Hail Mary (Meeker)!

Hail Mary (Meeker)

Internet

 

On the 29th of May, Mary Meeker released her annual compendium of the digital state of the world – the KPCB Internet Trends. For those who may not remember, Mary Meeker was a veteran who survived the dot.com crash and also the financial crisis of 2008, as the head of tech research for Morgan Stanley. She was named as among the 10 smartest people in Tech. She now serves as a partner at KPCB (Kleiner Perkins Caufield and Byers) and has been publishing her annual opus for a few years now.

The problem is that when you’re Mary Meeker, you can get away by putting out a deck with 294 slides. For us mere mortals, reading and absorbing this encyclopaedia of information is a challenge by itself. Every year I get this and carefully save the deck to read in detail and of course, it never happens. So this year, with the benefit of a relatively free weekend, I thought I would do a first pass and pull out some of the most interesting things that I found in the report. So here are my top 10 interesting things to take away from the Mary Meeker report – some of them confirm what we know, while others are what we didn’t know, or are truly counter-intuitive.

What I knew or suspected.

1. The devices story mobile device shipments growth has shrunk to zero. This confirms what we’ve known for a while – device evolution has stalled since Steve Jobs. And since Samsung, the largest manufacturer has a ‘follow Apple’ strategy. Will we see a new device redefine growth or will the we see a decline in shipment numbers next year? HMD – are you watching? (Slide 6)

2. The decline in desktop use despite overall growth. While mobile internet growth is expected, it’s the ‘other devices’ that is interesting. This will presumably include netbooks, etc. but also smart things. I expect in future this category will be broken out to reflect the detail on Internet of Things. (Slide 11)

3. The privacy paradox will be one to watch – after all data is how every single provider improves their services, while keeping prices low, which leads to user spending more time and sharing more data. Versus the regulators needs to protect consumers and protect data use. This will be a key axis of debate going forward and will determine the balance between innovation and protection. Unfortunately Meeker’s slides don’t carry too much insight on this by way of data. (Slides 31-36)

What I didn’t know (I’m intentionally using the singular, as you may well be aware of this)

1. While we’re aware that big tech now dominates the market cap list, what should worry the rest of the pack is how they dominate the R&D spending list, which points to a continuation of their dominance at the top. The top 15 R&D investors list is dominated by 6 technology firms, with 2 each from automotive, petroleum, telcos, Pharma), with GE as the only conglomerate. The top 5 in the list are Amazon, Alphabet, Intel, Apple, and Microsoft. Also, tech firms report the highest growth in R&D, with 9% CAGR and 18% YoY growth. (Slides 40-41)

2. We know that image recognition is an area where AI has now passed the human levels of accuracy leading to all kind of applications across scan analysis in healthcare, and more controversial applications such as face recognition. Now, voice-based natural language recognition is another areas as also demonstrated recently by Google. This should drive a revolution in customer contact centres and in human-computer interfaces in general. (Slide 25)

3. The extent to whichAmazon & Google are getting to dominate the enterprise AI race. To be honest, we know instinctively that the AI race will be one by players with the largest data stockpile. But the range of services being offered for enterprise customers is still an eye-opener. We’ve just started playing around with Google’s Dialogflow, but they also have Tensor (cloud-based H/w), the recently announced AutoML (machine learning), and Vision API (Image recognition), while Amazon has AWS based tools such as Rekognition (image recognition), Comprehend (NLP), Sagemaker (ML framework), and of course their AWS GPU clusters. (Slide 198 – 200)

4. The growth of Fortnight and Twitch on the gaming front – pushes forward what we saw with Pokemon Go. The sweet spot between the hardcore platform based gamers and the casual gamers and kids where millions of people get just a little bit more involved about game, that does not need a special platform – is the story behind Fortnight (Slide 24)

What I didn’t expect

1. The highest increase in spending in enterprise IT is in networking equipment. This is a surprise. I haven’t found the data on this yet, and while the 2nd and 3rd place results don’t surprise me, (AI and hyper-converged infrastructure), my curiosity is definitely piqued by why companies are spending more on networking equipment – connecting to cloud environments from the enterprise perhaps? More connected devices and environments?

