2016/2017 Shifting Battlegrounds and Cautious Predictions for Digital

Innovation slows down in mobile devices but ramps up in bio-engineering. Voice goes mainstream as an interface. Smart environments and under the hood network and toolkit evolution continues apace.

For most people I know, 2016 has ranged between weird and disastrous. But how was it for the evolution of the digital market?

The iPhone lifecycle has arguably defined the current hypergrowth phase of the digital market. So it’s probably a good place to start. In the post Steve Jobs world, it was always going to be a question about how innovative and forward thinking Apple would be. So far, the answer is not very. 2016 was an underwhelming world for iPhone hardware (though Apple has tried harder with MacBooks). Meanwhile, Samsung which you suspect has flourished so far by steadfastly aping Apple, ironically finds itself rudderless after the passing of Steve Jobs. It’s initial attempts at leapfrogging Apple have been nothing short of disastrous with the catastrophic performance of the new inflammable Note phones/ batteries. Google’s Pixel Phone could hardly have been timed better. By all initial accounts (I’m yet to see the phone myself) it’s comparable but not superior to an iPhone 7, Google’s wider range of services and software could help it make inroads into the Apple market. Especially given the overwhelming dominance of Android in the global OS market. The market has also opened up for One Plus, Xaomi and others to challenge for market share even in the west. Overall, I expect the innovation battleground to move away from mobile devices in 2017.

While on digital devices, things have been quite on the Internet of things front. There have been no major IOT consumer grade apps which have taken the world by storm. There have been a few smart home products, but no individual app or product stands out for me. As you’ll see from this list – plenty if ‘interesting…’ but not enough ‘wow’. I was personally impressed by the platform capabilities of enabling IOT applications, form companies such as Salesforce, which allow easy stringing together of logic and events to create IOT experiences, using a low code environment.

AR and VR have collectively been in the news a lot, without actually having breakthrough moment. Thanks to the increasing sophistication of VR apps and interfaces, with Google Cardboard and the steady maturing of the space. But the most exciting and emotive part of AR / VR has been the hololens and holoportation concepts from Microsoft – these are potentially game changing applications if they can be provided at mass scale, at an affordable cost point and if they an enable open standards for 3rd parties to build on and integrate.

Wearables have had a quiet-ish year. Google Glass has been on a hiatus. The Apple Watch is very prominent at Apple stores but not ubiquitous yet. It’s key competitor – Pebble – shut shop this year. Fitbits are now commonplace but hardly revolutionary beyond the increasing levels of fitness consciousness in the world today. There are still no amazing smart t-shirts or trainers.

The most interesting digital device of 2016 though, has been the Amazon Echo. First, it’s a whole new category. It isn’t an adaptation or a next generation of an existing product. It’s a standalone device (or a set of them) that can perform a number of tasks. Second, it’s powered almost entirely by voice commands “Alexa, can you play Winter Wonderland by Bob Dylan?”, third, and interestingly it comes from Amazon, for whom this represents a new foray beyond commerce and content. Echo has the potential to become a very powerful platform for apps that power our lives, and voice may well be the interface of the future. I can see a time the voice recognition platform of Echo (or other similar devices) may be used for identity and security, replace phone conversations, or also become a powerful tool for healthcare and providing support for the elderly.

Behind the scenes through there have been plenty of action over the year. AI has been a steady winner in 2016. IBM’s Watson added a feather to it’s cap by creating a movie trailer. But away from the spotlight, it has been working on gene research, making cars safer, and even helping fight cancer. But equally, open source software and the stuff that goes behind the websites and services we use every day have grown in leaps and bounds. Containerisation and Docker may not be everybody’s cup of tea but ask any developer about Docker and watch them go misty eyed. The evolution of micro services architecture and the maturing of APIs are also contributing to the seamless service delivery that we take for granted when we connect disparate services and providers together to order Uber cabs via the Amazon Echo, or use clever service integrators like Zapier

All of this is held together by increasing focus on design thinking which ensures that technology for the sake of tech does not lead us down blind alleys. Design thinking is definitely enjoying its moment in the sun. But I was also impressed by this video by Erika Hall that urges us to go beyond just asking users or observing them, and being additionally driven by a goal and philosophy.

2016 has also seen the fall of a few icons. Marisa Meyers has had a year to forget, at Yahoo. Others who we wanted to succeed but who turned out to have feet of clay, included Elizabeth Holmes at Theranos, and the continued signs of systemic ethical failure at Volkswagen. I further see 2016 as the year when external hard drives will become pointless. As wifi gets better, and cloud services get more reliable, our need to have a local back up will vanish. Especially as most external drives tend to underperform over a 3-5 year period. Of course, 2016 was the year of the echo-chamber – a reminder that social media left to itself insulates us from reality. It was a year when we were our worst enemies. Even through it was the Russians who ‘Hacked’ the US elections and the encryption debate raged on.

