: Verizon has a strategy to move beyond just serving mobile and broadband services. Verizon is adding Yahoo to its existing portfolio of content plays, such as AOL. For Verizon, it's an overall strategy to make billions through content and advertising. Net neutrality can potentially limit their ability to use this vertical integration to undermine competition, but regardless it shows how being a "pipes-only" company is not enough. Of course it is a bit ironic that former rivals, Yahoo and AOL, are now sitting in the same tent.  
  • Big Data is monetized at the expense of privacy: The ability of Verizon to combine the data plays between its various content plays is a great illustration of a point that I have noted before: for big data achieve value it must water down privacy. Since there are synergistic values (i.e. instead of just being additive) of combining the data, it could be argued that it's something that a user should explicitly consent because a user may simply not want Verizon to use their Yahoo data this way.  
  • Remember the Internet Bubble? Yahoo! had a market capitalization of "more than $125 billion at the height of the dot-com boom in early 2000", which is quite a steep decline to $6 billion. I wonder if it ever produced the cash flows to justify that valuation. 
  • Algorithms win over people: WSJ today published a good read comparing the algorithmic approach of Google, in contrast manual effort required to index the Internet. This is similar to Amazon's who found that the algorithms to better than humans in getting people to buy things: "Amabot replaced the personable, handcrafted sections of the site with automatically generated recommendations in a standardized layout," according to The Everything Store, a new book exploring the history of Amazon. "The system handily won a series of tests and demonstrated it could sell as many products as the human editors."
  • Innovation and exponential thinking: On a separate note, but related note Yahoo could have bought Google for $3B in 2002 but it didn't. It's a great example of how Google embraced leading-edge technology to deal with the exponential growth of the Internet and Yahoo's inability to recognize Google's approach as the winning approach led to its demise.

Yahoo! is now literally a shell of its former self - both in structure and the assets it holds. However, it's a good case study of how failing to identify exponential trends - and acting on them - can ultimately lead to disaster.

Monday, July 25, 2016

Hacking reading: Is there a better way?

Came across Google's latest use of machine-learning: making "e-comic books" more readable.

One of the challenges of reading such fine literature on a mobile device is the small print that is within the bubbles.

Google's solution? Bubble Zoom.

As per Ars Technica:

"Google is tackling this problem the way it seems to be tackling every problem lately: with machine learning. Google has taught its army of computers to detect the speech bubbles in comic books, allowing you to zoom in on them with just a tap. The bubbles lift off the page and get bigger without affecting the underlying image. This lets you see the entire page while still reading the text. Google calls the feature "Bubble Zoom.""

Here are a couple of screenshots that show how it works:

For those that want to try this out on their Android device, you can download some free preview titles on the Google Play store.

Of course the obvious point, as mentioned by Ars Technica above, is that machine learning is being by Google and others to solve such interesting problems. The entire DC and Marvel comic book library has the Bubble Zoom feature enabled, which shows the power of machine learning to essentially reconfigure a massive amount of content.

The other point worth noting is how this technology fundamentally alters the way we consume text.

We have different channels, video, podcasts, and audio-books and can access books digitally but plain old reading has not changed that much. Zoom Bubble attempts to do that by building interactivity into the traditionally static medium of comic books.

To be honest I was surprised when I polled my IT Audit and Innovation class in January 2016 to see really none of them had shifted to e-books. They still rather have the physical copy, highlight and take notes.

That being said, a lot of credit should be given to Amazon for trying to go a long way to make it comfortable to read and enable you to access the content from multiple devices.

I’ve been experimenting with e-reading the Kindle, Samsung Note 4, iPad and iPhone.

The reader of choice depends on how you absorb information. If you want to savor your book and slowly digest, then Kindle is the easiest on the eyes

However, for us reading-for-productivity, i.e. if you are the type of person that needs to highlight and then extract notes, for the purposes presenting, researching, or blogging, then I think the Note 4 or the iPad is best. 

With the Kindle ecosystem, when you highlight the text (regardless of the device) its captured and stored on the cloud and then you can always access your notes there. For example, I highlighted the text below on my mobile device and it appears in the cloud (i.e. by logging into 

“ although GitHub is currently optimized for developers, similar platforms will eventually emerge for lawyers, doctors, publicists and other professionals. The platform has already been extended into enterprise software development with a successful paid business model, and can or soon will be used by governments, non-profits and educational institutions. GitHub charges users a monthly subscription—ranging from $7 to $200—to store programming source code. Andreessen Horowitz, one of the world’s leading venture capital firms, recently invested $100 million in GitHub. It was the VC firm’s largest investment round ever.”

