The power to innovate is falling into the hands of hyper-talented individuals.
Traditionally, the largest and most successful corporations were also the largest employers. Manufacturing and retail businesses required factories, warehouses, logistics and plenty of manpower, all working in harmony to deliver their product or service. Building this capability took years, requiring significant capital investments. Thus, competitors were few and far between, and disruption was painfully slow to make a dent on existing hierarchies.
But with the rise of technology, the model of success has gradually evolved, with businesses requiring fewer and fewer resources and employees to make an impact. Whatsapp is the perfect example; already worth $19bn with only 55 employees. And as we enter the next wave of tech innovation, we’ll increasingly see power transfer away from traditional ‘corporations’ and fall into the hands of smaller groups of highly skilled and hyper-talented individuals.
More, but increasingly complex opportunities
There has never been a more exciting time to be an entrepreneur, with emerging technologies bringing an unprecedented number of opportunities for innovation across platforms and software, with minimal physical resources and infrastructure required. We’re only now beginning to understand the potential of tools such as AI, machine learning, AR, VR, and the Internet of Things, and how they can be combined to create breakthroughs across a whole range of industries and problems.
Yet, identifying and then maximizing these complex and increasingly technical opportunities requires equally specialist knowledge and skills, along with the ability to respond rapidly to new innovations and competition. Understanding and manipulating the most cutting-edge tools requires the best brains, not to mention the drive, resilience and vision to identify the ideas with the most potential. The barriers to entry are rising, placing the power in the hands of those highly capable individuals, who are no longer reliant on building large organizations or physical assets to realize their ambitions.
Size doesn’t equal power
Corporations have always struggled to innovate, lacking the natural agility and flexibility of smaller organizations. However, as we enter this new age of innovation, it is becoming even tougher for the incumbents to keep up with the pace of change and increasing complexity, even with all their manpower and their abundance of cash lying dormant on the balance sheet.
What these big businesses are lacking is the ability to harness the power of the most talented individuals, by providing an environment where they can thrive. Radical change needs mavericks and risk takers who in turn need the freedom and ability to innovate; not be put in a straight-jacket and told to behave and operate according to corporate rules. The most extreme innovators don’t fit into old-fashioned, archaic organizational structures, which means it’s very difficult for big businesses to attract, integrate and retain these individuals.
Investing in these most cutting-edge technologies is also extremely risky, and corporations are too afraid of making mistakes and too busy covering their backs to take a serious punt on ideas that might not build any value. Innovation requires agility and radical thinking, which is impossible in an environment that is paralyzed by politics, an aversion to change and worries of cannibalising its existing revenue streams and product lines. Their only real hopes are spin-offs, joint ventures and acquisitions of the most talented individuals – not in-house innovation.
Supporting the individual
Those who succeed in the next wave of innovation will be those individuals and small teams with the technical skills and a ‘knack’ for understanding the end vision, along with the freedom and agility to explore the unknown. But to have this freedom, these individuals must be adequately supported with resources, networks and capital to take the necessary risks and follow their instincts.
While there has been a lot of discussion about “what’s left for humans?” as AI improves at exponential rates — the customary answer is that humans need to focus on the things they are uniquely good at, such as creativity, intuition, and personal empathy — I think we now have to ask, “what’s left for firms?”
In many ways this is an old question, because it takes us back to the arguments of Nobel Laureates Ronald Coase and Oliver Williamson that firms exist to coordinate complex forms of economic activity in an efficient way. If computer technology has the capacity to simplify and streamline transaction costs, more and more work can be done through these smart-contract arrangements, making traditional human-managed firms obsolete. For example, when you say to Alexa “order more dog food,” a chain of activities is initiated that leads to the delivery of a fresh supply of Kibble 24 hours later, with little or no human intervention. This work is coordinated by a single firm, Amazon, but it often involves third parties (makers of dog food, delivery companies) whose systems interact seamlessly with Amazon’s.
But is this coordination logic, this ability to internalize transactions to make them more efficient, really the raison d’etre of firms? I would argue that it is just one among many reasons that firms exist. And as computer technology simplifies and reduces transaction costs further, it is these other things that firms do uniquely well that will come more to the forefront. Here are four areas where firms excel.
1. Firms create value by managing tensions between competing priorities.
In today’s parlance, firms have to exploit their established sources of advantage (to make profits today) while also exploring for new sources of advantage (to ensure their long-term viability). However, getting the right balance between these two sets of activities is tricky because each one is to a large degree self-reinforcing. Hence the notion of organizational ambidexterity — the capacity to balance exploitation and exploration.