One of the most interesting talks I attended this year was as the IIM Alumnus meeting in London, where a senior scientist from GSK talked about their alternative approach to tackling long term conditions. This research initiative is eschewing the traditional ‘chemical’ based approach which works on the basis that the whole body gets exposed to the medication but only the targeted organ responds. This is a ‘blunt instrument’. Instead, the new approach takes an ‘bio-electronic’ approach. Galvani Bioelectronics, set up in partnership with Alphabet will use an electronic approach to target individual nerves and control the impulses they send to the affected organ, say the pancreas, for diabetes patients. This will be done through nanotechnology and by inserting a ‘rice grain’ sized chip via keyhole surgery. A successful administration of this medicine will ensure that the patient no longer has to worry about taking pills on time, or even monitoring the insulin levels, as the nano-device will do both and send results to an external database.

Biotech apart, it was a year when Google continued to reorganise itself around Alphabet. When Twitter found itself with it’s back to the wall. When Apple pondered about life beyond Jobs. Microsoft emerged from it’s ashes, and when Amazon grew ever stronger. As we step into 2017, I find it amazing that there are driverless cars now driving about on the roads, in at least one city, albeit still in testing. That we are on the verge of re-engineering the human body and brain. I have been to any number of awesome conferences and the question that always strikes me is, why aren’t we focusing our best brains and keenest technology on the worlds greatest problems. And I’m hopeful that 2017 will see this come to fruition in ways we can’t even imagine yet.

Here are 5 predictions for 2017. (Or around this time next year, more egg on my face!)

  • Apple needs some magic – where will they find it from? They haven’t set the world alight with the watch or the phone in 2016. The new MacBook Pro has some interesting features, but not world beaters yet. There are rumblings about cars, but it feels like Apple’s innovation now comes from software rather than hardware. I’m not expecting a path breaking new product from Apple but I’m expecting them to become stronger on platforms – including HomeKit, HealthKit and to seeing much more of Apple in the workplace.
  • Microsoft has a potential diamond in LinkedIn, if it can get the platform reorganised to drive more value for its, beyond job searches. Multi-layered network management, publishing sophistication, and tighter integration with the digital workplace is an obvious starting point. Microsoft has a spotted history of acquisitions, but there’s real value here, and I’m hoping Microsoft can get this right. Talking about Microsoft, I expect more excitement around Hololens and VR based communication.
  • I definitely expect more from Amazon and for the industry to collectively start recognising Amazon as an Innovation leader and held in the same esteem as Apple and Google. Although, like Apple, Amazon will at some point need stars beyond Bezos and a succession plan.
  • Healthcare, biotechnology, genetics – I expect this broad area of human-technology to get a lot of focus in 2017 and I’m hoping to see a lot more news and breakthroughs in how we engineer ourselves.
  • As a recent convert, I’m probably guilty of a lot of bias when I pump for voice. Recency effect, self referencing, emotional response over rational – yes all of the above. Voice is definitely going to be a big part of the interface mix going forward. In 2017, I see voice becoming much more central to the interface and apps planning. How long before we can bank via Amazon Echo?

Happy 2017!

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The Future of Retail: How Will You Fight Amazon?

What to do when the elephant in the room is a 600-pound gorilla?

digital-retail

Once upon a time, there were 4 high street electronic retailers. Now, they are one. Dixons Carphone, which also includes PCWorld and Currys, now employs some 42,000 people and manages 17 brands across Europe. Yet, while the company continues to innovate and do a lot of the things you would expect from a leading retailer, they are fighting a very different kind of opponent. Like the movie Predator, this is an almost invisible creature, capable of superhuman strength, focus, and accuracy. This is Amazon.

It’s not just retail, the story is repeating itself in other segments too. In some cases, the commercial model has changed as well – for high street music retailers, see Apple and Spotify. For Blockbusters, it’s Netflix. But for most categories, such as for Book chains like Borders, its still Amazon. And given Amazon’s relentless strategy of growth and customer intimacy before profits, its the question every retailer must ask – how to compete with Amazon?

Everyone knows a few legends about Amazon. Many are about the maniacal customer focus – how Jeff Bezos and his family spent Christmas packing gifts by hand. Or how, when asked about why Analysts weren’t buying his stock, he said that as long as customers were buying his products, he didn’t care if analysts bought the stock. The fact is that Amazon is the 600-pound gorilla in the retail business. In 2015. 50% of all e-commerce growth in the US went to Amazon.

What lies behind Amazon’s relentless growth? A combination of the obvious and perhaps less obvious. Global distribution centres, world leading warehouse automation, customer experience par excellence, recommendation engines, one-click purchasing. Kindle readers, prime membership, all you can eat subscriptions. All of this is known and well documented. But there are three key areas where perhaps less attention is paid.

