Posts filed under “Blog”

Seasons of Work: Summer School Part 2

This is a “show your work”  post about sharing some of my thinking around  my own career development.  You can read Part 1 here

Last year, I wrote about my strategy of taking online courses in the summer (click here for a refresher). As I’m well into my semester, I wanted to share some of the things I’ve learned as I’ve refined my process. I think it’s amazing that we live in an age where we have access to the best professors at leading universities FOR FREE.

This Summer’s Courses: 

  • Online Games: Literature, New Media & Narrative (Vanderbuilt University)
  • Social and Economic Networks: Models and Analysis (Stanford University)
  • Networks Illustrated: Principles Without Calculus (Princeton University)
  • A Life of Happiness and Fulfillment (Indian School of Business)


1) Choose your platform wisely: I love the coursera app.

Screen Shot 2015-08-01 at 11.43.59 PM

Last year, I took a few classes on the MIT Open Courseware platform, but I found it bulky and annoying. It took me twice as long to complete the courses because it was such a pain.  I’ve been using the Coursera App obsessively ever since and I love it for several reasons.

  • It has an easy to use design, especially on mobile devices. User experience is key for me, especially if I’m going to be frequently accessing the app. I found the app to be intuitive and well designed, and it’s made it painless to access and interact with content.  It’s super easy to add, delete and change courses too.
  • You can download videos and course materials for offline viewing. This has been my favorite feature! As I wrote in my last post, I like to maximize my enjoyment of summer weather, and this app makes it easy to consume course materials on the go, meaning I can catch a lecture while I’m out and about – preferably on a nice patio or by the seine. Alternatively, you can power through a bunch of lessons on long airplane rides, making your travel time productive and interesting. Especially if you fly in one of United’s old, horrible airplanes that have no televisions oroutlets. (Seriously United?? Not even an outlet?!)


2) Build it into your weekly schedule

One of my favorite quotes comes from Tim Ferris’ Four Hour Workweek. He says: A lack of time is a lack of priorities. Here’s what I believe: continuous learning is essential for professional development. So it’s a priority for me. I make time for it in a way that makes sense to me and I’m realistic about what I can and can’t accomplish.

I purposefully schedule my courses in the summer because I make a conscious effort to scale back other responsibilities. I would totally fail at completing them if I tried to do it in the winter, which is one of my busiest times. I set aside time each week to sit and study some of the material. The day of the week might change depending on my schedule, but I always make sure I include the time.

Find the cycle that works for you: is it 20 minutes a day? An hour a week? Make it work for you. Self-paced learning means there are no excuses to making it fit with your schedule. Commuting time, waiting in line, coffee breaks, workouts, while cooking – there’s always an opportunity to listen to one of the lectures if you know where to look

Pro tip: Depending on the complexity of the material, I can increase the speed of the videos to 1.5 or 2x the normal speed without losing comprehension. If it’s really technical stuff, then I won’t multitask and will listen to it at normal speed. Experiment and see what works!

3) Be realistic about what you can do

I’ve learned that consistency is far more effective than quantity as a metric of achievement. When I first started, not only did I completely underestimate the time it would take to complete the materials, but I set up crazy expectations about how much time I was going to devote to this every day.

I have since learned that it’s better to set the expectation of constant forward momentum. I don’t force myself to adhere to the course schedule, because I’m auditing the courses, I don’t feel the pressure to stick to their timelines, and focus on completing the course in a way that makes sense to me. There’s no harm in starting with one course if that’s all you have time for.

I’ve managed to take more courses without getting overwhelmed by just making sure that I did something consistently. Even if all I could do one week was listen to 30 minutes or 10 minutes – who cares! It’s better than zero, right?

4) Figure out how to capture the information

Last year, I took a bunch of notes in my moleskin as I was going through the courses, but I didn’t plan out how I was going to use the information. This year, I think I’m going to type up my notes, and create a filing system for them online (Evernote or simplenote are great for this.) I’ll be sharing some of my outlines as well, so be sure to subscribe to my newsletter if you’re interested in getting those!


5) Always Include A Wildcard

Wild Card

Most of the courses I take are centered around the digital space, big data or strategy. However, I always make sure I include one totally random course. You never know what will inspire you. Incorporating different schools of thoughts and unrelated subject matters will only enrich your knowledge base. This year, I’m taking A Life of Happiness and Fulfillment because I think the premise is super interesting.  Other wildcard courses on my To-Be-Learned include:

  • The Psychology of Popularity (University of North Carolina)
  • Superhero Entertainments (National University of Singapore)
  • Soul Beliefs: Causes and Consequences (Rutgers, State University of New Jersey).