2. I’m seeing a lot more confirmation of the models of lifelong learning. This is repeated by Meeker, but her really interesting insight is around how much more learning freelancers invest in compared to their presumably complacent employee counterparts. Perhaps unsurprisingly the top courses sought include AI & related subjects, cryptocurrency, maths and English. (Slides 236 and 233)

3. Meeker makes a great point but Slack and dropbox and I wouldn’t have picked these 2 companies as the flagbearers of consumer-grade technology in the enterprise. But clearly, they are among the most penetrated consumer style tools in the corporate environment. (Slides 264-268)

Meeker has a big section on the Job market, on-demand jobs and future jobs. She also makes the same point others have made about how all technologies so far has created net new jobs. While I agree with this backlog, history is not always the best predictor of the future. And the fact that there will be net new jobs tends to gloss over the significant short-term and geographical disruption in livelihoods that is likely to occur. Think Detroit or Sheffield. There may be more automotive and steel manufacturing jobs today than in 1980 but they are in China, not in Detroit or Sheffield. And so of not much solace to the unemployed factory worker and his / her family in these towns. This may well be the story of AI – but potentially at a larger scale and possibly in a shorter time frame. (See slides 147-163).

There are also useful slides on the gig economy and on-demand jobs now being a scaled phenomenon. (Slides 164-175)

There are also entire sections on China, Immigration and Advertising – which I’ve not delved into as they are currently of less interest to me personally. The E-commerce section also didn’t have anything that jumped out at me as noteworthy. Happy to be corrected!

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Seven in 7: Amazon’s Infinite Monkey Theorem Defence, GDPR Impact on Innovation, Ocado’s Successful Transformation, and More…

Seven for 7: Alexa sends the wrong message; does GDPR take us backwards? Uber crash – design flaw; future gazing with Michio Kaku; AI Winners; Ocado transformation and Energy Industry Updates.

(1) Amazon Echo: message in a bottle

The technology story of the week is undoubtedly the one about Amazon Echo and the message it inadvertently sent. ICMYI, a couple in Oregon had a call from an acquaintance to say that Alexa had sent them a recording of a private conversation of the couple, without their permission, or even knowledge. Amazon’s explanation is that this is the rare combination scenarios where a normal conversation between the couple somehow triggered all the keywords and responses that made Alexa record, validate and send the conversation to the acquaintance. This feels like the equivalent of the money, typewriter and Shakespeare problem, only, it’s not an infinite amount of time.

Here’s Amazon’s explanation: https://www.recode.net/2018/5/24/17391480/amazon-alexa-woman-secret-recording-echo-explanation

(2) GDPR  – impact on marketing and innovation.

I’m sure you’ve all received hundreds of emails in the past week exhorting you to stay in touch and re-sign up for all the emails you’ve been getting from people you didn’t know were sending you emails. But now that the moment has come, how will marketing work in a GDPR world? In one way this will take marketing backwards – as there is now a ban on algorithmic decision making based on behavioural data. It’s a moot point whether advertising falls into this category but companies may want to play it safe and in any case, the confusion will create a speed breaker in the short term. We may now be back in the world where if you’re watching or reading about champions league football you will see a beer ad irrespective of who you are. Not just marketing – a lot of innovation will also come under fire – both because of safety first practices, but also because some organisations will use GDPR as a shield for enabling innovation stifling practices, as highlighted by John Battelle of NewCo Shift. He argues that the regulation favours ‘at scale first parties’ – large tech platforms that provide you with a direct service such as Netflix, Facebook, or Uber – where users are likely to still give consent for data use more readily than to smaller, upcoming or relatively new and unproven services.

Dipayan Ghosh in the HBR – GDPR & advertising: https://hbr.org/2018/05/how-gdpr-will-transform-digital-marketing

John Battelle on GDPR & Innovation: https://shift.newco.co/how-gdpr-kills-the-innovation-economy-844570b70a7a

(3) Driverless / Uber/ Analysis

The analysis of Uber’s recent driverless crash has now thrown some light on what went wrong. And the answers aren’t great for Uber. In a nutshell, the problem is design and not malfunction. Which means that all the components did exactly what they were designed to do. Nothing performed differently and no components were at fault for failing to do their job. But as a collective, the design itself was flawed. The car had 6 seconds and 378 feet of distance to do something about the pedestrian crossing the street with her cycle. But it was confused about what the object was. The human in the car only engaged the steering 1 second before the crash and started breaking 1 second after the collision. The car was not designed to warn the human driver about any possible threats. A lot of the inbuilt safety systems in the Volvo vehicle including tracking driver alertness, emergency braking and collision avoidance, were disabled in the autonomous mode. In a nutshell, the responsibility lies with Uber’s design of autonomous cars. Uber has stopped testing in Arizona but has now started exploring flying taxis. Not a project that might fill you with confidence!