First, Amazon is arguably the worlds most effective innovation company. Its string of relevant and successful innovations from automated warehouses to Amazon Echo, speak for themselves. Second: Amazon deeply understands what it means to be truly committed to an excellent customer experience – and they execute this across payments, site design, offers, delivery, and returns. Third, and most importantly it’s a digital native company. This means that all its core processes are run by software and algorithms, rather than people. Software behaves more consistently, doesn’t suffer fatigue or human errors, and can be improved relatively easily, compared to upskilling humans. Amazon can decide where to introduce human intervention rather than worry about where to automate.

Quite a few brick and mortar businesses have enjoyed success in the past decade, in the UK, through differing strategies. Tesco’s rise and fall with the Dunnhumby data business have been well documented. John Lewis continues to focus on customer service delivered via its partnership model. Halfords focuses on the cycling and travel niche. Each of these businesses will face the same Amazon question and have to figure out how to compete, especially if Amazon decides to open physical stores in future.

So How Should Brick & Mortar Stores Fight Amazon? Here’s a starting 5 point list:

  1. Dominate your segment – make sure that you define a sustainable market (e.g. kitchenware in the UK) and can be the dominant brick and mortar store in that segment, or as consolidation sets in, the last one standing.
  2. Build a strong digital proposition – one that spans the web and mobile, both deeply integrated into your business model. make sure you invest both in digital marketing and in your e-commerce platform. Exploit online communities and design around customer needs.
  3. Build powerful experiences which cannot be created online. Tactile, immersive and human experiences, which can exploit your physical store. You may redesign significant parts of your physical store and even allow customers to comparison shop and complete the purchase online, in some cases.
  4. Bring your physical and digital retail universes together – and ensure that this omnichannel experience becomes a source of data for sharpening your customer experience, in addition to contributing to your sales and profits.
  5. Automate your core processes – from merchandising, offers, check out, payment, delivery and returns, and then focus specifically on where human inputs will improve the process. Invest in developing algorithms that are valuable to your business.

Of course, this is only a beginning and you’ll need to keep investing and building competence in any number of new areas. Some that spring to mind include: trust models, building strong data stewardship, creating a lifetime value of customers, providing technical support for the increasingly smart products you’re likely to be stocking, creating new commercial models – perhaps around the idea of leasing or renting rather than outright purchase, understanding immediacy and real-time business models, advanced security modelling, designing of smart experiences, and deep supply chain visibility – these are just some of the areas you will want to ensure you understand well.

We should also expect to see other market patterns emerge – for example, corner shops/ convenience stores could be pulled together with a common platform which allows them to run independently but provide a shared platform for online & mobile ordering, stocking, supply chain and even leasing drones for delivery. After all, you would go to your corner shop when you need something quickly – when your sugar runs out, in the middle of making tea, for example. What better way for them to deliver to these urgent needs by having drones drop a packet of sugar to your doorstep even before you finish making the tea?

Because of course, if corner shops won’t do it, and the high street groceries dilly dally, this is something Amazon are already planning to do. And frankly, as a consumer, I’ll go to whoever meets my needs in the most painless way.

The Missing Pieces of Innovation

I realised something very important while I was a the innovation event organised by EditorEye at the General Assembly recently. It became clearer to me why, despite spending a lot of time and effort on innovation and hiring some excellent people, organisations are still struggling to get the results out of innovation. The speakers at the event, by the way, were all very good and were all covered the topic extensively. But there are some aspects of innovation which are simply not talked about, while others get a lot of focus, as I’ll show you later in this piece.

innovation

But the problem, I believe starts at the root. What is innovation? You can get as many definitions as there are people in the room. Is it new product development? Is it new ideas? Is it creativity? Is it bringing ideas to market? My definition is simple – it’s doing more with less. If it takes 100 units of resources to solve a problem, and you figure out a way of doing it with 80, that’s innovation. We can debate this later, but let me ask you a different question. Is all product development innovation?

Let’s suppose you are an insurance company and you figure out that increasingly there are older people whose lives depend extensively on technology. You survey the market, and you create a new product which looks at a comprehensive technology devices cover for this audience. You create an app and website for it, which is designed to be used by older people – simpler interfaces, larger fonts, etc. You spend time with prospective customers to understand their specific behaviour and problems and design your product to deliver their key unarticulated needs. Your product is a success. Was this an example of innovation? Let’s assume this product was prototyped in your ‘innovation lab’ which has been set up for bringing such new products to market. Still, is it innovation? Which part of this is innovative, given that all these processes are now standard practice for product development? It may be an excellent example of product development, but I repeat, is it really innovation?

Similarly, you might argue, is every successful advertising campaign ‘innovative’? Is every market research that delivers customer insight an act of innovation? What about a new business, or start up? The reality is that you’re perfectly justified in saying yes to all of these questions. And if your innovation lab delivers successful products, then surely it’s justified, irrespective of what you call it. And I’m not disagreeing with that.