I hope you found this post helpful and are inspired to kick start your own  summer school. If you’re into lifestyle design, I’ve written about it here and here. Happy learning!


If you’re interested in staying updated about my research, upcoming books and general cool things I find online, sign up for my monthly newsletters and get my best stuff first. Subscribe here.  

When Robots Weep Who Will Comfort Them?

This post explores some of my thoughts around concepts of Digital Culture.  You can find the other related entries HERE. 

*** This is an excerpt from the June Issue of Red Thread’s monthly newsletter. ***






What if one day, someone told you that you weren’t human – but a sophisticated sentient machine that was engineered in a factory. Your memories, your emotions, your habits, your quirks – everything that makes you unique – are all just binary code running in the background of an advanced operating system. Would you still consider yourself human? (If you’re intrigued by this premise, check out Battlestar Galactica.)

This month, we’ve thinking about the complicated interactions that take place between humans and technology.

Scientists have been trying to isolate the characteristics that differentiate us from other species for hundreds of years. The addition of technology into the mix has only further confused the issue. Frombiometric contact lenses to implants that enable us to control artificial limbs with our mind – we are redefining our relationship with technology on two fundamental levels.


1. Looking Inward: How much machinery can we integrate into ourselves while still being human? 

In last year’s RoboCop reboot, the main character, Alex Murphy, must face his own definition of humanity when his consciousness is transferred into a robotic cyborg. He discovers all that is left of his physical self are his lungs, one hand, and most of his head. Let’s just say, he doesn’t take the news well. If you take away the flesh and bones of a man, what does he retain?
2. Looking Outward: What kind of relationships can we have with machines? 

A 2007 study reported that people who owned Roombas (small, autonomous robotic vacuums cleaners) developed deep emotional attachments to their device, including giving it a name, creating customized covers for it, and even rearranging the furniture to accommodate it better.

Soon, the technology will be smart enough to recognize and even reciprocate our feelings. David Levy, AI expert and author of “Love and Sex with Robots: The Evolution of Human-Robot Relationships predicts that by 2050 “Robots will have the capacity to fall in love with humans and to make themselves romantically attractive and sexually desirable to humans.”

In her book The Human Age, historian Diana Ackerman wonders whether machines can ever possess that intangible spark that makes us human.

Key quote:


[Robots] will never be embodied exactly like us, with a thick imperfect sediment of memories, and maybe a handful of diaphanous dreams.

Who can say what unconscious obbligato prompts a composer to choose this rhythm or that — an irregular pounding heart, tinnitus in the ears, a lover who speaks a foreign language, fond memories evoked by the crackle of ice in winter, or an all too human twist of fate?

I don’t know if robots will be able to do the sort of elaborate thought experiments that led Einstein to discoveries and Dostoevsky to fiction. Yet robots may well create art, from who knows what motive, and enjoy it based on their own brand of aesthetics, satire (if they enjoy satire), or humor.

How Can Organizations Encourage Innovation?

This post, is a part of my thinking and research for my new book, centred around the tensions between productivity and creativity. You can follow other related entries here


I was in Sydney, Australia talking to the team at the Commonwealth Bank of Australia about innovation and the future of banking. One of the questions that came up several times during the day centred around the Culture of Innovation and what organizations needed to do – in concrete terms- to help bring some of these cultural changes about.


1) Innovation is the end product

Many organizations maintain that they want to build a culture that values and prioritizes innovation and yet lack a fundamental understanding of the changes that need to occur on an individual, team, and leadership level to make those changes a reality. It’s important to remember that innovation is the end product that occurs after many other factors have aligned.

In my Innovation and Disruptive Business Models class that I teach at Science Po, I spend a fair chunk of time identifying and addressing the various constraints that prevent innovation within an organization.  I always start at the individual level. Innovation stems from having the ability to take inspiration from the world around you and make new connections. It requires a certain level of creativity.

There is a common misconception that creativity is an integral part of a person’s individuality but research has revealed a different story. It turns out that creativity is underpinned by a collection of habits that can be strengthened and built up with diligent practice. These habits are Perception, Intellection & Communication. (I’ve written about this topic more here.)

At a team level, employees need to develop an understanding of how to manage conflict and different styles of ideation. I recommend taking the Basadur applied creativity that identifies how you approach problem solving. It helps identify each member’s communication style and highlights how to best communicate with each other.


2) Time to think

From an organizational level it’s amazing how many organizations expect their talent to continuously come up with good ideas and yet never give them the chance to do so. When this issue came up in discussion, I asked the crowd: How many people have time to  sit and think about their long term strategic goals on a regular basis? No hands went up. “I do some of that thinking on my commute home,” one gentleman offered. Another woman said she tackles those issues on the weekend while her kids nap.

