Seven and a Half Reasons to Be Optimistic About Tech in 2018


We’re now on the threshold of the 5G’s era. What can we  expect in the unfolding 2018? There are some cringeworthy moments about tech in the past year, however, looking forward, the whole society is very likely to witness faster and more achievements in more alluring entertainment, treatment tailored to cure disease and green energy exploited as the more realistic replacement. Last but not least, the revival of social conscience as the victims’ blog post blasts the sexual harrassment into public consciousness. All in all, a better life that deserves optimistic attitude.

A few weeks ago, my colleague Shira Ovide, a longtime tech reporter and columnist, said what many of us have been thinking: Silicon Valley sucks these days. “I’ve fallen out of love with technology,” Shira wrote, noting that this felt like the year when much of America began to seriously confront the downsides of the new economy. “The same qualities that made the internet so thrilling for a couple of decades—eliminating gatekeepers, making information instantaneous and connecting people with different points of view—now sometimes seem more threatening than alluring.”

The novelty of social media has given way to concerns about misinformation. Smartphone mania has become tougher to distinguish from outright addiction. Smart speakers are convenient, but could also double as scarily effective surveillance devices. The robots are going to take our jobs. Oh, and some of the guys responsible for these problems increasingly seem like a bunch of misogynistic creeps.

Yes, 2017 has been full of betrayals and unforced errors by people in the tech industry. A shocking number have revealed themselves to be even more greedy, petty, and narcissistic than common sense would suggest.

But some other stuff happened, too. I’m not saying it was a great year, but I am saying it wasn’t all awful. Here are some reasons not to go looking for a telegraph:

1. Faster Cellphones

These days it’s tough to rack up a $62,000 cellphone bill just because your nephew wants to watch Wall-E, but data fees and caps are still a prime consideration for lots of wireless customers. That should come to an end under the fifth-generation (5G) cellular standard, a set of improvements expected to make data transfer up to 100 times faster than it is today while dramatically increasing bandwidth. Once the system is that efficient, worrying about how much data you used in a given month will seem as silly as worrying about the cost of a long-distance phone call.

In November, Verizon said it’d bring 5G service to as many as five U.S. cities by the end of next year. T-Mobile promises nationwide 5G coverage by 2020. 5G may also serve as a credible alternative to local monopolies maintained by traditional internet service providers and cable companies, eventually adding an additional $3.2 trillion to the global economy and creating 22 million jobs worldwide by 2035. This should cheer you up if you’re depressed by last week’s net neutrality rollback.

2. Smarter Stuff

When it comes to 5G, faster phones are the least exciting part of the story. Right now, many developments in artificial intelligence tend to be stuck in the labs where the biggest, most powerful computers are located. Even self-driving cars have to carry trunks full of expensive electronic brains. Reliable 5G could allow enough of that computing power to be done remotely to make driverless cars safer and cheaper, and make internet-connected medical devices genuinely useful. Imagine, for instance, smart bandages that monitor the healing of a wound, alerting your doctor if it becomes infected, or internet-connected glucose monitors that use sophisticated machine learning algorithms to tailor treatment for diabetes patients. (There will be security concerns, of course.)

3. Bigger Batteries

Partly because phones keep getting more powerful, most still need recharging before the end of the day. Improved manufacturing processes, however, have made batteries cheaper and much more useful than they’ve ever been. Earlier this year, while blackouts were plaguing southern Australia, Tesla Chief Executive Officer Elon Musk boasted on Twitter that he would build a 100-megawatt battery facility in 100 days, “or it is free.” The Aussies took him up on it, and despite Musk’s tendency to set unrealistic goals, Tesla delivered the world’s biggest battery one day early. (This might count as two reasons: Elon Musk hit a deadline!)

There are other large-scale battery projects on the way, including an even bigger one Hyundai is building in South Korea, scheduled to open in February. The speed with which these facilities are being built suggests that wind and solar power are a more realistic replacement for fossil fuels than most people realize, as long as Tesla and others are able to work out manufacturing kinks.

4. A New Space Race

Musk’s other company, SpaceX, hit a big milestone Friday. For the first time, it sent a reused spaceship to the International Space Station on top of a reused rocket, which in the long run could mean dramatically reduced launch cost. SpaceX’s next-generation rocket, Falcon Heavy, could fly as early as January. Meanwhile, Planet Labs is democratizing satellites, Rocket Lab is trying to further slash launch costs, and Jeff Bezos is doing what Jeff Bezos does best on behalf of his rocket company, Blue Origin.

5. Cheaper Stuff

Economies of scale are an underappreciated side effect of Bezos’ growing wealth and power. Recently, New York Times columnist Farhad Manjoo described how the online retailer—which just so happens to be trying to jump into pretty much every other industry and increasingly looks like a target for antitrust regulators—had enabled no-name startups to undercut the big electronics companies. Wyze Labs, for instance, makes an internet-connected video camera and sells it for $26, including shipping; a similar product sold by Alphabet’s Nest division costs $200.

As Manjoo wrote, Amazon has essentially superseded the typical value of product brands (building trust, setting up a sales infrastructure, marketing). Customers who don’t go to stores and buy based on Amazon reviews essentially get to keep the money brands once invested in those things. That’s sad for Nest, I suppose, but it’s arguably pretty great for cash-strapped parents who can get an internet-connected video camera for the same price as a traditional baby monitor.

6. Bitcoin!

You can’t use bitcoin on Amazon, or for much of anything at the moment besides speculation. But that’s only half the story.
For a second, let’s forget the crazy runup, ignore the bitcoin lottery winners, and just marvel that bitcoin mania happened in the first place. At a time when a handful of giant companies and their billionaire founders control the technology landscape, a group of misfits led by a creator nobody knows managed to popularize a technology that may fundamentally change how Wall Street moves money around, how we vote, and how we organize ourselves. Bitcoin could turn out to be a total bust in every way, but the fact that it happened shows the internet is still capable of producing things that are genuinely new.

7. New-New Media

Outside of patent lawsuits, the big tech companies often act like rent-seekers in the media business, where Google and Facebook swallow most of the new digital ad money and wield that power poorly. Squint hard enough, though, and you’ll see some reasons for optimism. While Snap Inc. has performed poorly as a public company, Snapchat has done an admirable job of keeping free of fake news. Another bright spot: Patreon, which combines aspects of Kickstarter and the NPR pledge drive to help support tens of thousands of podcasters, filmmakers, and other artists. And then there’s the hot startup of the moment, HQ Trivia, an interactive game show that you can play on your iPhone. It’s not world-changing stuff, but it’s entertainment that feels genuinely novel without sucking up huge amounts of time.​​​​​​

7½. Tech Gets a Social Conscience, Maybe

As cringeworthy and depressing as the stories about sexism in Silicon Valley have been, it’s possible to see the outrage they’ve provoked as a sort of turning point for an industry that finally seems to be getting serious about its place in the world. Susan Fowler’s blog post about sexual harassment at Uber drove investors and the press to confront the company’s moral failures, helping to pave the way for the flood of revelations about men in other industries. And while Facebook has never looked worse than it does today, Mark Zuckerberg is showing signs of the humility that his company, and the broader industry, desperately need.

It may not be much, but it is something. Here’s to a happier 2018.

By Max Chafkin

Digital Operation Digital Supply Chain Highlights

Complexity In The Digital Supply Chain


Audience around world have been expecting better online experience for game, music and movies. Netflix, the world’s leading Internet entertainment network with over 100 million members in over 190 countries believes that to realize the construction of real digital supply chain entails 2 parts: to ensure the materials quality and to manage B2B order and catalog in a more efficient way. To make this happen, we need shared industry standards to help with delivery tracking and catalog curation.

Netflix launched in Denmark, Norway, Sweden, and Finland on Oct. 15th. I just returned from a trip to Europe to review the content deliveries with European studios that prepared content for this launch.

This trip reinforced for me that today’s Digital Supply Chain for the streaming video industry is awash in accidental complexity. Fortunately the incentives to fix the supply chain are beginning to emerge. Netflix needs to innovate on the supply chain so that we can effectively increase licensing spending to create an outstanding member experience. The content owning studios need to innovate on the supply chain so that they can develop an effective, permanent, and growing sales channel for digital distribution customers like Netflix. Finally, post production houses have a fantastic opportunity to pivot their businesses to eliminate this complexity for their content owning customers.

Everyone loves Star Trek because it paints a picture of a future that many of us see as fantastic and hopefully inevitable. Warp factor 5 space travel, beamed transport over global distances, and automated food replicators all bring simplicity to the mundane aspects of living and free up the characters to pursue existence on a higher plane of intellectual pursuits and exploration.