Uber crash analysis: https://sf.curbed.com/2018/5/25/17395196/uber-report-preliminary-arizona-crash-fatal

(4) A glimpse of the future: Michio Kaku & Jack Ma

The robotics industry will take over the automobile industry. Your car will become a robot – you will argue with it. Then your brain will also be robotised and brain net will allow emotions and feelings to be uploaded. You will be able to mentally communicate with things around you. Biotech allows us to create skin, bone, cartilage and organs. Alcoholics may be able to replace their livers with artificial ones. You may be able to scan store goods with a contact lens and see the profit margin on goods. The first 7 mins of this video tells you all of this through the eyes and experience of futurist Michio Kaku. Jack Ma (14 mins in) also talks about trusting the next generation. And how we are transitioning from the industrial era where we made people behave like machines, to a world where we are making machines behave like people. Believe the future before you see it, to be a leader, according to Ma.

https://www.youtube.com/watch?v=K1EZWYqm-5E&feature=youtu.be

(5) Who’s Winning The AI Game?

With the whole world hurtling towards an AI future, this piece looks at who exactly wins the AI game – across 7 different layers. It won’t surprise you to know that China is making amazing gains as a nation – their face recognition can pick out a wanted man in a crowd of 50,000. But it might surprise you to note that Nvidia’s stock is up 1500% in the past 2 years on the back of the success of their GPU chips. Meanwhile, Google is giving away Tensorflow free. All this points to a $3.9 tn market for enterprise AI in 2022. Are you ready for the challenge?

Who wins AI, across 7 layers
https://towardsdatascience.com/who-is-going-to-make-money-in-ai-part-i-77a2f30b8cef

(6) Ocado – digitally transformed.

When Ocado launched in 2000, it was on the heels of Webvan, a category of providers who set up to focus on eCommerce fulfilment, as an arm of Waitrose. Cut to 2018, and Ocado is a story of successful digital transformation. Ocado is today a provider of robotic technology for warehouse automation. Having become profitable in 2014, it now has a valuation of $5.3 bn and is set to become a part of the FTSE 100.

https://www.ajbell.co.uk/news/index-reshuffle-looks-set-deliver-ocado-ftse-100
https://www.theguardian.com/business/2018/may/17/us-deal-boosts-ocados-stock-market-value-above-5bn

(7) Understanding statistics: What medical research reports miss

When a drug is tested and the outcome suggests a 5% chance of a possible side effect, this does not mean that you have a 5% chance of being impacted if the drug is administered to you. It means there is a 5% chance that you will have the condition which leads to you having a 100% likelihood of being impacted. This is a subtle but very important distinction in how we interpret the data. But continuing down this stream of thought, it points to the lack of personalisation of medicine, not just the misinterpretation of data.
https://medium.com/@BlakeGossard/the-underrepresentation-of-you-in-medical-research-85289b591ba

 

Seven in 7 – Agile @ Scale, Maturing AI, The Ring of Success, Defending Democracy and More…

Agile at scale
As we head into the TCS UK Innovation Forum this week, I’m preparing myself to discuss big ideas and disruptive changes. With that in mind, this week’s Seven in 7 looks at scaling AI, a startup that was bought for a billion dollars, and hacking democracy. But also, as we’re committed to becoming agile as an organisation, where better to start, than at the great article in the new HBR about how to drive agile at scale!

(1) Doing Agile at Scale

This is a very timely look at Agile adoption at scale in the enterprise. It starts with enshrining Agile values in leadership roles, which requires a continuous approach to strategy. The next key thing is a clear taxonomy of initiatives which may be classified into 3 categories: customer experiences, business processes, and IT systems. The next step is sequencing the initiatives, with a clear understanding of timelines. It can take 5-7 years for real business impact, but there should be immediate customer value. Enterprise systems such as SAP can be delivered using agile as well. But it needs the organisation to create and move with a common rhythm. There are businesses working in agile who use hundreds of teams, solve large problems, and build sophisticated products. This can be made easier with modular products and operating architectures – which essentially mean the plug and play capabilities of individual components. It’s important to have shared priorities and financial empowerment of teams. Talent acquisition management needs to be reshaped to meet the new needs. And funding of projects and initiatives needs to be seen as ‘options for further discovery’. After all, at the heart of agile is the ability to proceed with a clear vision but without necessarily knowing all the steps to get there.

(2) Artificial Intelligence At Scale – for non-technology firms

It’s clear that Tech firms from Google, to Amazon and Twitter, have all been able to deploy AI at scale – in enabling recommendations, analysis and predictive behaviour. For non-tech firms too, the time may have come for delivering scaled AI. One of the key areas where AI seems to be ready to scale is around computer vision (image and video analysis) – relevant to insurance, security, or agribusinesses. The article below from the Economist also quotes TCS’s Gautam Shroff, who runs the NADIA chatbot project. A critical assertion the article makes is that implementing AI is not the same as installing a Microsoft program. This might be obvious, but what is less so, is that AI programs by design get better with age, and may be quite rudimentary at launch. Businesses looking to implement AI may need to play across multiple time horizons. And while the short-term opportunity and temptation is to focus on costs, there role of AI in creating new value is clearly much bigger.