In terms of iPad/iPhone versus Note 4, the Note 4 you can use its stylus to highlight text but you have to take an extra step to select the colour you want (you have 3 colors to choose from). In contrast, with iPad/iPhone you can just pick the colour right from the menu that pop-ups when you select a piece of text. The iPad’s larger form factor is also good for scan-reading. Of course the advantage for me on the Note 4/iPhone is that it’s my mobile device so it eliminates the need to carry around extra device.

One way to improve the readability is to change the background colour to Sepia from white. I have found it to be easier on the eyes.

The ability to move through multiple devices shows the brilliance of Amazon harnessing the power of open, mobile, cloud and seamless connectivity across platforms.

They could have gone the closed approach, i.e. you have to read their e-books off of their device. But by being open it enables the consumer to consume content in a manner that works for us. Microsoft has gone down this road as well with Office. I originally thought this was a bad idea but later recanted.

On a more critical note, as I have blogged before Amazon offers to US customers ONLY the ability to sync their audiobooks (Audible is owned by Amazon)  to their kindle ebooks for certain titles. It would be nice if this feature was also available out of the US.

What I've found to be a productivity hack, is to listen to the audio book on my Audible app at 2-3X speeds while driving around. I've self-diagnosed myself as an audiolearner it does help to learn things and get a good grasp of the topic. Such an approach can also help get the overall context of the material being presented. The Audible app enables you to bookmark, so that is a good way to track what you have to read up later.

Then I go through the Kindle e-book and highlight the parts I want to extract off the cloud. You can do this on the commute in or just waiting in line. The trick here is not to re-read the book but just extract those pieces of texts you wanted to focus on while listening to the audiobook. Moving the bookmarks from the audiobook to the e-books acts like a secondary review ensuring you've extracted all the content that's relevant to your presentation, research, blog post, etc. Alternatively, moving from the audiobook to the e-book may be the way you actually digest the content if you are more of a visual/text oriented learner. I personally need to do this with numbers and dates.

Finally, if you want to move the highlighted text off the cloud, try this to move the content to Evernote.

Although I think there are better ways out there to hack reading, I think the Amazon ecosystem goes a long way to get us there. One day, I hope, they will bring Immersion Reading to the world :)

Wednesday, July 20, 2016

Passwords: How's that still a thing?


How is this topic still a thing? 

In two words: Mark Zuckerberg. 

In June 2016, Mark Zuckerberg got hacked and his secret password was revealed for all to see. Did it meet all those wonderful rules we learn in information security school? Was it ISO27001/2 compliant? 

Well his password was "dadada" - so I'll let you decide. 

The Wall Street Journal's Nathan Olivarez-Giles had a great article on hacking/passwords. 

The article refers to a site where you can check to see if you've been hacked - definitely worth checking out. 

Of course the next step is to then change the password on the 7 million devices you own, but who says hackers make your life boring? 

Passwords are the best illustration of trade-off between convenience and security: you don't want the bad guys getting but at the same time you want to make it easy to use your email and the other services that you use.

One possible antidote to this unending saga of deal with hackings - managing the convenience versus security divide - is the use of password manager services. 

WSJ's Geoffrey Fowler had an article which reviewed "1Password, Dashlane, LastPass and PasswordBox"; giving the win to Dashlane.

Of course two factor authentication, as Oliveraz-Giles points out, is a key control that we all need to implement in our lives - especially since many popular services are making it easier two use such a feature. 

The fact passwords continue to be an issue reminds us that the most challenging aspect of a system is not the technology, but the people that use them.

Tuesday, July 19, 2016 The inaugural meetup

Just finished attending a meet up sponsored by The room was filled to capacity - illustrating the excitement around the disruptive technology right here in Toronto. 

Alan Wunsche, co-founder of the organization, walked through the road map of the non- profit organization, which looks at multiple initiatives to raise the profile of blockchain in Canada and prevent the departure of luminaries in the field, such as Vitalik Buterin (Alan wasn't so specific, but I decided to read between the lines).