The equivalent of Star Trek for the Digital Supply Chain is an online experience for content buyers where they browse available studio content catalogs and make selections for content to license on behalf of their consumers. Once an ‘order’ is completed on this system, the materials (video, audio, timed text, artwork, meta-data) flow into retailers systems automatically and out to customers in a short and predictable amount of time, 99% of the time. Eliminating today’s supply chain complexity will allow all of us to focus on continuing to innovate with production teams to bring amazing new experiences like 3D, 4K video, and many innovations not yet invented to our customer’s homes.

We are nowhere close to this supply chain today but there are no fundamental technology barriers to building it. What I am describing is largely what has been for consumers since 2007, when Netflix began streaming. If Netflix can build this experience for our customers, then conceivably the industry can collaborate to build the same thing for the supply chain. Given the level of cooperation needed, I predict it will take five to ten years to gain a shared set of motivations, standards, and engineering work to make this happen. Netflix, especially our Digital Supply Chain team, will be heavily involved due to our early scale in digital distribution.
To realize the construction of the Starship Enterprise, we need to innovate on two distinct but complementary tracks. They are:

1. Materials quality:

Video, audio, text, artwork, and descriptive meta data for all of the needed spoken languages

2. B2B order and catalog management:

Global online systems to track content orders and to curate content catalogs

Materials Quality

Netflix invested heavily in 2012 in making it easier to deliver high quality video, audio, text, art work, and meta data to Netflix. We expanded our accepted video formats to include the de facto industry standard of Apple Pro Res. We built a new team, Content Partner Operations, to engage content owners and post production houses and mentor their efforts to prepare content for Netflix.

The Content Partner Operations team also began to engage video and audio technology partners to include support for the file formats called out by the Netflix Delivery Specification in the equipment they provide to the industry to prepare and QC digital content. Throughout 2013 you will see the Netflix Delivery Specification supported by a growing list of those equipment manufacturers. Additionally the Content Partner Operations team will establish a certification process for post production houses ability to prepare content for Netflix.

Content owners that are new to Netflix delivery will be able to turn any one of many post production houses certified to deliver to Netflix from all of our regions around the world. Content owners ability to prepare content for Netflix varies considerably. Those content owners who perform the best are those who understand the lineage of all of the files they send to Netflix. Let me illustrate this ‘lineage’ reference with an example.

There is a movie available for Netflix streaming that was so magnificently filmed, it won an Oscar for Cinematography. It was filmed widescreen in a 2.20:1 aspect ratio but it was available for streaming on Netflix in a modified 4:3 aspect ratio. How can this happen? I attribute this poor customer experience to an industry wide epidemic of ‘versionitis’. After this film was produced, it was released in many formats. It was released in theaters, mastered for Blu-ray, formatted for airplane in flight viewing and formatted for the 4×3 televisions that prevailed in the era of this film. The creation of many versions of the film makes perfect sense but versioning becomes versionitis when retailers like Netflix neglect to clearly specify which version they want and when content owners don’t have a good handle on which versions they have. The first delivery made to Netflix of this film must have been derived from the 4×3 broadcast television cut. Netflix QC initially missed this problem and we put this version up for our streaming customers. We eventually realized our error and issued a re-delivery request from the content owner to receive this film in the original aspect ratio that the filmmakers intended for viewing the film. Versionitis from the initial delivery resulted in a poor customer experience and then Netflix and the content owner incurred new and unplanned spending to execute new deliveries to fix the customer experience.

Our recent trip to Europe revealed that the common theme of those studios that struggled with delivery was versionitis. They were not sure which cut of video to deliver or if those cuts of video were aligned with language subtitle files for the content. The studios that performed the best have a well established digital archive that avoids versionitis. They know the lineage of all of their video sources and those video files’ alignment with their correlated subtitle files.

There is a link between content owner revenue and content owner delivery skill. Frequently Netflix finds itself looking for opportunities to grow its streaming catalogs quickly with budget dollars that have not yet been allocated. Increasingly the Netflix deal teams are considering the effectiveness of a content owner’s delivery abilities when making those spending decisions. Simply put, content owners who can deliver quickly and without error are getting more licensing revenue from Netflix than those content owners suffering from versionitis and the resulting delivery problems.

B2B Order and Catalog Management

Today Netflix has a set of tools for managing content orders and curating our content catalogs. These tools are internal to our business and we currently engage the industry for delivery tracking through phone calls and emails containing spreadsheets of content data.

We can do a lot better than to engage the industry with spreadsheets attached to email. We will rectify this in the first half of 2013 with the release of the initial versions of our Content Partner Portal. The universal reaction to reviewing our Nordic launch with content owners was that we were showing them great data (timeliness, error rates, etc) about their deliveries but that they need to see such data much more frequently. The Content Partner Portal will allow all of these metrics to be shared in real time with content owner operations teams while the deliveries are happening. We also foresee that the Content Partner Portal will be used by the Netflix deal team to objectively assess the delivery performance of content owners when planning additional spending.

We also see a role for shared industry standards to help with delivery tracking and catalog curation. The EIDR initiative, for identifying content and versions of content, offers the potential for alignment across companies in the Digital Supply Chain. We are building the ability to label titles with EIDR into our new Content Partner Portal.

Final Thoughts

Today’s supply chain is messy and not well suited to help companies in our industry to fully embrace the rapidly growing channel of internet streaming. We are a long way from the Starship Enterprise equivalent of the Digital Supply Chain but the growing global consumer demand for internet streaming clearly provides the incentive to invest together in modernizing the supply chain.

By Netflix Technology Blog

Source: (abridged) [/vc_column_text][/vc_column][/vc_row]

Digital Strategy Digital Techonolgy Highlights

4 Examples of How AR & VR Will Improve Customer Service


What comes to your mind when you hear VR & AR, apart from dizzying delight from the games like Pokemon GO and exciting sci-fi movies? Have you ever thought about customer service? A consistent focal point for businesses is how we interact with our customers. Do they enjoy our customer service? The following passage expands on the usage of AR and VR by illustrating 4 examples concerning restaurants and in-person shopping etc.

It takes 11 minutes to read.

Great customer service is still alive and well in many businesses, but others are seeing more red-flag comments and lowered scores. With the internet at our fingertips at every moment, there’s no hiding a bad experience, so any and all are quickly there for us to post for all to see.

In a world where fears abound surrounding whether virtual reality will have us hunkered up in dark rooms attached to machines straight out of Bruce Willis’s Surrogates — unlikely to see another physical being for weeks at a time — could that same technology actually help or save declining customer service?

Why yes, I think it can.

Where We Currently See Breakdowns in Customer Service

We can all see where voids can happen, causing actual or perceived bad customer service. In fact, you may have already thought of one that happened recently. The lists are endless, but there’s a handful of common complaints plastered on review sites for both online and in-person consumer goods.

Customer service is always a human-to-human interaction in which we want and demand a personal touch, empathy, and help. Where we currently lack the technical abilities to provide such experiences, often across distance, further technological advances in AR and VR can and should be used to provide solutions allowing for better consumer experiences.

Flash forward to a super random date in time, say 2042. (I, personally, hope some of this technology doesn’t take that long, but 42 is always a good answer. For those of you who don’t know why, might I suggest some “light” reading surrounding the topics of interstellar highways, dolphins, and sad robots?)

Anyway, we’re in 2042. We’re still walking around as humans, interacting with each other in a physical world, and we’re consuming products in much the same way we do today.

1. The Dreaded Call Center

Hours of mind-melting hold music, fourteen different numbers to push in the hope of finding the appropriate department, and a bad connection that makes clear communication difficult all plague this consumer torment.

Imagine for a moment, though, that you are instead enlisting an AR device during what is normally a frustrating conversation.

Do you remember when you ordered that amazingly chic, Pinterest-esque cascading lawn fountain? You couldn’t have been more excited for it to arrive, but when it did, you discovered the company accidentally shipped a twelve-foot tall, fully-lit pink flamingo (who even orders something like that?).

On your call to customer service, a normal conversation can range from anything to, “we show we shipped you the fountain, so I can’t do anything since that’s what I show you have,” to “since it’s an item over ‘X’ value, we would need you to ship it back to us at your expense,” or “we’ve never had anyone order something like that.”

Instead, wouldn’t it be easier for both parties to use an AR enabled device, allowing the customer service representative to appear in your space. Now, as you can both see each other, the interaction is much more human. You see him, making him a human you’re less likely to scream at, and he sees you, making you more than just another voice in a long line of complaints.

