Marks & Spencer just opened a store on Nanjing Xi Lu, replacing a Muji. Both are established brands in their home country (UK and Japan) and both manufacture and package their own products. Both have a similar product approach in terms of keeping things simple but are different in their design approach. Marks & Spencer is not exactly an exciting retail experience and Muji has far better product design and presentation from functionality to aesthetics. Muji is not doing that well here, as it requires a level of sophistication to appreciate it whereas Marks & Spencer is basically selling British quality and this will win in the short term.

Distribution has always been the greatest hurdle for retailers. The opening of the wholesale sector should lead to major improvements in the distribution environment, but there is a big gap. Strategies that successful foreign enterprises have employed to overcome distribution barriers include developing their infrastructures or partnering with the locals, and both has unique challenges.

In 10 years, its retail sector has been transformed from a simple and inefficient distribution system to a much more complex and highly competitive market-oriented economy. The new retail economy in many ways resembles the contemporary retail economy in the US. It is also exhibiting significant differences with Chinese characteristics but I think eventually it will move towards a different direction. Shanghai and the rest of China is currently suffering from some kind of “Brand Fatigue” as consumers are slowly becoming more sophisticated. The trust and prestige issues carry very different meaning here in China. We are still 5-10 years away from a more predictable consumer behavior and the market evolves.

The findings show that executives have very different perceptions of the struggles related to finding and aligning their people. In short, there is still a lack of common understanding despite its importance. Innovation is not in the core curriculum of MBA schools. Another interesting data point is 40% of top managers say that they do not have enough of the right kind of employees. Among respondents who do say enough people are available, however, nearly 50% say the right employees are in place, motivated, and protected by senior leadership, and only 22% say the organization’s culture inhibits them from making progress. The question that immediately comes to my mind when they say they do not have enough of the right kind of employees, I wonder if they have a definition of what are the “right” kinds of employees. That would be an interesting question to add to the survey.

I don’t think you will get answers such as “we need more senior executives with design thinking” or “we need more corporate misfits” etc. People who are trained in various disciplines of design are particularly good at using their instincts more than other individuals. Any innovation strategist must develop a keen interest in what works in marketplaces and what are the desirability factors as well as usability factors. Designers have an advantage and a key role to play in this innovation movement and that’s why I was saying MFA is the new MBA. The innovation field, per se, needs to use many different forms of design, crossover, jammed and integrated, to get beyond some threshold level of activity–enough to get commercially produced and, to be strategic. The great news for designers, about the rise of a corporate interest in innovation, is that it recognizes, more than ever before, the strategic contribution of “design thinking” to products, services, information, and corporate level business strategy. I think this as a long-term trend that will likely persist for at least another decade. I am not saying any designer should be given the decision making power for important business projects. I think we are talking about new capability. I don’t think we can simply put designers together with spreadsheet crawlers and expect innovation to happen.

Design thinking is not only about design. Design thinking is inherently an imagination management and prototyping process. Once you have the idea, you start to play with it. People ask me what is a “concept”, it is an idea that is ready for prototyping. The prototype is a visualization, working model, or even a small book or short film that describes a product, system, or service. Design thinking is about applying their mental models, languages and tools to complex business decision-making. I’d like to see practitioners, design schools, business schools and engineering schools coming together to create broad new cross-functional capabilities and professionalism that will actually meet the underlying need for objects, places, human-centered concepts, and distinctive experiences supported by sustainable business models that human beings crave–and enterprises must increasingly learn to deliver to thrive and prosper.

Original posted in Innovation Playground July 2007

I can’t sleep.

At moments like this, I find myself reminiscing about how we used to live; sleep, wake, sleep, wake. I’ve always been nostalgic, but I guess I’m still having a hard time adjusting even though I have implanted and installed a solid understanding of the change. Despite the inefficiencies that we resolved, a hint of conflict lingers inside me.

It’s amazing that it’s been almost 3 years since the UN-owned organization, formerly known as Google, achieved a global mandate to cross-compute the human genome with the archives of Wikipedia, TwitterBook, and other vast data sets. That’s nearly 40 years of details from more than 17 billion people and at least 2 billion animals, plants and other organic entities. We finally had the power at our fingertips, after years of intellectual prophesy. What would result from flipping the switch? Nobody knew. But we were open, and we were eager.

Our thoughts and actions were absorbed, scanned, processed and spat out. Every sentiment. Every inclination. Even the unconscious motivation behind each Tweet was deduced, exposed and analyzed. Pictures were scanned and facial expressions were recognized, judged, compared and contrasted. Most of human knowledge, behavior and emotion were digested into a digital process destined to produce unprecedented ramifications.