Now this isn’t just the fault of organizations. We, as a work culture have become a little too productivity-obsessed. We like to fill our day to the brim with meetings, calls, emails and other busy work that give the impression of progress when in reality we are just reacting to the needs and priorities of others instead of doing the deep thinking we need to really tackle some of those business challenges.

I subscribe to Cal Newport’s deep work approach to personal productivity.  I usually try to structure my most important work into 90 minute sprints where I’m totally focused on only one task: no calls, no emails, no Facebook. Then I’ll take a 20 minute break and repeat the process through out the day. I’ve started carving out 90 minutes a day where I just sit and think. Whether it’s about a new project, new ideas, things I’m writing about – I use that time to stop and take the time to just let my brain process what’s been going on.

At first, it felt really uncomfortable. I felt like I was just wasting time  by sitting around and not DOING anything. But, it turns out that that little window of time was a life saver. It helped me prioritize the things that were the most important to my business, as well as gave me the time to be proactive and forward looking instead of constantly reacting to emails and requests.


3) An Honest conversation about failure

Failure is something that keeps coming up when you talk about innovation. One of the major reasons that radical (or disruptive) innovation often has such high rewards is because the risks are equally high. Radical innovation is unpredictable and requires a huge investment of time and resources. Unlike incremental innovation, we can’t always predict how it’s going to go. Many organizations can’t stomach this type of risk and while they say they understand that failure is a part of the process, their organizational culture still shames people who fail.

I should point out here that failure does not mean someone who isn’t doing their job adequately or up to standards, but rather someone who takes a risk by trying something new. Trying is the only way we learn if it’s going to work or not, so I would really encourage you to look inside your organizations and see how you define, react and encourage (or discourage) failure and how those things could be hurting your team’s ability to come up with good ideas.


Once we start digging into innovation we see that the brilliant ideas that emerge, can only do so within the right conditions. Instead of focusing on innovation, we should focus on creating the space where it can thrive within our organizations.

If you’re interested in staying updated about my research, upcoming books and the cool things I find online, sign up for my monthly newsletter and get my best stuff first. Subscribe here!  


Technical Literacy and Budget: 2 Hurdles for Big Data? [Amsterdam]


Thalys Train

This post is a part of my thinking around the concepts I wrote about in my latest book, “THE DECODED COMPANY: KNOW YOUR TALENT BETTER THAN YOU KNOW YOUR CUSTOMERS.”  You can see some of my other thoughts about big data, organizational culture and talent management HERE

I’m currently writing this from the Thalys train that is speeding from Amsterdam back to Paris. I am marvelling at the wonders of the modern age: traveling between two countries (three if you count our stop in Brussels) is seamless and I am comfortable and happy thanks to roomy seats and free wifi. One of the main benefits of living in Europe has been access to these amazing trains systems. I always prefer trains to the security hassle of removing shoes and putting liquids in tiny plastic bags. 

I was in Amsterdam keynoting  an event, and the conversations I had with some of the attendees afterwards got me thinking. Data literacy and budget constraints are the two hurdles I hear about most frequently that are standing in the way of organizations interested in embracing the Decoded Model.


1. The Decoded Model is a Philosophy

The great thing about the Decoded Model is that it encompasses a unifying philosophy to integrate analytics, not just a tactical response. This means that you can have 10 companies who are using the Decoded Model in 10 very different ways. This isn’t a solution  you pull off a shelf and plug into your organization. It’s a very powerful resource that helps bridge strategic vision,  cultural objectives and analytics together in a cohesive and coordinated way. So if you’re a small team or a huge multinational, our thinking around people, technology, and culture can be successfully implemented.


2. Being Decoded is not binary: It’s a spectrum

For some reason, there is this weird, persistent belief that implementing Big Data initiatives is an all or nothing approach. This is not true! Being Decoded falls on a broad spectrum. A small team who is looking to implement Technology as a Coach to create customized learning is going to have a different budget and scale than a company with 30,000 employees seeking to do the same. They are both applying the principle but in very different ways. This is good news: it means that no matter what your constraints are there is a spot for you to become Decoded in a way that makes sense for you and your team. This goes double for your technical competency: you don’t have to know how to code or be familiar with databases and algorithms to get started. In writing the book, we made sure to include experiments and easy to complete tasks that addressed a variety of skill levels.