(3) The Ring of Success:

What makes a new product successful? I met Jamie, the founder of Ring a couple of years ago in London and was struck by his directness and commitment. He even appears in his company’s ads. Ring.com was recently acquired by Amazon for $1bn. Here one of the backers of Ring talks about the factors which made Ring a success. In a nutshell, the list includes (1) the qualities of the founder, (2) execution focus and excellence, (3) continuous improvements, (4) having a single purpose, (5) pricing and customer value. (6) integration of hardware and software. (7) clarity about the role of the brand.


(4) Blockchain and ICO redux:

Do you know your Ethereum from your Eos or your MIATA from your Monero? This piece from the MIT Tech Review will sort you out. And for those of you who are still struggling to understand what exactly blockchain is, here’s a good primer. Of course, you could always go look at my earlier blog post on everything blockchain.

Links:


(5) X and Z – The Millennial Sandwich

X & Z: Or the millennial sandwich. All the talk in the digital revolves around millennial, but there is a generation on either side. The generation X – followed the baby boomers, and it turns out they have a better handle on traditional leadership values than millennial. This article talks about Generation X at work.

On the other side, there’s a generation after the millennials – the generation Z. They’re the ones who don’t have TV’s, don’t do facebook, and live their lives on mobile phones. This article talks about how Financial services are being shaped by Gen Z.


(6) Big tech validates Industry 4.0

This week, the large tech players disclosed significant earnings, beating expectations and seeing share prices surge. In a way it’s a validation of the industry 4.0 model – the abundance of capital, data, and infrastructure will enable businesses to create exponential value, despite the challenges of regulation, data stewardship issues and other problems.  Amazon still has headroom because when push comes to shove, Amazon Prime, which includes all you can consume music and movies can probably increase prices still more.


(7) Defending Democracy

The US elections meets the technology arms race – this article presents experiences from a hacking bootcamp., run for the teams who manage elections. While the details are interesting, there is a larger story here – more than influencing the elections either way, the greater harm this kind of election hacking wreaks is in its ability to shake people’s faith in democracy. As always, there’s no other answer than being prepared, but that’s easier said than done!

Meet The New Consumer

New consumer

The word revolution is overused, but in the past five odd years, there has been a significant change in how customers engage with products and service providers. Thanks to a combination of technologies, the consumer of 2015 is vastly different from 2010.

Let’s look at 6 specific points of change, which will reshape how you need to engage with consumers today.


The Encyclopaedia Effect: The Consumer Knows More
When a customer walks into a TV showroom today, the smart money is on the probability that he or she knows more about the product than the person behind the counter. In part this is exacerbated by the high turnaround and relative inexperience of shop floor staff, but also because consumers today have all the means and have learnt to thoroughly research their purchase – including features, price comparisons, technologies, accessories and performance. Contributing to this is the ease of garnering information via social media.

How ready are you to deal with this consumer? If you’re a retailer, is this a nightmare scenario or are you able to use this to your advantage? Do you arm your shop floor staff with information? Do you enable consumers to do their own research in the store? Do you provide enough authentic information out there for consumers – so they can trust your information?

In many ways, this puts the onus back squarely on the product or service delivery. You can no longer paper over the inferiority of your products through better marketing or better sales. This is a wake up call for product development and service design people. Get it right or you will be found out.

BYOW: Bring Your Own Web

When I last bought an airline ticket from Pune to Chennai in India, I asked the question on facebook about whether I should fly Airline X who had recently had some bad press and I wanted to check if it was a good idea to fly with them. About twenty people responded. Eighteen said it was a really bad idea (one person was being ironic and one was professionally involved with the airline). I was able to make a decision based on a cumulative 5 minutes of research.

It’s the internet to go. It’s carrying wikipedia, amazon, google and the the world’s product databases in your pocket. Earlier, the physical world and the digital world were distinct. You did your comparison shopping on the web and then took a print out to the store. Now you take the web with you to the store. You scan items with your phone and price compare then and there. Or pull up reviews

and product comparisons. Or check calorific values and nutritional advice. This is not a small evolutionary change. It is game changing.

We know that the mobile phone has already in larger or smaller measures replaced wrist watches, calculators, sat-navs & maps, time-tables and a host of other products. Even a spirit level, if you’re into DIY. But it’s ability to tap into the www wherever and whenever you like is arguably its killer app.

And what about your consumer? What is she checking for while selecting your product? Are you making it easier to find that information? Are you enabling or constricting this behaviour? Does your sales process factor in the always addressable consumer?

Generation M: Beyond Millenials

You’ve probably become accustomed to classifying yourself as a digital immigrant or a digital native. Maybe your kidds are the natives in your household. The “digital generation” aren’t even a homogenous group any more. The internet generation is a different breed from the mobile generation.