From there, you walk out to your lawn where your neighbors have gathered to sign a petition in order for the flamingo to be removed, and the representative can see the error.

Now, not only do you have a more human interaction, encouraging compassion on both sides, you’re able to base the remainder of the conversation on information you both share. Whereas the agent previously only had paperwork in which to gauge a proper response, he now has proof and is more likely to come to a swift solution.

2. The Contractor

You’ve done your research and asked for Facebook recommendations, but you still feel apprehensive about hiring someone you’ve never met to do work on your house.

Handymen and contractors are often seen under the guise of swindlers — taking longer than they should and causing themselves extra work to gain extra pay. While many deserve the good reputations they carve for themselves, trust is earned at a personal level.

In this instance, you’ve requested a kitchen remodel, which will require the group to work in your home while you’re away at the office. On just the first, day, you’ve gotten three calls. One stated they didn’t bring the right equipment, so they’d be back at a different time. Another call indicated the work was more intensive than they’d expected — they need to remove a weight-bearing beam — so charges will increase. The third indicates they’ll be changing the layout from what was discussed due to the beam removal.

The team lead tries to describe how it will look, but you’re having a hard time envisioning it. They’d shown drawings to start, but now that those are void, you feel the need to see a new visual in order to agree to the work.

When you finally arrive home, you see your kitchen is in utter disarray, but you can’t make sense out of what kind of progress they did or didn’t make during the day.

When we bring future AR/VR capabilities into the mix, we are able to re-add confidence and trust.
Now, if you wonder what the team of contractors does while you’re away, you simply trigger your AR or VR device. By way of AR, you can view a miniature, 3-D, realtime stream of your kitchen. VR would allow for the same, but in a different way (i.e. via a headset or by viewing a 360 video remotely).

You may be asking why we don’t just use cameras for this now, but remember that just because we have that capability doesn’t make it as useful. One nanny cam in your home doesn’t show the whole picture, and such cameras are easily moved.

At this point, when you get the call from the lead about the beam removal and the subsequent the design changes, you’re also provided with visuals. 3-D models show why the beam must be removed and indicate the extra work involved to shore up the rest of the home.

By way of VR, you can be transported into the newly-designed kitchen, and you are able to make educated decisions as to how you want to proceed.

Naturally, there is a certain amount of time necessary to create these modeled visuals, but when you cannot personally supervise work, the extra time spent putting everyone on the same page is worth the effort for both parties.

3. The Crowded Restaurant

We’ve all been there — the crowded restaurant where the person who fills your water is different from the one who takes your order, and another, still, brings your food. You flag down a server at the next table to indicate you’d like another beverage or to state your food is cold and incorrect, but you’re informed it’s not his/her table.

Often, especially in popular, crowded restaurants, efficiency is a key driver in how operations are run. However, when you are unable to make a personal connection with the person providing service, or indeed are unable to determine which of the many faces are at your disposal, a perceived lack of acceptable customer service can form.

While we cannot fix every challenge within the restaurant industry, augmented reality can be a useful tool in creating an environment in which we feel as though our concerns and care are of top priority.

Imagine for a moment that you’re in Bernadette’s Lettuce Bistro (it’s all the rage in the 2042, and yes, they only serve lettuce). While you may still have the different types of servers attending to your table (water-filler, order-taker, food-bringer), you have another unseen attendant in the back.

In a dedicated corner, out of sight from the public, there is an AR display showing the entire restaurant. It shows the tables, patrons, staff movements, etc.

In between the time the “food-bringer” delivers the food to your table and the when the “order-taker” comes back to check on things, this unsung hero in the back noticed a few things regarding your table.

·Your beverage glass is nearly empty.

·You took a bite of lettuce, made a face, and then looked around for something.

·You’ve put your utensils down and are no longer eating.

In a normal restaurant scenario, you may wait five or more minutes before getting ahold of a server willing to claim your table as his/hers. Five minutes may not seem like a lot of time in the grand scheme of things, but in customer service, that is five minutes for someone to seethe at an increasing rate. Five minutes is enough to make a final decision on the quality of an establishment. It’s plenty of time to build up enough anger to then project onto the awaiting staff, and it’s more than enough time to pull out a mobile device for an online review or scathing social media post.

Instead, Bernadette’s dedicated AR staffer sees these actions as key indicators that your table needs immediate attention. Now, as a server approaches your table, prior to even speaking with you, your concerns are addressed. You’re asked if you’d like another beverage and what can be done to make the lettuce more to your liking.

4. In-Person Shopping

You walk into your local computer store, let’s call it Larry’s Computational Emporium. There, you look at computers for roughly thirty minutes, trying to figure out why one is $1,000 more than another. You’re not a computer engineer, after all. You’d have bought something online if you could, but you’d hoped to speak to a clerk for assistance in making the right decision for your needs.

After thirty minutes, you hike around the Emporium’s aisles, desperately trying to find help. You finally locate eight employees having a Blow-Pop meeting near the tech-enhanced refrigerators (they monitor your weight and eating habits — chastising comments are optional). When you ask for help, you get a round of blank stares followed by a couple eye rolls and the very distinct impression that you are thoroughly bothering these people by asking them to “do their job.”

After fifteen minutes of hearing technical terms and acronyms referring to things outside the realm of your expertise, feeling as though you’re being talked down to by a person ten to fifteen years your junior, you make a slightly-educated decision on a computer.

Instead, let’s head back to Larry’s Computational Emporium with AR/VR. We walk in, and we patrol the computer displays for a few minutes. A moment or two later, we’re approached by a young human asking if assistance is needed. There was still, in fact, a Blow-Pop meeting near the refrigerators, but a wrist device buzzed on one human’s wrist indicating someone was in the computer aisles. (No, that’s not AR or VR, but all sorts of other tech is advancing, as well.)

This human still speaks in technical terms and acronyms, but thankfully you’ve downloaded the Larry’s Computational Emporium AR App, and that translates the jargon in a way that makes sense to you. You’ve already selected your expertise level, so when the associate says RAM, your AR device plops an overlay on the scene with, “it’ll make the computer do things faster.”

It’s easy for someone to say we should just train associates to speak in ways more accepted by the public. The inherent problem, however, is that every member of the public has a different level and understanding when it comes to any subject. One individual may walk in knowing about RAM but needs to know more about graphics cards while the next is buying his/her very first computer. Expecting an hourly associate to immediately and accurately assess a shopper’s existing subject knowledge is impractical and unproductive.

We can use our understanding of these shortcomings to improve customer service in other ways. When we empower the consumer with ways to customize the experience, we are creating situations where the experience is fulfilling, helpful, and efficient for all parties involved.

We See Customer Service in Our Every Day Lives

This will not change as time saunters onward. As advancements in the augmented and virtual reality spaces further enable better experiences across a multitude of platforms, we will better serve our future selves if we remember this technology can also enhance human-to-human interactions.

By Scottie Gardonio, creative manager.


Digital Techonolgy Highlights

Why Elon Musk is Right About AI Regulation


Though AI technology is still in its infancy, its double exponential in development could be the potential hazard putting the fate of all human beings at risk, as most expert observers fail to predict AlphaGo’s winning over the top human players. Elon Musk, calls for “proactive regulation” to be put in place now or in the immediate future because we can know from the history that governments and regulation always move at a slow pace while the technology is gaining momentum. The following passage offers in sight into such an apprehension.

It takes you 7 minutes to read.

I am not surprised that almost everyone who works in AI (specifically Deep Learning) has refuted Elon Musk’s suggestion that government needs to begin regulating AI. The key conversation at the moment is Mark Zuckenberg’s remark that Musk’s assertion was ‘pretty irresponsible’ and Elon Musk’s response that Zuckenberg’s understanding was ‘limited’.

Many professional researchers don’t have a limited understanding of Deep Learning and very few of them have chimed in support of Elon Musk.

Elon Musk is not only a radical thinker, he is also a very disciplined one. There have been plenty of naysayers regarding his ventures like SpaceX and Tesla. However, he has remarkably proven the skeptics wrong and executed in a manner that almost nobody else in this world can replicate. His ventures builds the most complex of machinery in a way that is not only technologically feasible but also economically feasible. Therefore on accomplishments alone, should at least give Musk the benefit of the doubt on this one.

I am writing this blog entry so that I can explore in depth Elon Musk’s reasoning. Musk holds an opinion that is clearly in the extreme minority.

What did Musk actually assert? Here is what he has clarified in a fireside chat after his remark’s during the governor’s meeting:

Click to play Elon Musk’s interview.