However, to miss the point of innovation is also to walk away from a lot of value. Let’s suppose the typical new insurance product costs £2m to develop and test and £10m to market, hypothetically speaking. Let’s say that the numbers here represent the comprehensive resource cost, and not just actual cash outflows. Now if your new product took about the same, and was averagely successful, you’re at par. But what if you could deliver similar success with 20% investment? Or much better returns? And what if you could build a methodology for doing this consistently? That’s innovation! That means you can deliver more for less and on a consistent basis.

Most organisations look at innovation as a way of delivering new products, or new businesses. It’s also common to look at it as a process that follows a standard path: brainstorm ideas, prototype in a lab and then scale through the organisation. I challenge both of these premises. First, looking at innovation as an idea to market process limits our thinking. Innovation needs to be seen as a problem solving methodology. And specifically, a methodology that looks to improve on the expected resource requirement for solving the problem. And to the second, if everybody is replicating this model, then it stops being innovative. Not that it becomes less valuable if the new products work. But the reality is that most innovation initiatives in most companies don’t lead to success. And wouldn’t it be great if we could increase the success rate?

My model of innovation therefore starts earlier, with Problem Definition. If you’re thinking of a new product, why? Is it to ensure coverage of the market? is it opportunistic? Do you believe that there will decline in current products & revenues? Is it a strategic response to competition? Do you feel you underserve the market? Is the problem financial – your return on capital is too low and you’d like to improve this? Are you missing out on more profitable customers or a growing segment? As you can see there are many, many ways of framing your new product development effort and the problem you’re trying to solve may vary significantly. 3M for example, has a commitment to drive 30% of revenues from ‘new products’ – i.e. those built in the last 4 years. For a pharmaceutical company a new product that better addresses a disease or a family of problems, is a protectable revenue stream that can run for over a decade, even as older revenues decline through patent expiration. Whereas Google (Alphabet) just wants to solve bigger problems. That allows it to be mission driven but even there, for example there are specific problems. Arthur Levinson, ex CEO of Genentech leads a platform in Alphabet to combat ageing. Whereas in the new famous example of British Cycling, the marginal innovations are aimed at driving higher performance, and nothing to do with a product at all. This is where we step away from product development and recognise that innovation is a methodology for solving any problem in a ‘do more for less’ way, not just product development. To do this well, try approaching this problem as at least two out of a CFO, a CEO and a head of Operations, or Marketing. Or apply design thinking principles to see how the people impacted by this problem think about it. This award winning redesign of the ambulance started by looking at the ambulance as an extension of the hospital, and the start of the medical process, rather than just a form of transportation to the hospital. Kees Dorst’s book ‘Frame Innovation’ is a good starting point for thinking about problem framing.

The next step is the Research and Baselining phase, so we know what benchmark we’re trying to beat. It is likely that your ambitions are not at the same scale as Google’s (or Alphabet’s), Amazon or Elon Musk’s. In fact you may just be looking to solve an punctuality problem in your department in a way that nobody in your company has done yet. If you define your context as your company, department, industry or the world, you can accordingly set your benchmarks. This is critical because what’s innovative for a government agency (say agile development) could be very old hat for a Silicon Valley company. But this my second key point. Innovation is surely about being different, and not replicating a tried and tested method. So you need to clearly set out what you’re going to do differently (better!) from other similar efforts, before you start. It’s worth noting that of the 5 stages, this gets the least amount of attention because it’s probably the least sexy part of innovation. But it could save you a lot of effort and also dramatically sharpen the subsequent phases. In fact, often, you will be able to find a lot of examples workable ideas in other industries and organisations. No better example of this than the Great Ormond Street Hospital for children learning from Formula 1 pit stops, about swift handovers from surgery to intensive care. This represents a huge reduction of risk, in the innovation journey.

It’s only once you’ve done stages 1 and 2 that you should then get to the Creative Spark stage. For most organisations, this equates to a brainstorming exercise. One of the biggest mistakes in the area of innovation is that people jump into brainstorming with a loosely defined problem and no benchmark. To make it worse, you then get a lot of people with very little knowledge of the context of the problem state coming up with ideas many of which clearly won’t work. I know of a company which was keen to ‘pitch’ ideas to Transport for London. They ran a competition internally, generated hundreds of ideas, evaluated them and drew up a short list of 10. But the brainstorm was run with a global team, not based in London, and consequently many of the ideas, such as mobile app based solutions for contactless ticketing did not factor in the actual challenges of rush hour volumes, or the speed of response required. Besides, many of the ideas were already at play at TFL, which hadn’t been researched well enough. Running pure-play brainstorms is also of limited use if the team doesn’t have enough context of the problem. You can’t brainstorm ways of improving care pathways in the NHS, or supply chains for broadcast equipment, if you don’t know much about them, or the problems they face. There are, however, plenty of techniques for running more effective brainstorms and idea sessions. Additionally, there are other ways apart from brainstorming for the creative spark phase. Best results are often achieved through having creative people in the mix along with experts, or building unpredictability into the process. Tim Harford’s book ‘Messy’ suggests some excellent ways in which this happens.