The mobile generation, or as Tammy Erickson calls it in this HBR article, the Re-Generation, was born around 1995 or later, is the generation that wants to swipe every screen they come across, and expects to be on multiple screens at the same time. This generation is all about expectations of connectivity, and being willing participants in solving issues – digital activists or at least aware of their role and influence by the virtue of a simple “like”.

If we are to go with this classification, this generation is about to enter the work force, armed with the ability to touch-text like their parents could touch-type. This generation can start a flash mob or, unfortunately, a riot from their hand held devices.

If you’ve been thinking about the “mobile-first” mantra – this is probably the generation of users it is critical for. Expect your first point of contact with consumers from this generation to be on the mobile device. Maybe even a significant part of all your interactions will be on the device. 

Perhaps it’s time to start thinking beyond mobile-first, to mobile-only. How geared up for you for this mobile-only relationship?

The Shazam Effect: Telescoping AIDA

Back then (10 years ago), you heard a song, you tried to find out what it was, maybe you heard it again, then on the radio. Somebody told you what the song was if you were able to hum it. Or you searched the lyrics on the internet. You went to the music store / Amazon and bought the cd, if it was worth the £7.99, or whatever the arbitrary price point for the cd was.

Now you hear and like a song that you’ve never heard before, you “Shazam” it, and it tells you the song, artist, and offers you the chance to buy it with a single click off itunes. In 30 seconds, from never having heard the song, you now own it.

This telescoping of the traditional “AIDA” marketing and sales cycle is what the mobile world is accelerating. Real time is in. Waiting is out. Consumers are starting to expect this in more and more areas. Whether its your bank account or your energy bill, or an itemized break up of your estimate for fitting out a new nursery, there is an increased expectation to make it available now.

How real time is your business? How long do customers have to wait for information about your products and services? How much self service do you enable in the information buffet?


The Interface is Dead: Long Live The Interface

We’ve argued about multi-screens, second-screens and even third screens, but what is happening now, is much more amorphous. The screen is vanishing, yet it’s everywhere. On your watch, in your line of sight from a wearable frame, on your shoes and in your car. In fact, sometimes it’s not a screen at all, just a natural interface. Think of Nest, or Amazon Echo, and it’s not a screen that comes to mind, is it? And once we get into the internet of things, the environment will be one giant interface.

With both computing and interfaces becoming much more amorphous, you and your consumer will always be connected in multiple ways. Are you ready for this kind of commitment?

Federated Identities

The two biggest challenges historically, used to be creating a single view of consumer data and marketing to a segment of one. Today, both are addressable with current technology. This project from Metlife, US is a great example of the former, and Amazon, Apple and Google all do a good job of the latter. The conceptual battle ground has moved. What’s even more granular than the individual? Federated identities.

Your customer in her office and your customer at the park with her kids are not really the same persona. Her needs are different, different receptors are at work, her emotional states are different. How can you tailor the messaging to this kind of contextual personas which are segments of an individual? This is very relevant if we’re going to talk about real time and always connected consumers. You have to model the different personas within a single person, based on context. This is your next assignment, should you accept it.

In Conclusion

These categories are just useful labels to stick onto a wide set of complex and ongoing changes. The journey isn’t over yet, but already, not recognising and adapting to these changes could mean that you are out of step with the consumer of today.

Digi-Tally: Through My Digital Viewfinder, Jan 21, 2015

This is still the week of the CES after-glow, and there’s a lot of reflection in the media about what we saw at CES. In a nutshell, and as summarised in the TWIT podcast, no tablets and more cars. Autonomous vehicles has been one of the areas that has moved forward quicker than most of us had anticipated and may have great positive externalities by way of enabling a sharing economy for transport. In much the same way as the word “television” has been redefined in the past decade, we may be entering a similarly transformative phase for ‘automobiles’. It may well be a reaffirmation of the name – a self driving car is after all truly auto-mobile. But increasingly we may start to see the car as a network, a node on a larger network, or a collection of smart (and inter-changeable) components. On the other hand the broader IOT examples keep mushrooming, and we’ll no doubt be exposed to weird and wonderful examples of the power of Internet of Things – from smart security to home automation, and from wearable health and wellness monitors to self managed environments.