Musk clarified that he envisions a government agency forming first and seeking to gain insight into AI and its use initially, without any kind of attempt to regulate by “shooting from the hip.”

The primary objection of anyone knowledgeable about this field is that there is nothing specific that requires regulation (One idea is an automation must never falsely pose as a being human). The field is still in its infancy (despite mastering Go and mastering arcade games from scratch) and the closest thing that we have to ethical rules are the “Asilomar AI Principles.” However, these principles are abstract and in a form that is not concrete enough to define laws and regulation around.

Musk’s fear however is reflected in his statement: “It’s going to be a real big deal, and it’s going to come on like a tidal wave.” Musk speaks about a ‘double exponential’ in the acceleration in hardware and the acceleration of AI talent (note: NIPS 2017 had over 3,500 papers submitted). This ‘double exponential’ means that our predictions of its growth may be too conservative. Musk further remarks that researchers can get so engrossed in their work and overlook the ramifications. Musk’s fundamental stance is that more effort should be placed on AI safety over pursuing AI advances. He argues that if it takes a bit longer to develop AI then this would be the right trail.

What we know about governments and regulation is that they move in a very slow pace. Musk is proactively kickstarting the conversation about government regulation with the calculation that when government eventually becomes ready that AI technology will have advanced enough to allow for meaningful regulation. It indeed is placing the cart before the horse.

Most experts will agree that it is pre-mature to bring up AI regulation. However government, society and culture move at rates that are much slower than technology progress. Musk’s gamble here is that the negative effects of pre-mature regulation outweighs an existential threat. Musk calculates that it is better to be early but wrong than to be late and correct.

The previous American administration had published a report on AI last year. However, the anti-science leanings of the current administration may put a damper on any future government subsidized studies on the effects of AI to society. US Treasury Secretary Steven Mnuchin evenly opined that the threat of job loss due to AI is “not even on our radar screen”, only to walk back his statements a few months later. In short, despite Musk’s statements, it is very unlikely that the current administration will make an effort in this area and would prefer to have ‘market forces’ decide the solution.

Musk sounding the alarm will likely fall into deaf ears for the next four years. Perhaps that is why he brought it up in the Governor’s meeting and like initiatives like climate-action this threat may be taken up by US states instead. Unfortunately, Mark Zuckenberg’s remarks and many of the other researchers objections only gives additional ammunition to other governments to do nothing.

Unfortunately, the examples that Musk gave in the Governor’s meeting to motivate regulation were examples of threats dues to cybersecurity and disinformation and are not necessarily a threat that only AI can perform. (on thinking about this, Musk may have deliberately chosen to avoid a use case that gives malicious actors ideas!) Musk’s best analogy that does make sense is the idea of it being easier to create nuclear energy as compared to containing it.

We are indeed heading into dangerous times in the next four years. It is difficult to imagine what Deep Learning systems will be capable of by then. However, it is likely that Artificial General Intelligence (AGI) will not been achieved. However something very sophisticated in the realm of narrow AI may be developed. More specifically weaponized AI in the domain of disinformation and cyber-warfare. The short term threats are job destruction and cyber-warfare. These are clear and present dangers that will not require the development of AGI.

Toby Walsh of University of South Wales however has a different take:

“We are witnessing an AI race between the big tech giants, investing billions of dollars in this winner takes all contest. Many other industries have seen government step in to prevent monopolies behaving poorly. I’ve said this in a talk recently, but I’ll repeat it again: If some of the giants like Google and Facebook aren’t broken up in twenty years time, I’ll be immensely worried for the future of our society.”

Rachel Thomas of Fast.AI has writes about similar concerns:

“It is hard for me to empathize with Musk’s fixation on evil super-intelligent AGI killer robots in a very distant future. (snip) … but is it really the best use of resources to throw $1 billion at reinforcement learning without any similar investments into addressing mass unemployment and wealth inequality (both of which are well-documented to cause political instability)”

Both opinions revolve about inequality. AI ownership has being confined to a few elite companies. Musk was concerned enough about this that he formed OpenAI. However, it brings up a concrete regulatory issue. Should AI be owned by a few private companies or should it be a public good? If it indeed is a public good, then how shall that be protected?

We coincidentally are exploring a few of these ideas in our Intuition Fabric project.

Update: I believe Musk is aware of A.I. technology that already exists today that can be extremely disruptive and requires serious discussion in regulating. It definitely is an application of Deep Learning, but he has deliberately not been specific to what it is. Suffice it to say that it is in the realm of network intrusion and disinformation.

By Carlos E. Perez


Digital Strategy Highlights

Bridging The Retail/Digital Divide In Customer Experience Marketing


As their market share is challenged by dedicated ecommerce sites, retailers are adopting several digital strategies that enable them to compete in the new omnichannel competitive space. Traditional retail must keep abreast with the developing technology that changes people’s life, including their customers. The following passage talks about challenges and opportunities, like how the impulse buys derived from the satisfaction of immediate acquisition could be transferred through better customer experience marketing.

It takes you 7 minutes to read.

Ecommerce is Conquering Retail

Observers have called the fight between ecommerce and traditional retail in favor of the internet giants. Amazon, eBay, and thousands of new ecommerce sites have broken down and conquered the profits of household names like Macy’s and Old Navy, and even beaten down monolithic retail powerhouse Walmart. Most of these brick-and-mortar stores have begun competing directly via ecommerce sites of their own, as retail companies such as Gap experience massive losses everywhere outside of their online platforms.

Challenges in Reconciling Retail and Ecommerce Strategies

Despite the stratospheric rise of ecommerce sites, from smaller, less sophisticated niches to vast marketplaces with 100M-plus user bases, there is ample room for innovation within the fundamental online shopping experience. Interestingly, while many of the customer experiences and strategies that have proven so effective for traditional retailers may not be effectively transitioned to modern ecommerce marketing, the application of enterprise analytics to retailers’ online presences might allow these older institutions to leverage their long-standing knowledge to innovate in the digital space.

Retail is being called upon to provide a synthesis of the best strategies of ecommerce, that builds on – and ultimately, with the aid of a data driven methodology, delivers – the trusted, established and comforting presence of the physical experience on which their brand was founded. Just as physical stores lay the groundwork for a consistent, satisfying customer experience, strategic analysis of data is how that same foundation is built digitally.

Data Is the Difference

Keeping pace with the upward trend of online sales requires retailers to gain a new level of insight into customer behaviors, shopping patterns, and product-level performance. Google’s Enhanced Ecommerce in the Google Analytics 360 Suite is a premier example of how a robust, systemic approach to incorporating data improves the online customer experience and turns mere visitors into purchasers. The site’s online journey is tracked through conversion rates, product metadata, user segments, and a complete analysis of the shopping funnel lifecycle, providing insights into pre-purchasing behavior and how products perform and convert digitally. Through these efforts, additional recommendations and other features such as promotions, product lists, and user segmentation to optimize customer experience and improve conversion rates can be had. The success stories of Analytics 360 and other data driven methods demonstrates how critical it is to leverage these data driven customer experience strategies.

Retail Dcommerce: Challenges When Enhancing Customer Experience In the Retail Space

In addressing customer experience gaps in ecommerce omnichannel marketing, retail companies must take a balanced approach that judiciously weighs a variety of insights and considerations of several questions that seasoned ecommerce players are well-accustomed to asking.

Finding Lost Carts

A central phenomenon that demands explanation is abandoned carts. 65-70% of carts are abandoned at some point during the purchase process, and this leads to a direct loss in revenue. Data analysis looks into funnel reports to pick apart sessions that resulted in abandoned carts, finds salvageable abandoned products, and chases those customers, whether it be through discounts, free shipping, follow-up emails, or other methods. Addressing the myriad ways in which carts can be lost on the way to checkout – it could be as simple as a hardware failure on the consumer’s end – is a straight gain on an already-undertaken customer journey.

Social and Ecommerce

Social networks are a dominant, instantaneous portal between consumer and retailer, linked to 18% of online purchases. A commitment to socially driven purchasing demands a balanced approach that keeps watch on the elusive, and sometimes misrepresented, social ROI. Analysis of keywords and other data that flows back from social likewise informs relevant content and messages, guides alignment with affiliated advertising.