Artificial intelligence is evidently helping many firms to exploit their existing sources of advantage — whether through process automation, improved problem-solving or quality assurance. Artificial intelligence can also be useful in exploring new sources of advantage: in the famous case of AlphaGo, the winning “strategy” was one that no human player had ever come up with; and computers are increasingly writing new musical scores and painting Picasso-like landscapes.
But AI is not helpful in managing the tension between these activities, i.e. knowing when to do more of one or the other. Such choices require careful judgment — weighing up qualitative and quantitative factors, being sensitive to context, or bringing emotional or intuitive factors into play. These are the capabilities that lie at the heart of organizational ambidexterity and I don’t believe AI can help us with them at all right now. IBM’s recently-announced Project Debater is a case in point: it showed just how far AI has come in terms of constructing and articulating a point of view, but equally how much better humans are at balancing different points of view.
2. Firms create value by taking a long-term perspective.
As a variant of the first point, firms don’t just manage trade-offs between exploitation and exploration on a day to day basis, they also manage trade-offs over time. My former colleagues Sumantra Ghoshal and Peter Moran wrote a landmark paper arguing that, unlike markets, firms deliberately take resources away from their short-term best use, in order to give themselves the chance to create even more value over the long term. This “one step back, two steps forward” logic manifests itself in many ways — risky R&D projects, pursuing sustainability goals, paying above-market wages to improve loyalty, and so on. We actually take it for granted that firms will do many of these things, but again they involve judgments that AI is ill equipped to help us with. AI can devise seemingly-cunning strategies that look prescient (remember AlphaGo) but only when the rules of the game are pre-determined and stable.
An example: the “Innovator’s Dilemma” is that by the time it’s clear an invasive technology is going to disrupt an incumbent firm’s business model, it’s too late to respond effectively. The incumbent therefore needs to invest in the invasive technology before it is definitively needed. Successful firms, in other words, need to be prepared to commit to new technologies in periods of ambiguity, and to have a “willingness to be misunderstood,” in Jeff Bezos’s terms. This isn’t an easy concept for AI to get used to.
3. Firms create value through purpose — a moral or spiritual call to action.
There is a second dimension to long-term thinking, and that is its impact on individual and team motivation. We typically use the term purpose here, to describe what Ratan Tata calls a “moral or spiritual call to action” that leads people to put in discretionary effort — to work long hours, and to bring their passion and creativity to the workplace.
This notion that a firm has a social quality — a purpose or identity — that goes beyond its economic raison d’etre is well established in the literature, from March and Simon through to Kogut and Zander. But it still arouses suspicion among those who think of the firm as a nexus of contracts, and who believe that people are motivated largely through extrinsic rewards.
My view is that you just need to look at charities, open source software movements, and many other not-for-profit organizations to realize that many people actually work harder when money is not involved. And it is the capacity of a leader to articulate a sense of purpose, in a way that creates emotional resonance with followers, that is uniquely human.
Successful firms, in other words, institutionalize a sense of identity and purpose that attracts employees and customers. Ironically, even though blockchain technology is — by definition — about building a system that cannot be hacked, or misused by a few opportunists, people still prefer to put their faith in other people.
4. Firms create value by nurturing “unreasonable” behavior.
There are many famous cases of mavericks who succeeded by challenging the rules, such as Steve Jobs, Elon Musk, and Richard Branson. With apologies to George Bernard Shaw, I think of these people as unreasonable — they seek to adapt the world to their view, rather than learn to fit in. And if we want to see progress, to move beyond what is already known and proven, we need more of these types of people in our firms.
Unreasonableness is antithetical to the world of AI. Computers work either through sophisticated algorithms or by inference from prior data, and in both cases the capacity to make an entirely out-of-the-box leap doesn’t exist. Consider the case of investment management, where robo advisors are not just making trades, they are also providing investment advice to investors, and at a fraction of the cost of human financial advisors. But as the Financial Times said last year, “when it comes to investing, human stupidity beats AI.” In other words, if you want to beat the market, you need to be a contrarian — you need to make investments that go against the perceived wisdom at the time, and you need to accept the risk that your judgment or your timing might be wrong. Both qualities that — at the moment — are distinctively human.
So one of the distinctive qualities of firms is that they nurture this type of unreasonable behavior. Of course, many firms do their best to drive out variance, by using tight control systems and punishing failure. My argument is that as AI becomes more influential, though the automation of basic activities and simple contracts, it becomes even more important for firms to push in the other direction — to nurture unorthodox thinking, encourage experimentation, and tolerate failure.
In a recent Fast Company article, Vitalik Buterin described how all the elements of Uber’s ride-sharing service could be provided through Ethereum-based applications that worked seamlessly with one another: “the whole process is basically as before, but without the middleman [Uber].” This is may be true, but it doesn’t necessarily follow that a computer-mediated service is the better option.