It’s also been the week for spotlighting the great transition of technology eras – as we move from the PC & desktop era into the untethered, wireless, mobile and ubiquitous computing era, the struggles of Intel and IBM amongst the behemoths of the 90s and 00’s are sharply in focus. Intel shipped over 100m chips, but are still dramatically dependent on the shrinking PC market. They’ve made an entry into the wearables, tablets and sensors space (interestingly, by acquiring a Chinese firm), but the numbers are still small and analysts aren’t convinced yet. IBM have just announced a 11th straight quarter of declining revenues. The slowdown is precipitated by the hardware business, with the digital arms, including mobile, security and cloud showing strong growth but very low numbers. Overall, a 16% growth in “digital” is probably not good enough, and the combined weight of 27% is impressive, but you sense that the bits that are big aren’t growing fast enough and that the parts that are growing well, aren’t big enough, to actually create an overall positive outlook for IBM just yet. At Cognizant, we often speak about the shifts of the “S-curves” we are currently in between the Web era S-curve (dominated by fixed wireless and PCs) to a digital S-curve – dominated by ubiqutous, nano-computing and wireless connectivity. Intel and IBM’s challenges are symptomatic of the difficulty of transitioning success from one wave to the next. But to state the blindingly obvious, they will not be alone. How will your business make this jump?

I continue to believe that 2015 will be a year of digital infrastructure. Broadly speaking this should include cloud, middleware and security, for most large enterprises. Of these, security has been much in the spotlight of late, with Sony obviously being the most high-profile victim. But arguably, despite the political intrigue and the alleged involvement of North Korea, the hacking of the US Central Command should be more akward, geopolitically speaking. This list of famous hacks from The Telegraph has some fascinating nuggets. From the unintentional Morris worm (Morris is now a professor at MIT), to the Target and Sony Hacks of the last 12 months. Two trends stand out. The first is the increasingly political colour of the hacks – indicating that this is now a serious form of warfare or international espionage. The second is the simplicity of many of these hacks. DDOS, phishing, these aren’t particularly sophisticated attacks, but they indicate that as humans we often represent the threats and weak links in the security environments of our organisations.

The HBR carried this great example of the success of Nordstrom’s digital strategy. I think all success stories tend to get over-simplified to an impractical level, in our hunt to find an easy formula. Usually there are dozens, if not hundreds of things that need to go right for a major project to work well, and it only takes a few to not work well, for it to be a limited result or an outright failure. This is why we have many more failures than successes of course. So while I agree about the arguments in this piece, I would hesitate to consider this as a necessary and sufficient condition for digital success. Nordstrom’s strategy comprises of a focus on customer experience, and the extensive use of digital (SMACIT) tools across the length and breadth of the business, to effectively create a new business model. As always, both God and the devil lie in the details.

And what should we make about Google’s change of tack on Google glass? It was initially interpreted as Google pulling the plug on a venture with mixed success, which it has a history of doing. But it seems apparent now that Google are taking a leaf out of Apple’s book and going design-first. By handing this product to Tony Faddel, of Nest and iPod fame, Google seem to be acknowledging that the technology (which works) needs to be nested inside a highly usable, and ideally beautiful product. This is hardly a revelation but if this is indeed the thinking, then it’s wonderful to see Google, the spiritual home of engineers, acknowledge the role of design and user experience.

Also, at CES, there was much buzz about more wearables – watches from Sony and HTC, and other devices. Smart watches look like being the wearable de l’annee, but the hunt for the killer app is still on. Any guesses? What would you use a smart watch for? What problem could you solve? Or what wonderful new benefit could you imagine? Like many others now, I don’t wear a watch to being with, so it would have to be a compelling benefit to make me wear a watch again (one more device to manage!).

It would be remiss of to not mention this video from Ola Cabs in India which a colleague kindly sent me. It’s refreshing to see such a stark focus on user experience from an engineering point of view, rather than design alone. Anybody looking to build a product should see this.

And finally, on a lighter note, this set of maps, yet another example of the emotive power of data in our lives, my favourite is the first map, on second languages spoken in the boroughs of London. Amongst other things, it shows you the patterns of immigration and the abundance of Indian and Polish people in London. May be there needs to be a new alliance for the IPOs (people of Indian and Polish Origins) a microcosm of a geo-political shift, a trading block and a platform for cultural enrichment hitherto overlooked. I mean, all this technology, data and understanding should bring us closer, right?

Internet of Things – Hype & Hope

(I had the privilege of speaking about IOT at the Oxford Technology and Media forum yesterday. What follows is the gist of my session and some thoughts from the panel discussion)

The tech industry is often guilty of pushing technology solutions to consumer without focusing on the benefits, the emotions and simplicity. Invariably, businesses that get it, do better at selling tech to consumers. Apple are clearly the masters at it, but UK customers will know that after many years of ‘interactive television’ discussions, what customers bought were ‘sky plus’ and ‘red button services’. (The technology didn’t actually deliver on the promise, but that’s a different story).

So we come to the Internet of Things and I believe, we’ve swung to a different end of the pendulum. We’ve created a pithy, catchy phrase, something that everybody can relate to and not be daunted by the jargon. I would personally have preferred the internet of stuff (stuff is cooler than things). But the internet of things means (pardon the expression) bugger-all when it comes to actually buying, implementing or solving something.