True “One-click” Purchases

Proprietary devices build on the physical foundation of retail, giving incentives to effortlessly continue or branch out from in-store purchases. Amazon has innovated the Dash, a small, Wi-Fi-connected, branded IoT device with a push-button that orders the product to which the device is specifically branded. By linking a specific repurchase to this device, the user is untethered from the weight of the purchase process while in their own home. Walmart’s take on this concept intends to be smaller and less obtrusive, angling for more pervasive domestic use. The device would simply track item usage, and then place an order when supplies reach a low point placed by the consumer, effectively taking autonomous choice out of the equation. By providing a physical interface that directly affects online purchases, retailers could, from within their customers’ homes, utilize a tool that makes customer experience seamless – that, essentially, makes impulse reality.

Impulse Buys

Spontaneous purchases are a hallmark of retail that is not easily replicated in the digital space. 30-50% of physical retail sales are impulse purchases, so the advantage of moving every manifestation of the impulse buy into digital marketplaces would be obvious for retailers. But how would the satisfaction of immediate acquisition be effectively transferred into the digital space?

An innovative company might be able to exploit this gap by developing and mapping a clever customer journey that takes a unique approach to ‘digital aisles’. Possible examples could be the following:

 ★ Augmented Reality and Virtual Reality have the ability to virtually generate these digital aisles, putting stacks of on-sale products in the customer’s field of vision, even if they are only browsing on their smartphone.

 ★ Better or unique UX design on search pages could allow for customers to be engaged by other products without disrupting their original search criteria.

 ★ A new style of ecommerce store could be created, one which does not simply attempt to replicate the classic Amazon search, filter and display related — but instead replicates the journey of successful big box stores, while removing the irritation, inconvenience and high overheads that initially drove customers away.

Maintaining the Lead

It can be particularly difficult to innovate in a cluttered area like ecommerce, especially in a segment with a set of existing ‘best practices’, but room for this sort of innovation could be baked into a company’s digital strategy, because the rewards for success are potentially enormous. To stabilize and maintain primacy in the age of ecommerce, traditional retailers must invest in and diversify their ecommerce positions in the competitive space. These retailers should look to synthesize modern approaches that leverage data with the select physical experiences that consumers enjoyed from their retail stores. Retail is a few millennia ahead of ecommerce, and by leveraging the insights that ecommerce has ushered into the game, it can stay there.

By Jared Stevenson


Digital Transformation Highlights

5 Ways To Use Microlearning For Informal Learning


Formal learning programs are synonymous with full-scale eLearning courses, instructor-led trainings, strong Instructional Design strategies and an extensive curriculum, all mapped in a very structured way. However, carefully constructed courses are not the only way learners can acquire skills and knowledge. Research shows that over 80% of employees learn their job from informal learning. Informal learning pulls learners toward knowledge and content,rather than pushing content onto them. As this approach is free from the bounds of classrooms, schedules, and computers, it allows employees to be spontaneous in their learning. So, can we use microlearning for informal learning?

It takes you 4 minutes to read.

Taking cues from the way informal learning takes place, we can create complimentary resources for employees who can access knowledge just the way they do (at the time of need), but will have a dedicated place on the Learning Management System or Intranet Portal from where they can access information. These complimentary resources can be in the form of microlearning modules. Microlearning can be very efficiently used to create learning content that promotes informal learning in the organization.

Microlearning is a strategy that delivers small bits of information, effectively. Today’s millennial employees don’t have the time to take a course that will shelve off hours of productivity from their day. The founding principles of an informal approach are so similar to microlearning that they can be viewed as a match made in heaven. Check out how microlearning adds to the informal learning experience of employees in organizations:

1. Multi-device Accessibility

Today’s millennial employees are constantly on multiple devices and they use all of them for different purposes. It seems but natural that their training should follow suit. Microlearning courses are designed in a way that makes them equally impactful on devices of all screen sizes and functionalities. By giving learners a seamless experience across all their devices, it makes sure that there is no disruption in the learning process. As there is no certainty as to where, and on what device, informal training might be taken, the multi-device accessibility of microlearning perfectly fits its bill.

2. Just-In-Time Training

Informal learning happens spontaneously, at the time of need. Microlearning, thanks to its format, can be used effectively to double up as an instant source of knowledge. It deters from flooding users with information at the wrong time. Rather, it aims to pull the user toward the training by giving them the right information at the right time. Microlearning as it turns out, is perfect to deliver just-in-time trainings. These trainings are supposed to be short, quick and impactful, enabling users to achieve an immediate goal. Like informal learning, microlearning gives great on-the-job context to help employees apply what they learn. The context creates an immediate change in behavior and skill, which is ultimately the goal of both these methodologies.

3. Personalized Learning Styles

Each of us has our own preferences when it comes to learning. I might prefer to go online and see a video to gain knowledge on a subject whereas you might prefer to quickly go through a PDF document or a podcast on the same subject. The driving factor of the microlearning approach is that it can be flexible according to the preferences of various users. Microlearning can adequately fulfill this need for personalization, as it takes a course or module and deconstructs it to form the building blocks for the micro-course. Different teaching techniques can be applied to each of the blocks to create a bucket of courses that has something for everyone.

4. Rich Multimedia

We keep hearing instances where people have built things, repaired appliances, and gained new knowledge, just by watching educational videos on the Internet. The use of graphical elements, images, and animations often makes the content engaging and learner-friendly. All these resources are examples of microlearning modules, albeit this is ‘informal’ and open to the public at large. But, we can use the same concept in training. Multimedia elements keep learners thoroughly invested in the training and also increase knowledge retention and recollection.

5. Fewer Distractions

Informal learning intertwines around a learner’s schedule. When does informal learning take place? Usually, when there is a need. In the context of work, employees seek knowledge when they are faced with a problem or issue, and want to fix it. It is not taking employees away from work but is actually helping them work. Microlearning offers the same option, but in a more structured way. Instead of leaving it to the employees to figure out where to find information, employees can access the bunch of resources on the LMS or Internet Portal whenever they need to resolve an issue or are looking for quick information or guidance. It does not involve elaborate preparations in terms of planning to take time off work, therefore it causes minimal disruption to work. If at all, these resources only complement employees’ job responsibilities.

By understanding how informal learning takes place, you can create strong microlearning modules so that learners get an appropriate informal learning experience. Utilize microlearning to create powerful corporate training that can really drive up your profitability.

By Ayesha Habeeb Omer


Digital Operation Digital Supply Chain Digital Techonolgy Highlights Internet of Things

How IoT is Revolutionizing Supply Chain Management


IoT, the Internet of Things, has gradually led us into a truly connected world, making the collection and exchange of data far more convenient. The following passage focuses on IoT’s revolutionary role in supply chain management, such as fleet management and asset tracking, with examples of 3 big players – Verizon, Cisco and IBM.

It takes 6 minutes to read.

Supply chain management is a foundational business process that impacts nearly every enterprise, whether you’re a manufacturer who must transport parts into a factory and finished goods to the point of sale, or a farming operation tasked with transporting produce for processing or to commercial kitchens.

Quite often, this important task involves third-party logistics companies, which, while filling an important role, can also insert inefficiency and lack of visibility into the process.

Sensors that can monitor the condition of products in shipment and cloud platforms that can optimize delivery routes are just some of the technologies that are currently disrupting the way supply chains are managed.

Asset Tracking & Fleet Management

Two important supply chain management use cases that have been enabled by the Internet of Things (IoT) are asset tracking and fleet management.

# Asset Tracking

Based on RFID tags or global SIMs, for example, asset tracking allows a supply chain manager to know in real-time where a product, truck, or shipping container is located; if it’s passing through the Panama Canal on a container ship or moving down an assembly line on a factory floor.

This granular insight into the supply chain, when coupled with cloud computing and data analytics, can inform predictive models that allow for up-to-the-second delivery information, which, in turn, can create efficiencies in staffing levels as it relates to monitoring and receiving products, as well as the availability of complementary assets, like a crane needed to unload a barge or a forklift to load a truck.

# Fleet Management

To fully understand the impact of fleet management, consider FedEx or DHL drivers tasked with moving light-trucks filled with packages around an urban area. Factors such as weather, traffic congestion, time of day, day of the week, and whether a co-worker called in sick can all change the time it takes to get packages from a warehouse to the customer.

With so many variables, it’s unrealistic to expect that a human could always make the most efficient decisions. However, cloud platforms that are fed data from the fleet, traffic models, weather reports, and other sources, can plot a much more efficient route.

Packages get to the customer faster, ensuring a better end-user experience. Also, driver headcounts, fuel consumption, and maintenance costs can all be reduced. Finally, fleet management allows operators to know, based on analysis, that asset reliability, availability, and efficiency are all optimized.

Network Operators & Equipment Vendors

From the perspective of network operators and equipment vendors, asset tracking and fleet management are low-hanging fruit for a number of reasons.