The result was shocking at first. Religious entities were unable to reconcile but their numbers were insignificant. It sounded, at first, like a joke. But the math added up.

Logic prevailed. It was not a question of “if” but rather “when”. It took a mere 3 days for the grid of Antarctic server farms to inform us of the recommendation, and only 6 more before it was implemented by the heads of states across the world. There was no sense in waiting. The result was indisputable despite natural reactionary protest. The leaders got together and quickly signed a document (as per the instruction of the machine).

With the exception of various health-related issues (mitigated by RNA interference and other related techniques), the transition occurred without significant social disruption. For more than a decade, cultures across the globe have grown accustomed to abiding by data-driven ideas and direction, and so there were few incidents of dissent. The promise of the changewas immense and irrefutable. Who were we to question the data?

There were, however, tremendous adjustments made in all economic markets. They were favourable, as predicted, but they were time-consuming and temporarily stressful nonetheless. Resources were reconfigured, re-optimized and redeployed. Agriculture was definitely hit the hardest, mainly in terms of logistical costs and re-planning. Overall, the computation ensured a relatively smooth conversion, equipped with instructions and support for all. It was quite an adjustment, but well worth it. That’s undeniable. It has been calculated. It has been done.

I can’t believe that it’s been 3 years. They have gone by well and fast for me, but I’m still experiencing occasional sleep issues. I know that this new system is right – because the data says so. It’s more efficient and beneficial for both the individual and the collective. General health-related issues have been contained and we’re adjusting well as a whole.

But alas, I lay here awake, in the 32nd hour of the day, 4 away from Newmidnight, in doubt.

Excerpt from AMR’s Journal,
Montreal, United Townships of Quebec,
Solember 12, 2038 – 32:14 SM.

Nota bene: This post is a follow-up to this post.

Progressive Change.

In a discussion about improvisational jazz, a teacher of mine once expressed, “the only constant thing in life is change,” paraphrasing the greek philosopher Heraclitus. That phrase remains meaningful to me fifteen years later, complementing my general fascination with progress.

I deeply enjoy progress. That may sound very vague, but it’s true. I enjoy learning and gaining new skills, whether it’s a new instrument or a programming language. I love progressive music (Tool, Yes, Dream Theater, etc.) and I pay for Progressive car insurance (just kidding – I’m with Belair Direct). I enjoy working towards Checkmate as much as I enjoy working through a Rubik’s Cube. I get excited by Darwin, Stephen Jay Gould and Bill Hicks’ rambling of “how we’re going to get to Mars.” I just love progress.

There is nobody more excited by progressive change as Ray Kurzweil. Like many others, when I first read Kurzweil’s The Singularity is Near in 2006, I felt a real exhilaration as if I had just cracked open the coolest fortune cookie of all time. Unite my consciousness with a supercomputer so I can exist throughout all eternity?? Sure, sign me up!

For those who are unfamiliar with Kurzweil’s Singularity, I strongly recommend delving into it. It’s worth checking out. Info on Ray can be found here, his book here, the upcoming movie here, and the supporting organization here. You may also be interested in TED videos here and here.

Exponential Growth.

Kurzweil observes that change is abound, and moving quickly in a particular direction. Vast and diverse occurrences of exponential growth transcend technological paradigms, perpetually driving us forward. Just in case you’re skeptical of such claims, here’s an excerpt from the book’s Wikipedia article, citing just some of the exponentially growing technologies:

• Dynamic RAM size (smallest feature sizes decreasing exponentially)
• Dynamic RAM price performance (improving exponentially)
• Average Transistor price (decreasing exponentially)
• Transistor Manufacturing costs (decreasing exponentially)
• Microprocessor clock speeds (increasing exponentially)
• Microprocessor costs (decreasing exponentially)
• Transistors per microprocessor (increasing exponentially)
• Processor performance (increasing exponentially)
• DNA sequencing costs per base pair (decreasing exponentially)
• Random Access Memory bits per dollar (increasing exponentially)
• Magnetic data storage bits per dollar (increasing exponentially)
• Wireless Internet and phone services price performance (increasing exponentially)
• Number of Internet hosts (increasing exponentially)
• Bytes of Internet traffic (increasing exponentially)
• Internet backbone bandwidth (increasing in a very terraced, quasi-exponential manner)
• Mechanical device sizes (decreasing exponentially)
• Number of scientific citations for nanotechnology research (increasing exponentially)
• Number of U.S. nanotech patents (increasing exponentially)

Growth, growth, growth. Now add a little more growth for good measure. Pun intended.