Maybe I’m being harsh. It’s a catch-all word conveying a general wave of technologies much like “digital convergence” in the broadcast and comms space. But it’s a very loaded phrase and masks many layers of complexity that haven’t yet been resolved to the point where they can be implemented. Or even understood by the consumer.

The IOT includes communication between machines, between people and machines, and also between people and people via machines. It includes wearables, and all manners of sensors, and an ever increasing ocean of data, an implicit assumption of an economically viable, reliable and available network. And so far, very few standards.

After all, we’re all spoilt by the Internet – in the world of standards driven browsers, we only had to worry about the browser environment. The most complex questions in the early days of the web included ‘web safe’ colours. And later, pushing the limits of HTML. You never had to think about the OS, the device (are you viewing the website on a Dell or IBM laptop?) You didn’t have to think about whether the user was sitting or standing or walking around. And all you had to know was a URL, and the internet would find the website from over 50 million computers in a fraction of a second. Even transactions and ecommerce are now taken for granted. 

In the IOT world, all these are non-standard and have to be thought from scratch. What’s the user interface of a ‘thing’? If it’s a sensor on a coffee machine vs a door, how should we access the data, how can interact with the thing? The design challenge moves from an ‘interface’ design to an experience and even environment design. Who designs the experience of walking into a retail store which is armed with iBeacons or other sensors? Design challenge will range from fitting an antenna while managing heat dissipation, to figuring out how to retail product aesthetics while adding a bunch of tech.

Service design has been a term in vogue for a few months now, but is fundamental to the creation of IOT models. We must take a design centric view and build from there. That’s the only way we’ll get around to focusing on the right problems to solve, to ensure adoption.

As with all emerging technologies, we’re in the world of ‘compound change’ – where each layer builds on previous layers, and so it creates an exponential change curve, which is near impossible for us to predict, since we’re still very used to thinking in linear terms. What is intuitive to me, is that we’ll get entirely new companies dominating the IOT space, in the way that FB, LinkedIn and Twitter dominate the social sphere, and Google and Amazon dominate the web, Apple and Samsung dominate mobile devices and Microsoft and Intel dominated the Desktop world.

Because, this will take a whole new business model. It will shift value, destroy old models and create entirely new services. Most often, we think of new tech as better ways of doing what we do today. So the ‘better’ model leads us to thinking about how our fridge will tell us when it’s out of milk. Rather than ‘different’ models – perhaps our fridge telling us which of the foods we’re storing has the earliest use-by date, so we can modify our consumption appropriately. Or other more imaginative and useful behaviours.

Undoubtedly the way in which business models will evolve will involve adding layers of services to existing and new products. The value of the service will outstrip the value of the product. You may pay more for the service of tracking your weight and the feedback on your lifestyle and diet, than you do for the weighing scale itself. In fact asset ownership models may change, with companies willing to give you the asset for free in order to lock you into the service, or simply, follow an asset leasing model, which brings down your outlay but enables longer term revenue stream for the seller. Soon we should be able to view this information and services layer explicitly and this explicit-isation of the service and information layer may be one of the biggest sources of consumer value in the IOT. This would enable us to understand better the total cost of any product (say a sweater, or a vaccuum cleaner) and make different choices on that basis. It would also align value realisation with costs – imagine a washing machine which you lease and pay per use.

Although it’s tempting to consider just the things we acquire and own, there are all those things we use, which form the asset base for service delivery, from smart meters, to hotel rooms and railway stations to rented cars. These can all also follow the same principles of creating explicit service and information layers, so that maintenance, usage, and cost and value can all be tracked more easily. Then you have natural resource and public environments – weather, floods, pollution tracking, and more.

As has been noted, it is almost impossible to talk about IOT and emerging technology of any kind without talking about data, privacy and security. I used to think, like everybody else, about a data brokerage, or info-mediary. Now I think data-brokerage should be a feature built into every product. A data brokerage module will ensure that consumers data is stored, transacted and valued in a way that is fair to both sides, and in a transparent manner. Really, you can’t ask for more than that.

Undoubtedly the IOT is a big deal. We’re talking about billions of connected devices changing the way we live our everyday lives. The transformativer potential of this can barely be imagined. I just hope we use this to solve some of the bigger problems we face – the energy crisis, caring for an ageing population, getting supplies more efficiently to the needy, across the world. And not spending too much time debating whether our kettle should gossip with our washing machine.

Digital Transformation: From TOM to EOM

TOM / EOM – sounds like a soup you might order. But for the purpose of this discussion, put your appetite to one side, and think about Digital Transformation. 

 

TOM or the Target Operating Model is the staple of the consulting framework in transformation environments. The logic being, you have an initial operating model and you enter a transitional phase, driven by internal and external change, and you emerge with a new “target” operating model. It’s an excellent construct and very useful for delivering change. 