Almost every potential customer engages in some form of supply chain management, equating to a huge addressable market. Also, the necessary technology is well-understood, readily available, and easily integrated into existing enterprise IT platforms.

As with many other enterprise and industrial IoT use cases, most of the major players are approaching supply chain management with an end-to-end solution, which is meant to ease adoption for buyers by bringing a turn-key solution from a single vendor point-of-contact.

While that sounds easy enough, this means the vendor, to truly bring an E2E offering, needs domain expertise in IP connectivity, cloud services, security, hardware and positioning.

How Big Players are Using and Enabling Asset Tracking & Fleet Management


Verizon is looking to leverage its investment in a nationwide LTE network and spectrum to support IoT services such as asset tracking and fleet management.

The selling point for LTE for IoT, particularly LTE Cat M1, is dependability, scalability, security, cost, and long battery life for sensors and other field appliances.

Verizon is partnering with Sequans to design and build Cat-M1 chips that embed Verizon’s ThingSpace IoT management platform. This would let enterprise users easily develop and deploy devices tailor-made to support their particular role in the supply chain process.


The same techniques that help a delivery driver optimize his or her route can be used to help save lives.

Cisco worked with the nonprofit California Shock Trauma Air Rescue (CALSTAR) air ambulance service to bring efficiency into its dispatch system. When an emergency call is routed to CALSTAR dispatch, the public safety answering point is geo-matched to the nearest air ambulance crew, which is, in turn, dispatched.

The dispatcher can speak with the ambulance crew and emergency caller through one system, which facilitates communications about arrival and lift time, as well as helps the crew prep for dynamic emergency situations.

“The Internet of Everything is connecting our people, processes, and data in ways that we couldn’t do before,” CALSTAR IT Director Julie Hyde said. “The biggest change is that we have better operational control now. Operations has greater peace of mind and so do crews, because they know that our technology helps ensure their safety and security.”


Obviously, data analytics is a big part of deriving supply chain efficiency from IoT. To better understand the role of big data, let’s look at how IBM is leveraging its Watson artificial intelligence platform to address supply chain needs.

In a recent white paper, IBM noted that “as much as 65% of the value of a company’s products or services is derived from suppliers.” To overcome lack of transparency into the supply chain, the report author concludes that, “By establishing greater visibility into supply chain data and processes and leveraging cognitive technologies, supply chain organizations can both predict and mitigate disruptions and risks and deliver more value to the business.”

In terms of visibility, IBM suggests providing every supply chain stakeholder with a shared, unified view of relevant data. In a case study of customer Bonnie Plants, which provides plants to retail locations, IBM enabled “real-time visibility [which] allows the company to ship new plants where and when they are needed.”

The other big piece is predictive abilities — if you can see a potential supply chain disruption coming, it’s easier to plan and mitigate.

Working with IBM, KeHE Distributors modernized its logistics network to ensure operational efficiency. “In our industry, operating lean is crucial to combat downward pressure on margins,” Carl Snyder of KeHE said. “We have not experienced any unplanned downtime, keeping our logistics network running smoothly and cost effectively.”

By Brian RayFollow, an entreprenuer, founder of Link Labs.




Digital Strategy Digital Transformation Highlights Top-Transformation

A digital transformation case study: The Met Office

[vc_row][vc_column][vc_column_text]Digital transformation has brought new mode of thinking and exciting experience to re-vitalize the traditional weather industry, as what people perceive when using the Met Office, the UK’s national weather service. The content and service it offers to its users as well as the internal structure of the organization are greatly change to better interact with the public. The following passage is a reader friendly introduction of the on-going digital transformation with such a successful case.

It takes 8 minutes to read.

It was 1758 when Samuel Johnston wrote: “When two Englishmen meet, their first talk is of the weather.” Fast forward 250 years or so and he’s still pretty much spot on.

The only difference now is that digital technology enables us to talk about it even more.

For the Met Office – the UK’s national weather service – shifting to a digital-first approach hasn’t just meant reacting to this change in consumer behaviour.

Digital now spans across the entire organisation, impacting everything from research to content marketing and internal culture. I recently spoke with Simon Swan –working in digital strategy and transformation at the Met Office – to gain more of an understanding about the organisation’s ongoing journey.

Growing reach and revenue through a digital team

Despite being in the public sector, it’s important to first remember that the Met Office is also a trading fund (within the Department for Business, Energy and Industrial Strategy), operating on a commercial basis under set targets, meaning that it needs to generate revenue.

When Simon first started at the organisation, it mainly did this through B2B partnerships – working with multiple business areas across the UK and globally. At this time, the company had no real digital marketing team to speak of, however –identifying the opportunity to monetise the reach of the Met Office through sponsorship programs and advertising – this soon became a priority.

Simon started in the role of head of digital marketing at the Met Office with a focus on building out the digital team and identifying ways to grow reach and further revenue. This also fell in line with the organisation’s central remit –to increase awareness of the Met Office as an organisation that delivers socioeconomic benefits, as well as provides weather warning information to the public at large.

Creating a point of difference through content strategy

One of the biggest challenges the Met Office has always faced is differentiating itself in a competitive market. Recent growth in new technology – an explosion of mobile apps, APIs, and even voice search – means data around weather has become much more accessible.

In the face of stiff competition, the Met Office set out to achieve a point of difference, focusing much more heavily on its content marketing efforts through storytelling.

One of the first steps was to determine exactly what everyday consumers want from the Met Office. Turning to analytics, it soon found that the answer is not simply data, but as Simon describes it, the ‘what, the why, the where, the when’ that surrounds it.

In other words, users want content that brings weather data to life – information that impacts decision making, event planning, or aids learning about particular weather phenomenon, for example, the answer to questions like ‘what is a weather bomb’?

Drawing on the huge vertical knowledge of scientists working within the organisation, the Met Office has set out to separate itself by creating and distributing this kind of content. Using the pillars of trust, authority and relevancy, it has been able to build on its social strategy over the past few years in particular, growing to a combined audience of around 1.75 million. In turn, this has also led to the creation and optimisation of new channels to better interact with the public.

 Excerpt from a Met Office infographic about the pollen forecast – an product of the organisation’s content strategy

Optimising digital formats and content

Since discovering that users desire contextual information about the weather, the Met Office has also focused efforts on determining the specific kinds of content that drives the most engagement.

Video in particular continues to be an effective tool, also helping to differentiate the organisation’s mobile app from competitors. It provides users with an updated weather forecast four times a day, and includes other innovative features like an interactive rain fall map and pollen push notifications.

The Met Office also optimises content based on different audience demographics, pushing out tailored infographics, videos, and blogs geared to people interested in seasonal or timely events, such as Glastonbury festival or the pollen season. Again, it is this kind of contextual information that really drives engagement across all channels.

“Whether it’s video vs. infographics, how we use YouTube compared to Instagram, or how we use Twitter

for customer service – it’s all about how we can use these channels to help us

differentiate our proposition around weather and climate

and pass that information directly back to the public.” 

Collaboration and digital education across the organisation

So, what does it take to produce this type of content? In order to properly serve digital users, the Met Office realised that collaboration was going to be key, with the digital marketing team working closely with everyone from scientists and forecasters to the observation and graphics departments.

The solution has been working with various departments to explore and find areas of real value, educating internal teams on how collaborating horizontally can benefit all.

For example, if the core digital team is able to determine that a specific area of content works well on social – let’s say satellite imagery, for instance – it is able to feed this back to the satellite team to help them better understand the type of information they should be sharing.

Another example could be discovering any gaps or opportunities for content. For instance, if a user asks a question on social media about rain formation, the team can directly liaise with scientists and forecasters to establish how best to answer it.

In order to facilitate and further this approach, the Met Office has recently set up the Digital Academy – an initiative designed to help educate and up-skill internal teams. It involves fortnightly workshops and webinars on different digital principles, with talks often held by external organisations.

The end goal is to expand digital knowledge internally, encourage and foster a culture of knowledge sharing, as well as give clients a better understanding of how they can work with the Met Office.

Commercial partnerships and new opportunities (search and voice)

Alongside internal and user-facing activity, the Met Office also provides industry-specific weather and climate services.

The organisation has been working with a number of companies in the retail space, with this market particularly interested in how weather data can be used to better understand and optimise product sales. One specific example is an affiliate network that worked with the Met Office to optimise product feeds, enabling the network to recognise what products to promote and when, in accordance with weather changes.

Another area of interest for the Met Office is voice technology – unsurprising considering that weather is the second-most popular search activity enabled through voice devices.

