To Digitally Transform, Think like Clive Davis

If you’re a music fan you probably know the name Clive Davis. If you’re not though – and heaven help you - Clive Davis is one of the most successful music producers and record industry executives of all time. He’s worked with a who’s who of rock and pop musicians from Janis Joplin to Rod Stewart to Whitney Houston over the last 50 years. Now 85, he’s still in the game and is the Chief Creative Officer of Sony Music Entertainment. By any measure of success and longevity, in what is after all an extremely precarious and fickle business, Davis has earned his place in the Rock and Roll Hall of Fame.

What you may be wondering though does the archetypal A&R man have to do “digital transformation”? Well, let me explain ...

The “digital” alarm bell has been going off (literally and figuratively) now for 20 + years. The transition to the cloud, the slow decline of ERP, the rise of Google and Apple and Amazon, the primacy of “consumer IT”, the move to Agile and Containers, the awakening to the power of data, the importance of design thinking – none of these things are new, and yet in the second half of 2017 many, many organizations are still struggling to master them, let alone leverage them to thrive in markets changing all around them faster than ever.

The question is, why? The answer – in my humble opinion – is because the executives running these organizations don’t think like Clive Davis.

Clive Davis’s success can be put down, in no small measure, to his ability to separate his own personal tastes from the tastes of the market. As an octogenarian, Davis probably favors Frank Sinatra or Tony Bennett when he’s doing the dishes or mowing the lawn (as if). But when he’s working he’s listening like an 18 year old and can hear the magic in Lil Uzi Vert or Rex Orange County - music that to his contemporaries must sound like the aural equivalent of a dislocated shoulder. Or at least the decline and fall of western civilization.

Davis recognizes that he is not the target audience; that the music is not aimed at him and has nothing to say to him. He knows that he wouldn’t buy the music. But yet he can still make judgments about its quality and its commercial appeal. And he can do this precisely because he knows that the music isn’t being made for him.

This is the mistake that is hampering so many executives in so many businesses facing the onslaught of change being rendered by digital technology. They don’t personally like the new generation of technology and technology mediated solutions and they don’t appreciate that the new technology/solutions aren’t aimed at them.

Twitter is ridiculous. Facebook is for egotistical blowhards. What even is Snap? Why do my kids spend so much time on it? Social media is destroying a generation. We can’t do this transaction on-line because of the threat of hackers. Pokémon Go? Give me a break. Virtual Reality? What are these guys on? The Cloud? But we’ve got a data center. Monetize our customer’s data? Why? Isn’t that illegal? How does this Slack thing even work? What’s wrong with email?

To the average 50 year old, running an insurance company, a bank, an airline, a retailer, contemporary technology, contemporary business approaches, and contemporary norms are the commercial equivalent of Lil Uzi Vert – terrible, ugly, ridiculous, not nearly as good as the things we listened to aka the technology solutions we built and used.

These executives fail to see that they are not the target audience. That new solutions shouldn’t be built for their contemporaries but for their kids. They fail to separate their own personal tastes from the tastes of the where the market is going.

Doing this – separating your own personal judgments from those of the market – is terribly hard (hence why so few executives can do it). It’s tough for people who have ascended slippery career ladders to admit they don’t know something. It’s tough for them to even contemplate that they are “aging out”. That they are no longer “hip to the hop”, in touch, on fleek. But mostly it’s hard to admit – privately to yourself let alone publically to your staff/boss/board – that you’re no longer that interested in something and that you don’t really like x or y.

To truly grasp the promise of the Fourth Industrial Revolution you’ve got to really love it – and everything about it. Or, if you can’t, you’ve got to surround yourself with people who do. In Clive Davis’s case, A&R people who trawl the clubs and Soundcloud and YouTube and Spotify and SXSW. In your case digital whisperers from Cognizant’s Center for the Future of Work.

So next time you’re in a meeting with your team trying to inch forward with your digital transformation initiative, remember to think like Clive Davis. Remember, it’s not about you. It’s about the next generation and the stupid things they’re interested in. Play your Sinatra or Costello or Counting Crows tunes all you like at home. But don’t pretend that, now that you have the turn table (aka the digital transformation budget) the kids are going to dig what you all say. They ain’t lit with that.

The Speed Mandate

As CEO Marc Benioff rightly said, “Speed is the new currency of business. If you’re not going fast enough, someone else is.” In an age when a start-up can reshape an entire industry overnight, businesses must be on their A-game. For instance, Alipay, the world’s biggest payment company, had hit $100 billion in transactions in less than a year with zero branches, while DBS Bank in Singapore took 50 years to reach the same milestone. It is not a coincidence that many shareholders’ reports of S&P 500 companies are littered with “speed,” “fast” and their synonyms today. The stakes are higher because the pace of business change has intensified dramatically.