Our data pools are growing rapidly as well. I remember the excitement years ago when I upgraded my 386 laptop with 80 megabytes of disk space. Well, last night I caught myself cursing at my home computer for its pathetic 2.4 terabytes of space. (Note to self: buy more space.) Things have changed, clearly. We have oceans of digital assets at our fingertips and we constantly apply a myriad of operations upon them.

What really interests me, however, is not the fact that we have more of anything (or everything), but the idea that we can potentially do more with what we have. As any good statistician will tell you: more data is not better data. But more data when intelligently analyzed, probed, manipulated and mastered can be extraordinary data.

This brings me to the promise of the Petabyte Age. The petabyte is a unit of information or computer storage equal to one quadrillion bytes, or 1000 terabytes:

1 PB = 1,000,000,000,000,000 or 10¹⁵ bytes.

Translation: A lot of data. That’s about 250 trillion MP3 downloads from iTunes, 1.5 billion DivX Movies, or 100 billion 20 megapixel superfine photographs.

One year ago, Chris Anderson – the editor of Wired Magazine who is often (understandably) mistaken for the curator of the beloved TED conference – wrote an article called “The End of Theory” in his widely cherished magazine. He wrote of emerging opportunities and trends that will result from immense data compilations and subsequent manipulations. Here is a short excerpt from the article, where Anderson explains some fundamentals of this upcoming “Petabyte Age”:

The Petabyte Age is different because more is different. Kilobytes were stored on floppy disks. Megabytes were stored on hard disks. Terabytes were stored in disk arrays. Petabytes are stored in the cloud. As we moved along that progression, we went from the folder analogy to the file cabinet analogy to the library analogy to — well, at petabytes we ran out of organizational analogies.

At the petabyte scale, information is not a matter of simple three- and four-dimensional taxonomy and order but of dimensionally agnostic statistics. It calls for an entirely different approach, one that requires us to lose the tether of data as something that can be visualized in its totality. It forces us to view data mathematically first and establish a context for it later. For instance, Google conquered the advertising world with nothing more than applied mathematics. It didn’t pretend to know anything about the culture and conventions of advertising — it just assumed that better data, with better analytical tools, would win the day. And Google was right.

Google operates with a particular philosophy that it applies to virtually all of its activities: spare humans from the burden of tasks that machines are simply better equipped to accomplish. For example, it does not make sense for humans to maintain a dictionary for Google’s seemingly flawless “did you mean _____?” corrective search feature. Google uses pattern recognition to identify (with remarkable accuracy) typographical errors and likely intentions of users. Data knows best. Numbers don’t lie. This is a great example of how data – and intelligent manipulation of data – can drive useful solutions.

Lest we forget, questions precede answers.

Depending on data for answers makes an awful lot of sense when [a] there’s enough of it and [b] we’re equipped to extract meaning from it. Anderson suggests that we should also depend on data to derive the questions. This intrigues me deeply. As a business strategist, technologist and experience designer, I have tremendous respect for the process of asking the right questions. Idris is an exemplary role model of this practice. He often reminds me to not only leave the assumed answers at the door, but the questions as well. While fundamental, it is often overlooked and deserves to be emphasized.

Rather than trying to figure out how to sell more product, let’s re-examine if this product is really what people want. More interestingly, is it what people need? Rather than innovating upon an existing service, let’s make sure that the goals provide meaning and utility.

Pehaps the data-driven insights of the Petabyte Age will teach us that we are moving in the wrong direction on several fronts that we assume to be natural, safe and promising. Perhaps data-driven questions will produce answers that will provide real and lasting enlightenment.

Get ready for the revolution with an open mind.

There are a lot of ideas in this post (hence “Part I”). The topics mentioned are broad and complex, and there’s no way I can do justice to them through a series of blog posts. The links and notions presented here provide a decent starting point for those interested in pursuing these topics further. There’s no right way to end this post but to express the intrinsic purpose behind its composition.

My goal is to stimulate mere awareness and support for any enthusiasm surrounding these important ideas. As a champion of progress and someone who longs to witness the materialization of the petabyte-promised innovations of the future, I feel a duty to tickle the collective interest and generate some excitement for the opportunities on the not-so-distant horizon.

You can be sure that future posts will be more focused on specific implications of the Petabyte Age, tackling a broad spectrum of fields that include education, healthcare, art, consumerism and culture.

For now, enjoy some of the links provided above and keep an open mind for the progressive future that awaits us all.

As always, thanks for reading.

AMR

Continue here…

Anything Is Possible: Embracing the Petabyte Age, Part II

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