The Met Office’s Informatics Lab recently designed an Amazon Alexa Skill which helps users to make decisions by talking to the device. Instead of merely responding to a request for the weather, the technology also recommends recreational activity based on the forecast, including contextual detail such as location and time.

Establishing the right culture

While other areas of technology such as voice and machine learning undoubtedly offer exciting opportunities for the Met Office, Simon suggests that its main focus will be consolidating its position in the market. It is through internal initiatives like the Digital Academy that it aims to do this.

As well as sharing knowledge, Simon also sees the Digital Academy as a vital way of establishing a digital culture throughout the organisation – extending to employee values and attitudes, not just technical expertise.

“Culture is the hard bit,” he says, “you can spend money on finding people with the specific tactical skills, but it is the attitude that drives real innovation.”

By Nikki Gilliland, a writer at Econsultancy.


Digital Operation Digital Transformation Highlights

Machine Empathy: How Machine Learning Can Bring Real Insight to UX Design


Great UX design embodies empathy between the company and its users. The roots of unsatisfying design, which often leads to bad user experience, may lie in the wrong analytical tools and insufficient information of user. The following passage illustrates a better approach to understand the user behavior by using other available tools except Google Analytics, with an example of a transportation information website. The meaningful conclusion out of the numerical statistics, coupled with human interpretation, makes for smooth UX design.

It takes you 8 minutes to read.

Combining Empathy and Data Mining for Better UX

Empathy has rightfully become predicate to good user experience (UX) design. But the means designers use to achieve empathy—such as Personas—fall short of their intended purpose.

While the motivation to use personas is noble, too often they are the product of idealized users built on demographic profiles rather than original insight sourced from real user behavior.

The limitations of personas are well understood. This recent video gives a good breakdown on the limitations while this paper from 2010 describes all sorts of pitfalls of developing personas from the process being unscientific to having a tendency towards groupthink and confirmation bias.

But should personas be thrown out altogether? By what method can priorities be made for design if there are no identified groups to serve? How is UX design to possess any empathy as is cited so often if the motivations or mindsets of the users aren’t known nor considered?

An alternative approach to empathy?—?incrementalism?—?uses behavioral data to incrementally change design toward an optimized UX. But this method, which focuses on conversion over quality of experience, inhibits innovation by making incremental improvements rather than holistic solutions.

We believe there’s a better way to approach UX challenges by matching the needs of the designer with the right data and analytical tools.

Roots of the Problem

Before we dive into the solution, it’s worth looking at the causes of how we arrived at this point:

  1. An over-reliance on one tool, Google Analytics
  2. Siloed thinking by using only web data for web UX
  3. Superficial analysis of the data available enabling the HiPPO effect and leading to subjective creation of personas

The first point is the underlying cause of the other two. Expertise with Google Analytics passes wrongly for expertise in website analysis. It is Mazlow’s Hammer for website data when other sources and analytical tools are available. In short, the wrong tools and insufficient information lead to an arbitrary starting point for design.

Let’s take a simple example of a transportation information website where a key performance indicator — time on site — can be linked to opposing motivations and a false understanding of experience. In one case, a train line was down and commuters needed to use the site to find alternative routes.High time on site is linked to friction and frustration for the user in finding relevant information.Conversely, the peak-season tourist plotting her route around a city would need more time for consideration to choose how best to tour the sights.

Without grounding in an understanding of what different users are trying to achieve, well-meaning site goals can become false flags to performance.

A Better Way to Understand User Behavior

Grouping users is still essential for developing priorities in UX design, but how? It’s actually as simple as gathering more meaningful user data and using the right analytical tools and methods.

Here are our 4 steps to developing rich and meaningful user groups:

1.Take ownership of your web user data

Back in 2005 when Google acquired Urchin Software the options for web analytics were a little limited and were all paid-for or very simplistic. It would be hard to imagine how ubiquitous Urchin would become once made free and rebranded as Google Analytics. To its credit (and benefit) Google has given everyone who operates a website an opportunity to measure its performance in a easy and effective way, but unless you pay $100,000 for the premium version you cannot get your raw data out for external analysis.

Nor do you need to invest in commercial level systems like Adobe or Webtrends. Although these systems are powerful, you would be merely swapping, with unnecessary expense and time, one walled-garden for another.

Instead there are systems that are low cost or free that give rich visitor data that can be exported for external analysis. The systems we use are:

  • Piwik — open-source free analytics software
  • Opentracker — low cost software offering visitor identification

These can be installed easily as code snippets in the website master page template or in a tag manager to run side by side with Google Analytics.

Ownership goes beyond tin-hatted concepts of a single corporate entity controlling your information. While the duopoly of digital media may over time make this worry more mainstream, the main threat is that analytical tools are tied to the feature priorities of what Google and/or Facebook deem most profitable to them, not to you.

2.Think about all the external factors that influence users’ motivations and mindsets towards your site

Typically we run client workshops to map the journey of the user before they arrive at the site — and catalog all the relevant data available, including sources outside web analytics. For example, in the travel example cited above, we assembled data sets related to weather anomalies and service disruptions.

The more scenarios and user journeys uncovered, the more external data can be brought to bear.

3.Gather all the data and analyze

This is where things start to get interesting. Analysis needs the right tools and skills. Fortunately both of these are pretty abundant.

Our choices are typically:

  • MySQL, PostgreSQL, or SQLite for collating data held in relational databases
  • The statistical programming language R and its development environment R Studio
  • AWS to run analyses at scale

The data to be analyzed should be as flat and tidy as possible, meaning every row is a visit (observation) and every column is a descriptor (variable). If you are from the world of relational databases this may seem wasteful when the data for analysis could have millions of rows and dozens of columns. R is designed to work at scale; analyzing a few hundred thousand rows can take a few seconds on a laptop. For huge datasets, prototypes can be developed on a personal computer using a data sample and the same analytical code can then run in the cloud on the full dataset.

Once the data is tidy we can use unsupervised machine learning via the ‘Cluster’ package in R. This type of analysis is used in realms as varied as medical research to pricing of cell phone packages. It may sound really complicated and a little scary, but it isn’t. The mathematics are complex, but the principle and practical execution are simple: the machine learning algorithms assign each visit into a group (cluster) by simultaneously maximizing and minimizing distances between all the variables describing the visit.

Firstly we need to know the optimal number of clusters. Trial and error can work to visually assess and get the balance of whether the resulting clusters are too similar, too different or just right. Alternatively there’s the fviz_nbclust function in the factoextra package that can give the optimal number:

The k statistic peaks around 4, hence we’ll run the functions for a target of 4 clusters.

There are a number of visualisation outputs; a popular one is using radar charts to understand magnitude of variables for each cluster.

Each radar segment for this chart shows the relative importance of each variable within each cluster. A numerical output will also tell us what proportion of the overall sample is represented by each cluster, giving objective priorities.


From the radar chart above we can interpret the clusters into meaningful segments. Even with just 2 external factors, weather and service, a greater context is brought to the three web analytics metrics.

For the above example, the segments might be:

  • Imperators — Bad weather and low time on site; they need information quickly
  • Generalists — Not quite sure as to what information they need but will take a wander around the site
  • Considerers — High engagement
  • Panickers — Referrals through from another site to check service

The above example uses only five variables — more variables can reveal more about the end users, but from the clusters available we can intuit some priorities around design:

  • How best to signpost specific travel and service-status content needed by panickers and imperators?
  • Can we provide a logical navigational structure to generalists to get them to where they need to be more efficiently?
  • What calls to action can best feed the engagement considerers crave?

Since every visit has been assigned into a cluster, If we serve these priorities and hence the segments, very little remains to be solved.

To restate, the more meaningful the variables we capture for each user visit, the more descriptive the clusters, and the better the conclusions about segments and briefing for design.

Synthesized Creativity or Machine Empathy?

The math of machine learning can remove arbitrary notions of what web analytics mean by combining user data with with contextual factors. But there is still plenty of need for human interpretation and creativity to color in the massive white space between the numbers. To be successful, designers and data scientists need to work together to develop meaningful insights and purpose driven segments.

Will artificial intelligence ever be able to bridge the gap between analytics and creativity? Not yet, but with each day and every improved algorithm we take one more step toward true machine empathy.

By Jason Kowal, partner at Deducive


Digital Operation Highlights

7 Ways to Test Your Product Idea & Gather Real-World Feedback


Feedback works as a key link preceding the launch of a new product. In a digital time, how to acquire honest and thought-provoking feedback through both online tools like and Google Analytics and offline encounters? The following passage gives guidance on leveraging face-to-face connections with potential users and successful entrepreneurs and connections through internet.