Once you have ideas you want to take forward, you can then push them through the Innovation Lab stage. Of the 5 phases of this methodology, this is the one most organisations have invested in already and are doing with a lot of focus. Setting up a lab environment, running ‘Google sprints’, ensuring that small teams turn around quick prototypes, building design thinking into the mix and fusing the efforts of creative technologists with deep experts, a lot of companies are able to do a reasonably good job of taking new ideas through a laboratory process to an MVP stage. When I was working at Cognizant, in 2015 we conducted a quick research of ‘innovation labs’ and were not surprised to find that an overwhelming majority of leading banks and retailers already had an innovation lab of some kind. If you haven’t yet been exposed to or been a part of an exercise like this, grab hold of ‘Sprint’ by Jake Knap et al.

But even that is not enough because a lot of initiatives can fail even after lab success. Be they new products or internally facing solutions. Scaling innovation is fraught with risk, and even Google is famous for the number of initiative it has killed after promising starts. This is the key reason that many organisations prefer to buy in the finished product rather than try to build it in house. What the newly created and lab-tested idea needs is not just organisational support, but often a network in which to flourish. The best results are created when the new idea has a life of it’s own and is allowed to grow and morph independently, not simply scale to a larger replica of it’s initial form. The perfect baby needs to grow into a healthy human adult, not a full sized replica of the baby. Most businesses are unable to provide this kind of sustaining network. Steven Johnson’s excellent book ‘Where Good Ideas Come From’ beautifully elucidates this idea of a sustaining networks. When GE set up it’s fledgling IOT business in Silicon Valley, it was not just allowing it to flourish outside of the corporate headquarters, but also allowing it to sustain and nourish itself in a high tech network. In organisations such as Google and 3M, there isn’t a small and tightly defined number of ideas being pipelined to the market, there is a huge internal innovation network, where dozens or even hundreds of ideas feed off each other, combine and morph on their way to a handful becoming successful products. If it’s new product and new business development that defines innovation for you, then you could do well to keep at hand the Innovators Solution, by Clayton Christiansen.

innovation-methodology

This is just the tip of the iceberg, in a way. Innovation is hard work, and much of it is done away from the public eye, and the adulation of success. But more importantly, innovation is a methodology, which when applied, dramatically improves your ability to problem solve in a way that is ahead of the competition.

3 Easy Ways to Boost Your Mobile Strategy

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It’s 2016 and almost a decade since Steve Jobs put a ding in the universe with the launch of the first iPhone. A significant part of my life in that time has been spent in delivering better business outcomes using mobile technologies. And as the iPhone 7 blinks it’s baby eyes at the world, here are some of the things I’ve learnt about mobile strategies. (If you’re wondering whether business should have a mobile strategy or just a business strategy, let me just suggest that you need to have a clear roadmap and strategy for how you’re going to exploit the mobile ecosystem. What you call it is up to you!). Assuming you are a progressive organisation, I would expect to see the following three things happening in your business:

It’s NOT a marketing problem: There has been a historical tendency to look towards the CMO when we think about mobile solutions. But people who make the investment of effort, time and attention, to download the your app are usually your existing customers, looking to make it easier to deal with you. These are the also committed customers who are self-selecting and need to be recognized and rewarded. This goes to the heart of your customer retention, cross & upsell and will directly impact your cost of servicing customers. When I was working for a major European airport we knew that the airport didn’t have a direct relationship with travellers, nor much data about the millions of people using the airport, yet there was a prevailing school of thought that the mobile website was good enough, and there was no business case for upgrading the mobile app. For any frequent user of a service, logging into a website every time is a nightmare. This is an operational and cost of servicing issue. Customer experience, after all, is a COO problem really. This is even more true as employee apps take centre stage. So if your COO and head of Channels aren’t involved and sponsoring your mobile strategy it might be time to rethink.

The New New Stack: A Whole New Architecture: In the last few years there have been a very quick turnover of the preferred ways for building mobile apps. You only have to look at the rate of change of Gartner terminology – from MCAP to MEAP to MADP as the flavour of the month. Cut to today and none of those are preferred options anymore. The axis has shifted again. Most apps are being built today on light-weight front-end tools involving some flavour of Angular with loose coupling to the back end via APIs. A word on API management is worthwhile here. As a manager, you don’t need to know about SOAP or REST but think about this as a much more modular setup, where the API layer simply pushes information out in a governed manner to whichever channel requires it – be it the mobile app, the website or a partner.