 

In the digital arena, though the idea of the Target Operating Model is challenged because of a number of reasons. 

 

Critically, it assumes that the change is a finite and one time activity. This is no longer true. Consider the landscape today. You enter a phase of virtualisation of your servers and networks, and before you finish that you’re in the middle of the mobility revolution. You combine cloud and mobility to create another transformation and everybody is talking about big data and social analytics. And then there’s the Internet of things, machine two machine and smart environments waiting to happen. So which points do you pick as the start and end of the change? And if you took this whole set as one change, would you even survive it?

 

And then, if the change is not a finite or a single event, what do you assume as your end state or ‘target’ environment? And if there is no target environment you can define, how can you create a target operating model? Would it not be outdated even as you were implementing it? 

 

There could be an argument that these individual technology waves do not affect the business model and are just technology changes. I would disagree with that. Yes, moving from one vendor to another, or upgrading from version n to n+1 is a technology change, though even those projects need to be seen as business change projects. But the waves of technology I called out earlier – from Cloud, to Mobile, to IOT are all pretty fundamental shifts – often creating deep changes in business models. 

 

To add to these problems, as this article in the Forbes highlights, many organisations undertake digital transformation without actually knowing what it is. Many don’t really understand the transformation, many others just see it as platform upgrades. 

 

So here’s the bad news, your digital transformation project is not a one time exercise, there is no target environment and so your target operating model may be in need of an update by the time it’s bedded in. 

 

The likely scenario is that there will be multiple waves of transformation. And here onwards they will all be digital (or at least until we come up with a new word). 

 

Which leads me to my proposition – that perhaps the right way to think about this is as an Evolving Operating Model, rather than a Target Operating Model. 

 

What would be the key features of an evolving operating model? Here are three key ones, though there may well be more. 

 

Building a change capability – at the core of this is the creation of a Culture of change adaptability. I’ve consulted for many organisations where the smallest change has to be handled with kid-gloves and is a source of anxiety and organisational stress. These are all big changes we’re talking about, so there’s a lot of work to be done to make people change friendly. This should ideally be reflected in contracts with employees. HR needs to take a leading role here and ep build a culture of change through awareness, education, self-empowerment and counselling. At the same time, leadership needs to invest by ensuring the right people are chosen and then given the time to grow into this change culture. Based on my experience, there are parts of the world, such as Europe, where this would be a harder process than, say, in Asia. European business cultures are much more rigid about roles and function, and these are often defended by regulation. Also, in Europe, there is often a much higher premium on matching exact experience to a role, rather than bet on adaptability. One of the ways to address this is to balance the majority of such fixed role people with a handful of adaptors – people who can foster a pro-change environment within the business. 

 

For example, I met a European company in the travel segment who could not even change business rules in their enterprise apps, or implement a mobile app store without validating the decisions with worker councils. 

 

Funding Change: Not a capital expense but the cost of doing business: Build in the cost of change into your cost of running the business. Rather than the one hit capital expense of a digital transformation project, budget for change annually, that LOBs and divisions can draw from, with the right checks and balances to ensure governance is provided. There is every likelihood that each of the next five years will require significant changes to some part of your business or the other. Rather than running it as a giant centralised project, or leaving this to individual departments and LOB’s who may not value this investment, organisations should explore creating an investment bucket which is made available to teams based on their justification, against a stated vision. But this investment is locked down for change efforts and cannot be used for other purposes. 

 

Earlier this year, the BBC announced a program of saving £48m and reinvesting at least £29m of that into Digital Transformation services across channels, mobile and digital journalism. Cooperative Bank had set aside £500m on IT alone, to enable it’s digital transformation. Your budgets may be comparable to BBC, or Cooperative Bank, but in all probability they represent significant amounts of money. 

 

The big bang approach assumes that one large and hugely diverse project is the best way of optimising the way this budget is spent. Reality may be very different. 

 

Instrument your company: Build an instrumented organisation where process change can be systemised easily, using BPM, middleware, SOA, and other architectural approaches. This is fundamental in order to plan, implement and measure change. For example, if you want to change your mobile customer service layer, with new processes without necessarily having to make big changes in your CRM or ERP systems, you need a decoupled approach that will allow you to modify or even replace your mobile front end without always having to change a legacy application. But also, it will be faster and quicker to implement a new process if the systems can change quickly, rather than become a symbol of the organisational inertia. 

 

A good analogy and one you hear often in business discussions is about turning the tanker. We talk about large businesses being like large tankers – hard to turn. But your digital transformation should not be seen as that one awkward turn. It’s more like suddenly being in an environment where you will need to turn and often. The real challenge here is actually, how do you stop behaving like a hard to turn tanker?