It takes you 10 minutes to read.

Before you can effectively transition from potentially marketable idea to actually profitable product, you must first test your idea by collecting real-world feedback from actual consumers — otherwise, it’s simply impossible to determine with any certainty whether your idea responds to a true monetizable customer pain.

Today I’m going to be sharing with you a number of effective strategies that you can use to test how the market is likely to respond to your idea without actually having to launch a tangible product.

I’m hoping not only will these tactics allow you to gain concrete insight into whether actual customers will view your product as an attractive solution to a pain they need resolved, but they will also cost you little-to-nothing to execute.

Note: before you embark on any of these strategies, make sure you:

  • Can present something tangible — a mockup, wireframe, or even a simple sketch — to the people with whom you’ll be sharing your idea (i.e., at this stage your idea can be mostly, but not entirely, words — consumers need some sort of visual, audible, or physical representation in order to connect with your idea);
  • Learn how to effectively describe your idea and explain the problem(s) it will solve using simple language (e.g., language that a 6th-grader would understand);
  • Spend a significant amount of time thinking about and working on the exact questions to which you want to receive answers (test out your mock questions on others before going “into the field” to make sure it’s fully clear what you’re asking in each case); and
  • Detach yourself from your idea in the sense that you’re able to discuss it in a dispassionate and rational way (your goal is not to sell or defend your idea but rather to present it in a neutral fashion and thereby gather objective feedback necessary to tweaking and improving your idea).

Here are 7 free (or nearly free) ways to test the validity of your idea before jumping into the market and launching your product:

1. The $20 Starbucks Test

  • Take out $20 from an ATM and visit your nearest Starbucks location.
  • Politely walk up to one stranger at a time and calmly explain your situation: “Excuse me, do you have a moment to help me with something? My brother will be quitting his job at the end of the week and investing his life-savings into an idea we have for a start-up company. If I were to buy you a coffee would you be willing to give me your honest thoughts on whether you think the idea would work? That’s it, no catch — just your honest feedback.”
  • Objectively pitch your idea to the person. Speak slowly and clearly whilst maintaining eye contact. Be friendly but not overly enthusiastic. Feel free to show him/her whichever visual, auditory, or physical representation you’ve brought with you.
  • Ask the person what he/she thinks of the idea. If he/she seems overly supportive (i.e., trying to please you) then ask: “Can you give me three reasons why you think the idea might not work?” Keep him/her focused on the idea rather than the backstory of how you created it. Listen attentively and do not argue in any way.
  • Thank the person for his/her time and wish him/her a good day.
  • Repeat steps 2–5 over and over until you run out of money. If you feel that you have not collected enough valuable feedback by that point then take out another $20 and start the process over again.

The hope is that the $20 Starbucks Test will allow you to gather a number of previously unrecognized criticisms/objections with which you’ll be able to then fine-tune your future product.

2. The “Knock-On-The-Door” Approach

The above-described Starbucks test is one way of meeting people face-to-face in order to generate real-world feedback on your idea.

Internet entrepreneur and venture capitalist Tony Hsieh recruited his first customers by directly emailing webmasters; he then sold his company for $265 million to Microsoft and founded the ultra successful Zappos.

How to create impact with direct mail #infographic 

Noah Kagan, the founder of AppSumo, began using a similar direct contact approach; he too emphasizes the importance of dealing with people in person during the earliest days of your start-up.

Using the power of the Internet is a second method:

  • Create a set of well-thought out, easy-to-understand, and clearly articulated questions about your idea (the pain it’s meant to solve, the ways in which it functions as the fix, and so on).
  • Upload the questions as an online survey connected to a sign-up link for product launch notifications. Offer potential participants some sort of incentive for taking the survey (e.g., the chance to win an Amazon gift-card).
  • If you’re building an enterprise product then use Google Search to find the names and emails of potential customers; if you plan to operate in the consumer space then leverage your network of friends to collect potential participants.
  • Locate relevant groups on sites like LinkedIn, Facebook, Quora, and Reddit, and send each of the members a short, personalized, and genuine message about your survey.
  • Do not send generic, spammy messages or emails; rather, act like a friend who’s asking for some quick and painless feedback.

If your messages/emails are written properly and sent out in non-spammy ways then some of the recipients might become your future customers, with many of them offering to speak to you via online video chat or in person in order to give you additional feedback on your idea.

3. Polls and Surveys

As a continuation of the previous strategy, consider utilizing the power of online surveys in order to generate real market feedback about your idea.

There are many free and paid survey tools that you can use, including:

Keep the following basic rules in mind when writing and sending out surveys:

  • Keep the surveys simple, i.e., use basic language, easy-to-understand questions, and clearly labeled answer options
  • Offer participants some kind of incentive or prize (e.g. a discount or a chance to win something)

Always add links to email sign-ups to ensure that you can directly contact respondents in the future and thereby dig out additional feedback from them.

4. Send out a Test Ad Campaign and Measure the Results

Many advertising platforms offer new clients free credits to start using their services.

Google AdWords, Facebook Ads, LinkedIn Ads, AdRoll, Twitter, etc., all maintain offers for free advertising credits between $50 and $150 for new accounts. Use Google to find the service most attractive to you, sign up for some free credits, and then follow these steps:

  • Create a simple landing page presenting a unique value proposition (UVP) and a sign-up link (or even better, a real “pre-order” button that collects actual pre-orders for your future product)
  • Add Google Analytics tracking codes to your site and call-to-action (CTA) buttons
  • Run campaigns to drive traffic to your site and check the conversion rates
  • Follow-Up with people who register using the sign-up link in order to learn more about their specific needs and wants, and why they signed up in the first place

Aside from gathering data that will help you test whether your UVP sells well, the test ad campaign method will also allow you to determine which traffic channels work best for your UVP and where can you get the best return-on-investment (ROI) once you start marketing your actual product.

5. Beta Promotion Sites and Startup Directories

Beta promotion sites like allow you to distribute your simple, pre-launch site amongst early adopters and then collect their sign-ups to participate in beta testing and customer feedback campaigns.

Most of the submissions are free; with respect to in particular, there is a paid option that allows you to distribute your site even faster.

Follow these steps to launch your own beta promotion:

  1. Create a simple landing page presenting a unique value proposition (UVP) and a sign-up link (or even better, a real “pre-order” button that collects actual pre-orders for your future product)
  2. Add your submissions using this list over at Quora
  3. Track the results and follow-up with people who respond to your campaign
  4. Visit websites like Reddit, Hacker News, or specific forums and online communities and ask for feedback. Do not attempt to promote or sell anything; just be humble and ask for some honest opinions from those who are interested in contributing and you’ll get some feedback.

6. Meet-Ups and Events

One of the best ways to get out of the office building and talk to real-world people is to strategically locate customers by focusing on specific meet-ups and events.

An easy method for doing this is to search sites like and for meet-up groups and events relevant to your particular niche. This can be very beneficial as it allows you to find targeted communities of potential users for your future product.

When physically attending a meet-up or event, keep in mind that you’re there to engage: talk to people, ask questions, elicit feedback, and encourage others to be honest/upfront with their opinions. Again, don’t promote yourself in any kind of over-the-top, obvious, or annoying way.

You always get better results by being real with people and asking for friendly feedback rather than aggressively pushing your idea or product.

Bonus tip: Get a bunch of double-sided business cards: one side with your contact details listed and the other with a special sign-up URL to your site. For instance, “Get 20% off on”.

7. Earn Face-Time with Successful Entrepreneurs

Leverage your social and professional networks — call in favours, complete free work for others, offer to organize mutual introductions — such that you earn the privilege to meet with some of the most successful people you know (preferably one-on-one, if not then in a small group setting).

If you’re unable to arrange a meeting on your own then politely ask friends and family for introductions.

Successful entrepreneurs are individuals constantly interacting with the market. Even though they might not be your actual customers, you will almost certainly learn a lot and acquire some great feedback from established professionals who have successfully completed the journey on which you’re now starting out.

Thus, you should absolutely put the effort into politely and humbly trying to catch the ear of one or more founders with whom you could discuss your idea.

Remember: entrepreneurs love to help out other entrepreneurs, especially because there is a shared understanding and respect amongst self-driven professionals who recognize the importance of hard work and networking.

If a successful entrepreneur sees potential in your idea then he/she may very well play a major role in helping you ultimately transition from idea to product — which, after all, is the entire point of the strategies outlined in this article!

By Mark McDonald, co-founder at