The organization is driven by community, and the thoughtware to be produced by the group will rely on the volunteers. For example, I volunteered for the accounting working group to explore Canadian initiatives around triple entry bookkeeping and alternative accounting models.

For those interested, in a deeper dive into blockchain checkout their blockchain hackathon this weekend.

Monday, July 18, 2016

Big Data and Predictive Policing: Can algorithms become racists?

Interesting article on Forbes by Thomas Davenport on Big Data. The articles discusses how various government, including Canadian Public Safety Operations Organization (CanOps), have used big data tools for "situational awareness". These systems draw on myriad sources of data to give users (e.g. law enforcement) the information they need to deal with a particular situation.

Here are a few points that I thought were worth noting:

Government is making strides in big data: We often think of Amazon, Google and other tech-giants as key users of this data. However, as the Davenport points out that the government is using this technology to assist with decision making. However, whether this is something that should be celebrated remains to be seen (see predictive policing below)

Privacy versus Value trade-off: He talks about how CanOps use of MASAS, the Multi-Agency Situational Awareness System, is limited by the filtering of sensitive information: "breadth of MASAS is noble, but it seems to limit its value. For example, as the CanOps website notes, because agencies are reticent to share sensitive information with other agencies, all the information shared was non-sensitive (i.e. not terribly useful)." It seems that this continues to be a theme that we had noted in back a couple years when discussing a similar trade-off the companies face when dealing with big data. As I noted in this post:

"privacy policies require the user to consent to a specific uses of data at the time they sign up for the service. This means future big data analytics are essentially limited by what uses the user agreed upon sign-up. However, corporations in their drive to maximize profits will ultimately make privacy policies so loose (i.e. to cover secondary uses) that the user essentially has to give up all their privacy in order to use the service."

Consequently, there still needs to be a solution as to how privacy can be respected but organizations can use the data they have collected to make better decisions.

Predictive Policing is an emerging reality: The sci-fi movie, Minority Report, paints a future where law enforcement arrests people before they commit crimes.

That future seems to be well on its.  Davenport mentions how "predictive policing" was introduced in 2014 to the NYPD.  He also mentions how much data is being collected by the police:

"It collects and analyzes data from sensors—including 9,000 closed circuit TV cameras, 500 license plate readers with over 2 billion plate reads, 600 fixed and mobile radiation and chemical sensors, and a network of ShotSpotter audio gunshot detectors covering 24 square miles—as well as 54 million 911 calls from citizens. The system also can draw from NYPD crime records, including 100 million summonses."

The idea of predictive policing was also raised in the book,  Big Data: A Revolution That Will Transform How We Live, Work, and Think, which I had explored in a multi-blog post series (click here for the first installment).

Andrew Guthrie Ferguson, Law professor UDC David A. Clarke School of Law, wrote an article on how that predictive policing is something that has not be really sorted in out in terms of legality. He notes:

"The open question is whether this big-data information combined with predictive technologies will create “predictive reasonable suspicion“ undermining Fourth Amendment protections in ways quite similar to the stop-and-frisk practices challenged in federal court.

In two law review articles I have detailed the distorting effects of predictive policing and big data on the Fourth Amendment and have come to the conclusion that insufficient attention has been given at the front end to these constitutional questions. New York has the chance now to address these issues before the adoption of the technology and should be encouraged by the same civil libertarians and ordinary citizens who challenged the stop and frisk policies."

His commentary highlights another limitation: big data predictions are biased based on how the data is collected. The stop and frisk policies he refers to disproportionately targeted minorities. Furthermore, policing is more focused on poor, black/hispanic neighbourhoods. Michelle Alexander documents in her book, The New Jim Crow, how this happens:

"Alexander explains how the criminal justice system functions as a new system of racial control by targeting black men through the “War on Drugs.” The Anti-Drug Abuse Act of 1986, for example, included far more severe punishment for distribution of crack (associated with blacks) than powder cocaine (associated with whites). Civil penalties, such as not being able to live in public housing and not being able to get student loans, have been added to the already harsh prison sentences."

Consequently, if the data by law enforcement is used to predict crime that essentially the targeting of minorities will continue to target such groups given that it is based on biased data. 

Technology often is seen to be a silver bullet for problems. However, we need to keep in mind that it is vulnerable to the human element that makes it. Given Microsoft's recent faux pas of accidentally allowing an AI avatar to become a Nazi, it is something that should actively be considered in the systems that are built to police and govern.