IBM and the U.S. Department of Energy’s Oak Ridge National Laboratory (ORNL) today unveiled Summit, the department’s newest supercomputer. IBM claims that Summit is currently the world’s “most powerful and smartest scientific supercomputer” with a peak performance of a whopping 200,000 trillion calculations per second. That performance should put it comfortably at the top of the Top 500 supercomputer ranking when the new list is published later this month. That would also mark the first time since 2012 that a U.S.-based supercomputer holds the top spot on that list.
Summit, which has been in the works for a few years now, features 4,608 compute servers with two 22-core IBM Power9 chips and six Nvidia Tesla V100 GPUs each. In total, the system also features over 10 petabytes of memory. Given the presence of the Nvidia GPUs, it’s no surprise that the system is meant to be used for machine learning and deep learning applications, as well as the usual high performance computing workloads for research in energy and advanced materials that you would expect to happen at Oak Ridge.
IBM was the general contractor for Summit and the company collaborated with Nvidia, RedHat and InfiniBand networking specialists Mellanox on delivering the new machine.
“Summit’s AI-optimized hardware also gives researchers an incredible platform for analyzing massive datasets and creating intelligent software to accelerate the pace of discovery,” said Jeff Nichols, ORNL associate laboratory director for computing and computational sciences, in today’s announcement.
Customer experience is what sets you apart from your competition. A lot of dollars are being invested to analyze customers’ expectations and building technology that can enhance how customers perceive your brand.
AI is at the core of Cybernetic CX – a cyclic process – analyzing, identifying problems, determining solutions, applying them, monitoring, and repeat.
Cybernetic CX will use advanced analytics and AI to detect patterns and identify anomalies. This information will be fed to machine learning algorithms, which will continue to evolve and be able to correlate with a set of outliers to the root cause. As the problems are diagnosed and the remedies applied, machine learning algorithms powered by heuristics will be able to correctly predict remedies, which will be automatically applied to fix the problem.
Better still, it may even anticipate an upcoming issue and take actions to mitigate it.
According to a J.D.Power study, American Express has excelled at customer satisfaction for their credit cards. They seem to be getting their cybernetics right. For instance, a customer doesn’t have to go through multiple hand-offs while connecting to AMEX departments, as their routing system uses advanced analytics, predictive modeling and operational consolidation to route to the correct department.
Though in an embryonic stage, cybernetics can augment your future CX efforts.
2. Digital experience platform
For weaving a seamless customer journey, a customer-centric view and integration of all activities like marketing, sales, operations, customer service etc. have become a mandate. DXPs (digital experience platform) help you centralize and share context and content across your organization, which enables ease of coordination and knowledge sharing across locations, teams and technology platforms.
Technological solutions like social media monitoring, cross-channel surveys, speech and text analytics are used to capture and analyze customer preferences, feedback, and expectations. VoC tools can give insights that can aid frontline agents to understand their customers better and help various departments (marketing, sales etc.) to have an in-depth view of the customer journey. VoC helps in:
Formulating better campaign messages
Creating a unified customer view
Uncovering areas of opportunity
Identifying areas of customer dissatisfaction
Measuring business efficiency and performance
A Voc tool may contain:
Ability to collect a large amount of customer feedback and generate reports
A holistic view of customer journey like the type of interaction, touchpoints etc.
NLP, text analytics, speech recognition, semantic analysis, emotion detection etc.
Augmented and Virtual Reality(AR/VR) are the game changers when it comes to creating awesome customer experiences. Both AR and VR can create engaging customer-brand interactions.
AR is being adopted by retail, financial, healthcare and hospitality industries alike to create immersive and meaningful experiences. For instance, AR in the food and beverage industry enhance guest experiences. AR menus create virtual food with multiple digital renderings and 3D photographs to display accurate representation and portions. Customers can also scan menus or food packages to determine nutritional information.
Internet of Things is how various devices form a wireless network and communicate with each other using sensors. IoT holds tremendous engaging power and is the key to bring coherence to omnichannel CX strategies. Leveraging IoT, businesses can:
Reach customers in real-time: As a loyal customer is nearing your store, using hisgeo-location you can offer to serve him his favorite meal or offer a discount on his favorite order.
Make lives convenient: How about reading a grocery list on your customer’s smartphone and automatically creating a cart with the discounted items, and sending an alert to her to hit the buy button, before she runs out of stock?
Product health: IoT product can report its health to the customer care, which can proactively act by scheduling a service and fix issues before they become a reality. Read More