3. Money isn’t the issue.

The other big issue that gets mentioned quite often is always about money. Isn’t data expensive? Clients tell me that they don’t have the budget to invest in customized analytical solutions. Once again, budget is a constraint that falls on a spectrum. A small company with limited budget shouldn’t have to invest hundreds of thousands (or millions) into a customized platform. It doesn’t make sense! Instead, when looking at the Decoded Model know that there are many inexpensive or free tools that can help you get started without a large capital investment.

I should note that while there are a multitude of ways to implement data and analytics inexpensively, doing so will always require a significant investment of time: it will take awhile to familiarize yourself with the new and available tools and  to deeply examine your own systems and processes to spot areas where you can apply the Model. I wrote a few months ago about some easy ways for companies to track their productivity, that you can use to help you get started right away.


Don’t Psych Yourself Out!

The biggest hurdle is often a mental one: letting go our beliefs or assumptions about what we think big data and how we can use it to make better decisions. Remember, if you have a piece of paper and a pen – you can be Decoded. Know how to use an excel spreadsheet? You can be Decoded. Have a budget of $0? You can be Decoded.

Interested in applying the Decoded Model to your team? Check out my MasterClass.



If you’re interested in staying updated about my research, upcoming books and general cool things I find online, sign up for my monthly newsletter and get my best stuff first. Subscribe!  

Be Informed Not Afraid. Don’t let Big Data Scare You.

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The Arcadia (via P&O Events)

This post is a part of my thinking around the concepts I wrote about in my latest book, “THE DECODED COMPANY: KNOW YOUR TALENT BETTER THAN YOU KNOW YOUR CUSTOMERS.”  You can see some of my other thoughts about big data, organizational culture and talent management HERE


Data Is Everyone’s Responsibility

Last week, I had the opportunity to keynote the IT Directors Summit and HR Forum at a very interesting venue: a cruise ship. Getting there was an adventure, my very own version of trains, planes and automobiles! I took the Eurostar from Paris to London followed by the Gatwick Express to the airport. I few to Guernsey, a small island in the UK that is apparently also a phenomenal tax shelter. Finally, I boarded a small tender that took me aboard the Arcadia.

I spoke about the importance of understanding the possibility of analytics – not just from a technical standpoint but from a strategic and cultural perspective as well. Too often, many people assume that Big Data (or not-so-big data as we call it) is outside of their job function – and this couldn’t be further from the truth. The reality is this: data is everyone’s responsibility.

As an employee it is up to you to be informed and engaged with your organization’s data policies. We must each be accountable for own data footprint and that means asking for clarity and transparency when needed.

  • Do you know exactly what data your employers are tracking?
  • Do you know how they collect it?
  • What do they do with it?


The Vital Role of Transparency: The Corporate Public Record

Many employers cover some of these policies in handbooks but it never hurts to get extra clarifications. For example, many organizations use swipe cards for security purposes.  At my co-authors’ company, Klick, the door swipe data is used to track your location and the number of steps you take – information that has been very transparently communicated and easy for people to access and understand. Klick has taken the time to explain to their employees exactly what purpose they have in mind for the data: in this case the number of steps is used to foster friendly competition between colleagues to see who can take the most steps and encourage a culture where people make healthy choices by taking the stairs instead of the elevator.

Guernsey. Flickr: stephoto, CC

As an employer or manager, you must make sure you asking the right questions about any new data initiatives to make sure they are ethical, transparent, and helping to build a positive work culture. In The Decoded Company, we outline a set of guidelines to help executives assess the ethicalness of their policies. We stress the importance of being open and transparent about the data being collected and introduce the concept of the Corporate Public Record – job-focused metrics that can be used to measure performance without invading an employee’s privacy.  Too often, we let technology or a desire for more data blind us to the cultural ramification of introducing invasive data policies that end up breaking trust and damaging the working environment.


Pairing Culture and Analytics Is Key

Klick has been very clear about not using data for punitive purposes. The swipe card data that tracks when you get into work and when you leave are never used against you in performance reviews or reprimands. However, it is used to help Klick’s managers make better informed decisions. For example, if an employee has stayed late several nights in a row, Klick’s analytical system will ping their manager to let them know there might be a workflow issue. The purpose of this data is to help establish organizational culture norms: Klick values work/life balance and the company does not want to see employees staying late. This information is used to start a conversation that can uncover an underlying issue such as the need to hire more staff to handle demand. It enables managers to spot an employee who is at risk of being burned out and overworked before disaster strikes.


Interested in applying the Decoded Model to your team? Check out my MasterClass!


If you’re interested in staying updated about my research, upcoming books and general cool things I find online, sign up for my monthly newsletter and get my best stuff first. Subscribe!