To get a sense of how valuable the API layer has become consider that Apigee have recently been bought by Google. Mashery, another API management platform was first bought by Intel and then acquired from Intel by Tibco. Other majors including IBM and CA have their own solutions in the space. APIs themselves are not new but the way they are written now and the platform through which they are managed and governed are relatively new and you’re missing a trick if your business lacks an API strategy.

There are also a number of low-code or no-code platforms. Fliplet, for example, allows you to build simple, and functional mobile apps with little or no coding. Of course, this doesn’t include scenarios where you need to connect to other systems or consume APIs. But even those can be added with relatively low effort. In the Business to Employee world which is defined by a number of micro-applications, this is a very good option.

Exploit New Behaviours: New Technologies often engender new behaviours. Probably one of the most salient in recent times is the swipe left/ swipe right behaviour that was made popular by dating apps like Tinder. Understanding these behaviour patterns and using them is key to reducing friction for your processes. Another new ‘behaviour’ is the mobile only customer behaviour – i.e. somebody who would rather transact only on the mobile device. Uber is a very good example of how massive this can be, but you will definitely see customers in future at both ends of the age spectrum, whose only device is a mobile device rather than a laptop.

What new behaviours will we become used to over the next 5 years? Will it be the invisible payment mode of Uber? The voice interface of Amazon Echo/ Alexa? Or will we find more ways of self-quantification for our personal and professional lives? The good news is that you don’t have to create new behaviours. You just need to keep abreast of them and ensure you’re able to exploit them.

The Unbearable Bigness Of Data

(And What We Should Be Doing About It)

Big-data


Welcome to the Data Deluge.  

By now you’ve probably gotten sick of hearing about big data, little data, fat data, thin data and all manner of data. You’ve gotten your head around Terabytes, Exabytes and Zetabytes. You’ve noted that the price of data has crashed by 90% over the past few years on a per unit basis. Your CIO has mastered Hadoop and MongoDB and you understand the benefits of data lakes over, say, data puddles. The scary part of all of this is that we’re still in the early days of the data deluge. We are hurtling into a quantified universe fed by smart cities, homes and cars; platform driven models and clickstream driven relationships. In fact, I was having coffee this morning with the well travelled, well informed, and always insightful John McCarthy from Forrester, and we were positing that in a few years from now, data will take over from ‘Digital’ as the centrepiece of the organisational transformation and focus across the world.

Right now, though, we’re caught in a deluge with no real clarity about how we’re going to actually use all the data that’s floating around. And here are three key challenges we’re going to have to deal with:

What, not Why – A New Mindset

A question I often ask my colleagues who are experts in data sciences is as follows: let’s suppose that when it rains, people drink more cappuccinos. Now, if Starbucks knew this, it could advertise or promote cappuccinos every time it rained. It could even launch branded umbrellas. But how would it discover this? Historically, the story would be one of a smart store manager who one day realises that rainy days increases his cappuccino sales, and having defined the premise, starts to collect the data to validate his hypothesis. Or even more traditionally, Costa Coffee runs focused groups, and the link between weather and coffee preferences is established. Critically, a qualitative hypothesis would be at the front of the process and data collection would follow. Because, how else would we know if it’s the rainfall or the pollen count or indeed, the volume of traffic on the roads that we should be correlating coffee sales with?

In the new world of data, or ‘big data’, this works the other way around. A brand like Caffe Nero could take all their sales data across the world, and run hundreds or thousands of analyses, searching for correlation, with any number of external and easily accessible data sources. This includes the obvious ones such as weather, or transport, but also for example days of week or month, time of day, and train and bus schedules, sales in other retail stores, etc. This list is only limited by your creativity and the data availability.

But most fundamentally, this is a shift from why, to what. As well highlighted by Cukier and Schonberger in their book on Big Data, in this new world, we find the correlation first and then the hypothesis. And we actually don’t care why. Let’s suppose we discovered that the coffee consumption actually varied with the tides. We would need to verify whether this was simply a spurious correlation, but from there on, we could go straight to predictability and dispense with the causality, or the ‘why’ question. This is a mind shift for those of us who are used to a ‘scientific’ mentality which requires us to establish causality in order for any approach to rise beyond heuristics into a scaled and logical argument.

The Crown Jewels?

If you haven’t read Adrian Slywotzky’s great book on Value Migration, this would be a great time to start. The book talks through how value migrates from older to newer business models or from a segment to another, or even one firm to another.

We are going to see significant value moving to those companies in each industry that get the value of the data. Be it healthcare, or education, or automobiles, or even heavy industry. Either an incumbent, such as GE, with it’s smart engines and its Predix platform, or challengers such as Amazon, in retail, or upstarts such as 23andme.