The speed of doing business, generating value, making decisions, meeting customer expectations and getting products and services to market decide whether you are moving ahead or lagging behind. In short, time-to-everything matters more than any other strategic imperative. In particular, there are five approaches that set the speed context and leaders need to be brutally honest about the current pace of change in their organization on each of the five areas:

  • Speed to automation. If you’ve spent most of your career around ERP and Six Sigma, you’ll know that 3% to 5% efficiency gains were once considered big. It’s a different ballgame now. According to our Work Ahead research, applying robotic process automation (RPA) to long-standing core business processes can drive 30% to 60% (or even more) of costs out of a business’s operations, with error rates plummeting to near zero. This is the reason more than half (55%) of companies recently surveyed are either piloting or planning to adopt RPA, while 10% are already applying automation to their core processes. Businesses should set a target to double the speed of their core processes to double their cost savings and time-to-market improvements.
  • Speed to monetize halos of information. Massive data volumes and the pressure to derive insights from it are creating a digital overload for many companies at a time when they need to accelerate the speed of decision-making in their organizations. Companies that use advanced analytics and machine learning are twice as likely to be top-quartile financial performers, and three times more likely to execute effective decisions. To stay ahead of the curve, businesses should set a target for the next 12 months to match their decision-making speed to that of anticipated growth in data volumes. For instance, if you expect a 30% annual growth in data over the next 12 months, then the organization’s speed of making insights and applying data intelligence needs to accelerate by 30% during the same period. Anything less is going to impact the speed of doing business in this fast-changing world.
  • Speed to enhance the workforce. The enhanced workforce is the new workforce. Rather than jobs being eliminated, it is more likely they will be altered or enhanced by bots. Moving to the cloud, automating back- and middle-office processes and workflows, and leveraging bots to address employee and customer support will not only eliminate mundane technical and maintenance tasks but also drive greater operational efficiency. For example, the team at Amazon Web Services uses AI to improve employee efficiency and decision-making by suggesting the best places to focus their attention each day. Businesses should set a target to enhance every person in the organization to speed up the company’s performance, as well as help workers focus on the more human elements of the job (strategic thinking, leadership, decision-making, innovation, among others) to double their output or greatly increase their quality of delivery.
  • Speed to abundance. Simply put, as prices decline, demand typically rises; once a mass market is created, customers become bought into the need for the product and/or service. This, in essence, is the definition of abundance. Businesses can create markets of abundance by leveraging AI, analytics, and automation to drive down the price point of products or services to compete and win in low-cost, high-volume markets. A good example is the success of Reliance Jio, a new telecom company in India, which aims to provide data services for as little as the cost of a postcard. The business reached 100 million subscribers in just 170 days, or roughly seven users per second per day, forcing the competition to lower their prices. Aim for lower-cost, high-volume approach for your business.
  • Speed to discovery. Innovation is central to remaining relevant. By leveraging the new machine, businesses can conceive of entirely new products, new services and new industries for the digital economy. Companies that are trying to establish their digital strategy for triggering innovation must rip up the rulebook. For instance, A3, the innovation outpost of Airbus, recently embarked on development of an on-demand service for urban helicopter transport, usable via a mobile app. This would connect passengers and operators, making helicopters more accessible and affordable. In another example, Tesla cars use “over the air” software updates, eliminating the need for owners to bring their cars to the dealer.

The speed of change that leaders set will determine how fast or slow they grow their business in the years to come. Companies that accelerate by automating everything they can, instrumenting everything they can, enhancing every worker they can, driving the price points of their products and services as low as they can, and discovering and inventing all their possible futures will be best positioned to take advantage of the new machine age.

Learn more about the speed context and acquire the insights you need to set the right speed of your business by checking out our new report, “Fast, But Not Furious.”

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Six Months on the AI Road

In the six months since the publication of What to Do When Machines Do Everything I, and my fellow authors, have been to all points north, south, east and west, spreading the good word. In that time we’ve spoken to hundreds of people individually, and thousands collectively, about the great story of our time - the rise of Artificial Intelligence. 

Here are a few of my personal observations from those last six months; of how people are thinking about and reacting to the emergence of intelligent machines; of the current mood towards AI; of media interest in this important topic, and where the current zeitgeist seems to be. 