The question you want to be asking yourself is, in your industry and in your firm, what are some of the areas of opportunity where you can create new platforms to data-enable processes, or value to customers. How can you converge the primary and ancillary meaning in your data onto areas of your competitive strategy? And also, you may want to perform an audit of what data you might be giving away, perhaps because you feel that it’s not core to your business or you have a player in the industry who has historically be collecting this data. For example, Experian and credit scores. Ask yourself are you merely giving away data that you don’t use, or are you handing over the source of competitive differentiation in your industry? Remember the story about IBM, Microsoft and Intel? I argued this point in my post about Uber and taxi companies, too.

To underscore the earlier point, I believe that value will increasingly migrate, in each industry, to those who best manage, and build strategic & competitive alignment with their data strategies and/ or new offerings based on the data and its meaning.

Adding Love To Data

A couple of years ago, at the annual FT Innovate conference, a lively round table discussion followed after a well known retail CEO had made a presentation about data and analysis. The presentation covered examples of analysing customers to great and occasionally worrying insight, within the industry. From knowing if a woman is pregnant even before she knows it herself, to people having affairs, or stacking beer and nappies together, in front of the stores, all of this can today be deduced from data itself. The debates afterward spilled over onto lunch led to the insight that while there’s been a lot of talk about analysing customers, it misses the point of empathy.

Let’s remind ourselves though – the customer does not want to be analysed. As with any relationship, he or she wants to be loved, cherished, understood and served better.At the end of the day, for most businesses, this translates to a mind-shift again, of adding a layer of human understanding to data, to creatively and emotionally assess the customers’ needs and to allow the analytics to feed off the empathy and emotional connect, rather than be driven purely by the algorithm.

In Sum:

You will hear a whole lot more about data in the coming weeks and months. However, for starters, you could keep these 3 guidelines in mind:

  • Look for correlations, not causality. You want to throw tons of data together and find patterns that aren’t born in some logical causal hypothesis but is simply an observed correlation done at the data level.
  • Be aware that the future of your industry, just like any industry, will involve the value of data. So try to identify and own areas of data which help you drive competitive advantage and/or new products and services, and start building proofs of concept.
  • Add love to data. Don’t just analyse your customers. Bring observation and empathy to the table as well, and marry the analytics with the empathy for best results.
What are your lessons from working with big, small and tiny data so far?

Why Is Good Design So Difficult?

Carbon-Black-Wheelchair-2
Golf has been described as a game where you try to put a very small ball into a even smaller and remotely distant hole, with instruments singularly ill adapted for the purpose. 
 
While a degree of difficulty is desirable in sport, it’s safe to say, we don’t want to gamify everything we do to by adding levels of challenges. On the contrary, we spend much of our lives individually and collectively working towards the opposite objective. How to make it easier. Easier to shop, to commute, to acquire and consume. Easier to access, easier to use. Making things easier has always been the holy grail of progress, the end game of science and technology and of design.

So why is good design so infernally difficult? Why do we feel at so many points in our lives, and during our everyday routines, that a product or a service has been really badly designed? Just this morning we discovered that the water filter in our fridge needed replacing. This can only be done by moving the cupboard sized fridge away from the wall, and unscrewing a plate behind, and then following nearly non-existent instructions in the manual, which are definitely not for the model we own. We decided to call in the professionals. Samsung recommends that the filter be changed every 6 months. Would you pay £80 every 6 months to a plumber to keep your fridge running. No, me neither. Which is why we’re going to video record the plumber and ensure we can do it ourselves next time round. Computer hardware manufacturers solved a similar design problem a long time ago, by putting the USB ports and network points in front of the device, rather than behind, and colour coding the ports.

But surely you must see instances in your daily lives that make you want to pull your hair out, simply because of the thoughtlessness of a service or a product? Some are unintended such as the walkie talkie building and the hitler tea pot. But others are just examples of callousness in design, while still others are simply relics from an older world that need a makeover.

In fact this lethargy is probably at the heart of any number of products and services which were fine a few years ago, but you simply would not design them the same way today. Consider home security. Some of the leading brands offer you the choice of “key-holder” response and “police response” at different price points. But why not a combination? Why can’t I opt for police response when I’m on holiday? Why does the alarm signal go to the provider first and then as a phone call to me? Why can’t it trigger a message to an app on my phone, with an option to turn on one or more video streams from inside the house? If you had to design a home security system from scratch today how would you design it? Chances are you’ve walked down a road where an alarm has gone off, in a home or a shop, and you’ve just walked past it, because everybody around is just ignoring the noise and getting on with their lives.

A friend of mine had an instance of an alarm going off while he was on holiday and as I was the nominated person the alarm company called me and I went round to his house at 6 AM on Sunday morning. As it turned out, there wasn’t much going on but a friendly neighbour popped by and  we looked around the house together. The neighbour found a way to get into the house because he discovered that a back window was open upon entering the house the alarm went off again. At which point the alarm company called on the land-line inside the house. The neighbour picked up the phone and he told the alarm company that he was the neighbour and he was with the key-,holder and that everything was alright and incredibly, the alarm company said in that case it was fine and hung up. Needless to say my friend changed the alarm company as soon as he got back.

Today you would probably design something like this, which allows you to see what’s going on in your house. DIY web cams aren’t the answer though, as they’re susceptible to be hacked. The right combination of institutional and personal information sharing is key.  You might also enable some community and collaborative features which allows the local community to get involved – after all they’re the ones putting up with the alarm shrieking, so they have a vested interest. Not to mention that they run a risk of a similar burglary.

Tony Fadell, the designer behind Nest and now at Google, calls this the challenge of habituation, the way in which we get used to how things are. (Like ignoring the neighbours house alarm). This is a brain feature which allows us to make somethings second nature so we can take our environment for granted without having to process everything we see all the time. The inertia, or lethargy for businesses to change a product or service stems from our habituation process. But also baked into this are network effects, accepted semiotics and social norms. The QWERTY keyboard could arguably be improved on, but the network cost of billions of people relearning how to type is mind-boggling. But the Android app Swype is a great example of a marginal design improvement. You do not want to try and improve universal symbols such as the red-amber-green of traffic lights or the signs for male and female toilets. Yet, we’ve all seen the attempts at creative improvements on toilet signs and I’ve certainly scratched my jaw on occasion trying to figure out the right sign when it’s been too abstract, or when it’s at the bottom of a flight of stairs in a pub where I’m already not at my thinking best.

Having said that, there are hundreds of products and services which could and should be better designed. Increasingly because of the way technology evolution is creating a change in our behaviour. A simple example is business cards, for those of you who still use them. Previously you would try to perhaps make your business card memorable, or be creative about how it conveys your key messages, especially if you weren’t working for a well known and recognizable brand. Increasingly though, you may want to ensure your business cards scan well, mobile apps for scanning business cards becomes a mainstream behaviour. This means avoiding vertical cards, and preserving clarity of the data in an OCR situation. The way Apple Pay or Uber scan your credit/debit cards into your mobile phone apps, is leaps ahead of earlier apps where you had to manually enter the information.

The design challenge of today, is that as products get smarter, and software gets baked into every product, how can we ensure that the experience is a good one. This isn’t simply about traditional interface design, because many products won’t have a traditional ‘user interface’ i.e. a screen of some description. In fact the user interface is now a combination of interaction, transaction, experience and environment design. You have to be aware of how the user is engaging with the product through it’s lifecycle – from unwrapping and setting up the product through to it’s ultimate replacement or disposal – and also how it engages with the environment. Parking sensors in a car is an excellent example of how the product engages with the environment and provides the feedback and engagement with the user so you know how close you might be to the object behind your car. But my earlier example of the fridge filter is a clear example of not considering the environments. I would think most people keep their fridges with their backs to the wall and probably wedged in between other appliances. As such accessing the back of the fridge is difficult and potentially dangerous if you’re moving a large fridge yourself.

One of the best principles for redesigning objects is to re-imagine their evolving purpose. Here are two examples. The first is the ambulance. Traditionally thought of as a vehicle to transport people to hospitals in the shortest time, and designed accordingly. Based on some research, it became apparent to the redesign team that a better way to consider the ambulance as a mobile unit for delivering energy care and medical services. I.e. the treatment begins in the ambulance itself. This made the principles of the redesign clearer and in turn led to a series of changes which dramatically changed the concept of the ambulance design. The second example is the wheelchair. Again, traditionally seen as a way for people with walking disability to gain the freedom of movement,  wheelchairs have always been visually  overpowering. Now, viewed as a way of giving the same people a normal social life, the redesign principle is that when you see somebody in a wheelchair, you should notice the person first and not the wheelchair. In fact even the standard wheelchair symbol is getting a redesign, in New York.

Both of these examples highlight the need for empathy, for research and for re-imagination. Sometimes the hardest of the three is the empathy and this is what makes great design so difficult. Even though plenty of design principles are now chronicled, perhaps none as well as those of Dieter Rams.

dieter rams design principles

In these times of digital transformation, the big opportunity for most organisations is to use software and smart technologies to redesign their products and services in a way that dramatically improves customer engagement, solves the problem or creates delight. The opportunities for rethinking and redesigning are immense, and if you don’t do it, the chances are that there’s a start up somewhere reinventing the design of your products.

Innovation in Pictures

These 2 cartoons wonderfully illustrate the nature of transformation – both the problem of structuring innovation and the opportunities to see things from a different perspective.

Think outside the box

The problem of structuing innovation….

Coffee new business model

The ability to map your business model to true customer needs….