  • The Explosion of Interest is Unprecedented - In my 25+ year career as a professional IT industry analyst I have never seen something take off and reach such dizzying heights so quickly. When we put our manuscript “to bed” in the fall of 2016 we little expected that we would be launching the book in the following spring into the middle of a maelstrom of AI sound and fury. 
  • Everyone is Interested - This interest has been widespread amongst the general “civilian” media as well as the technical and business press. If you run or edit a media property - of any type or  flavor in any part of the world - you have probably run a story on “the robots are coming for our jobs” theme in the last few months. 
  • Everyone is Afraid - AI clearly touches a very powerful nerve in humanity. “We” (aka “people”) have a visceral, real fear that one day robots will, at best, make us redundant, and at worst, enslave us. One doesn't have to get very far into a conversation with someone (or an audience) before seemingly intelligent, senior folks - who you might think already have a lot of pressing things to worry about - raise existential fears that they, or their kids, will soon be surplus to requirements. The success that writers and film makers have had over the last two hundred years exploring the dark-side of the robots theme - remembering that the first edition of Mary Shelley’s Frankenstein was published in 1818 –is testament to the reality of this fear. To dismiss it lightly is to misunderstand human psychology. 
  • Dystopians Rule OK - There are far more dystopians than utopians around today. Optimists about the future of work are in the minority and have the burden of proof. In fact, on my travels and in my readings of the last few months, I have detected a strong souring towards “technology” in general. Concern over AI has become mixed with concern over the downsides of data analytics which has become mixed with sociopolitical questioning of the role of social media and “fake news” in the 2016 US election and the impact phones are having on “screenagers”. It feels like “Big Data” – with AI as its engine - is beginning to move into the same territory that “Big Oil”, “Big Pharma”, and “Big Soda” have come to occupy.  
  • It’s the Economy, Stupid - Interest in AI is heavily orientated towards its socioeconomics implications, rather than the underlying technology or on its impact on business. Even technologists and business leaders gravitate very quickly towards this broader conversation. I was at a dinner with a CIO of a large utility company outlining the themes and ideas within our book and what it could do for his organization; after listening to me for 10 minutes or so, he then launched into a soliloquy about how the long term prospects of his company could be fatally undermined as unemployment and underemployment took hold when machines do everything. He had clearly thought about this a lot in a very sophisticated way and was genuinely concerned. He wasn’t interested in talking about which AI platform he should deploy. 
  • Extrapolation Rules OK - taking huge leaps from what they know of AI today to what it might become in the future is extremely common. Due probably to the deep seated fears mentioned above, few people seems to have any compunction in thinking the very worst based on a small set of flimsy facts. Getting from Tesla “driver assist” to the wholesale collapse of the truck driving industry in 3.2 seconds is common in conversation and debate. Digging into the nuances of that dynamic and recognizing that a) this scenario is unlikely in the forecastable future and b) will take a long time (e.g. 30-50 years) to unfold even as it inevitably does, is less interesting and fun than throwing up one’s hands and crying “we’re doomed, we’re doomed”. 
  • Opinions Wanted: No Experience Required - Never have so many unqualified people pontificated on something so important so much. Most people (I think, I hope) wouldn’t discuss the future of neurosurgery, or quantum computing, or the Ornstein-Uhlenbeck mean reversion algorithm, unless they were a surgeon, or a PhD wielding mathematician or a coder in a financial services firm. Being a journalist or a teacher or a fundraiser or C++ programmer or a law professor though is no disqualification from having very strong opinions about the future of AI. Given its importance, perhaps it is understandably (and maybe even a good thing) that everybody wants to weigh in on AI. But the consequence is that 95% of the general media debate around AI is pretty worthless. 
  • Philosophy’s Important Too. Isn’t It? - Those with an arts based degree are very motivated to argue that “soft”, non-technical skills will be even more important in the coming highly technical age. As someone with an arts degree myself I’d like to believe that’s true but I can’t help thinking that it’s a clear case of the “wish being father to the thought”. Geeks are truly inheriting the earth, though I hope I’m wrong. 
  • AI Forever - The AI “wave” is a very long one. Inevitably, there will be an “AI backlash” in the next year or so, and the current frenzy will abate. But AI - being the great story of our time - will develop and spread into every aspect of our lives and society for the rest of our natural lives, and the lives of everybody alive today. Cloud Computing is 20 years old this year and whilst old news to those of us around at its inception is still a brave new world to many people and companies. AI is an even bigger wave than the Cloud and will take even longer to fully unfold.  
  • We’re Still at the Bottom of the 1st - Companies have only started scratching the surface of using AI – even the most sophisticated ones with the current biggest AI related deployments. It’s logical that the next few years will see an explosion of use of AI – following the explosion of interest – but I would hazard a guess and suggest that even in five years the actual real amount of leverage of AI in the typical insurance company or government department will be still relatively minor and a fraction of what it will be in 2067. The media are only beginning to become interested in thinking about the business implications of AI. 
  • WMDE Signal and Noise - Finally, finishing where I started, the professional “thought leadership”, and “content marketing” industry is having a field day with AI. Every consulting firm, software provider, academic, tech player of any background has pumped AI collateral into the market. I fully recognize that this is a case of the pot calling the kettle black but the speed at which this has happened has been noteworthy. I blame Twitter - the “echo-chamber” it creates spreads memes at warp speed and its gravitational pull is hard to escape. Thinking differently is harder and harder when everyone and their wife is so keen to share (putting it politely). I and my fellow authors take comfort in knowing that we spent two years writing our book so it would be hard to accuse us of jumping on any bandwagons. I fear though that just as the ease of making and distributing music killed the music industry the ease of creating and distributing thought leadership has worrying implications for the health of my 401k. 

The last six months have been an incredible ride. We don’t stop here though. The story of AI continues to develop and evolve and there are still many miles to go, case studies to outline, and anecdotes to spin. When Machines Do Everything there will still be presentations to make, conferences to attend, and heated debates to have. One day a robot or an avatar will stand before you as an ambassador from the strange new world you’re set to inhabit. But until that day – that happy day?! – you’re stuck with yours truly. I look forward to seeing you when I roll into your town.