Innovation Archive

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Machines increasingly complement human labor in the workplace

Automation and artificial intelligence (AI) are transforming businesses and will contribute to economic growth via contributions to productivity. They will also help address “moonshot” societal challenges in areas from health to climate change.

At the same time, these technologies will transform the nature of work and the workplace itself. Machines will be able to carry out more of the tasks done by humans, complement the work that humans do, and even perform some tasks that go beyond what humans can do. As a result, some occupations will decline, others will grow, and many more will change.

While we believe there will be enough work to go around (barring extreme scenarios), society will need to grapple with significant workforce transitions and dislocation. Workers will need to acquire new skills and adapt to the increasingly capable machines alongside them in the workplace. They may have to move from declining occupations to growing and, in some cases, new occupations.

This executive briefing, which draws on the latest research from the McKinsey Global Institute, examines both the promise and the challenge of automation and AI in the workplace and outlines some of the critical issues that policy makers, companies, and individuals will need to solve for.

  1. Accelerating progress in AI and automation is creating opportunities for businesses, the economy, and society
  2. How AI and automation will affect work
  3. Key workforce transitions and challenges
  4. Ten things to solve for

More: McKinsey Global Institute

Authors: James Manyika is chairman and director of the McKinsey Global Institute and a senior partner at McKinsey & Company based in San Francisco. Kevin Sneader is McKinsey’s global managing partner-elect, based in Hong Kong.

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Intelligent process automation

Full intelligent process automation comprises five key technologies. Here’s how to use them to enhance productivity and efficiency, reduce operational risks, and improve customer experiences.

Since the financial crisis of 2007–09, many companies have applied lean management to improve cost efficiencies, customer satisfaction, and employee engagement simultaneously, and many programs have achieved substantial impact on all dimensions. Progress on digital, however, has been more uneven. In the insurance sector, for example, an October 2016 FIS study found that 99.6 percent of insurers surveyed admitted they face obstacles in implementing digital innovation, while 80 percent recognize they need digital capabilities to meet business challenges. This difficulty has been compounded by the boom in “insurtech” investments in 2016—topping $3.5 billion in funding across 111 deals since 2015.

As macroeconomic conditions continue to put pressure on profit margins across sectors, cost productivity and unlocking new value are back at the top of the senior-management agenda. The question is, what else can be done?

That’s where intelligent process automation (IPA) comes in. We believe it will be a core part of companies’ next-generation operating models. Many companies across industries have been experimenting with IPA, with impressive results:

  • Automation of 50 to 70 percent of tasks . . .
  • . . . which has translated into 20 to 35 percent annual run-rate cost efficiencies . . .
  • . . . and a reduction in straight-through process time of 50 to 60 percent . . .
  • . . . with return on investments most often in triple-digit percentages.

New technologies that promise double-digit or even triple-digit same-year returns should rightfully be viewed with skepticism. But our experience shows that the promise of IPA is real if executives carefully consider and understand the drivers of opportunity and incorporate them effectively with the other approaches and capabilities that drive the next-generation operating model. (For more on these approaches and capabilities, please read “The next-generation operating model for the digital world.”)

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Shaking up the value chain

Data and digitization are creating a growing array of value-creation choices in industries as diverse as pharmaceuticals, mining, and energy.

During the 1980s, McKinsey’s Fred Gluck and Harvard Business School professor Michael Porter began writing about the interrelated activities through which companies create value for their customers. Executives have always had choices about how to perform the activities in this “business system” (Gluck’s words) or “value chain” (Porter’s). In the digital age, as information disrupts the nature of value creation in many industries, the range of choices available to senior business leaders has increased. For example, digital platforms in the pharmaceutical industry now make it possible to aggregate massive amounts of data on diseases—potentially accelerating the discovery and design of new drugs and challenging the industry’s legacy processes. In energy production and mining, although companies have long outsourced some functions in efforts to drive down costs, digital requires a new approach. Using data, suppliers can offer incumbents an expanded range of capabilities and productivity gains—alluring possibilities that are accompanied by the risk that sharing too much data could shut off areas of future growth. This type of flux in value chains will only intensify across industries, forcing leaders to grapple with existential questions about core competitive strengths in an environment where destabilizing technologies will be the norm.

Will digital platforms transform pharmaceuticals?

Start-up companies are combining genetic information and new therapies to transform drug discovery and development—at greater speed and scale.

Product innovation is at the heart of the pharmaceutical industry’s value chain. Long, capital-intensive development cycles and legacy processes, though, have made it difficult to exploit the full potential of emerging digital technologies to deliver faster, more agile approaches to discover and develop new drugs. Indeed, McKinsey research shows that the industry’s digital maturity lags that of most other industries.

A new current is forming in one area of the industry: start-up companies that are creating biomolecular platforms around cellular, genetic, and other advanced therapies.1 The platforms marshal vast amounts of data on the genetics of diseases, such as cancer, and combine that with patients’ genetic profiles and related data. They zero in on key points along the information chain—for example, where there are linkages between DNA and proteins, and then cells—to “design” new drugs. Much like software developers, the platforms engineer disease therapies built upon the “code-like” DNA and RNA sequences within cells (Exhibit 1).

These techniques have significant implications for the treatment of many life-threatening illnesses that are outside the reach of standard therapeutic approaches. They could also disrupt the industry’s value chain as they speed up drug discovery and development, with the potential for a single platform to scale rapidly across a range of diseases (Exhibit 2).

In one example of a biomolecular platform, for a disease that results from a mutation in DNA that codes for a needed enzyme, the platform models the disease from medical and genetic data to arrive at an enzyme “optimized” to correct for the mutation. The platform then designs a sequence of genetic material to treat the disease, as well as a delivery vehicle to get it to the target cells. In another example, for CAR-T2 therapies, the platform modifies a patient’s T cells (an immune-system cell), which are then deployed to attack a cancer.

A new competitive landscape

Optimized biomolecular platforms have the potential to accelerate the early stages of R&D significantly. For example, it can take as little as weeks or months to go from concept to drug versus what’s often many months, if not years, of trial and error under conventional discovery methods. This is achieved by routinizing key steps (such as preparing a drug for preclinical testing) and using common underlying elements in the design of the drug (such as drug-delivery vehicles that are similar). In the past five years or so, a number of start-ups have formulated dozens of drugs that are in clinical trials and, in some cases, drugs that have already been approved. The large information base behind therapies helps identify the right targets for preclinical and clinical trials.

By Olivier Leclerc and Jeff Smith

More: https://www.mckinsey.com

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Blockchain beyond the hype: What is the strategic business value?

Companies can determine whether they should invest in blockchain by focusing on specific use cases and their market position.

Speculation on the value of blockchain is rife, with Bitcoin—the first and most infamous application of blockchain—grabbing headlines for its rocketing price and volatility. That the focus of blockchain is wrapped up with Bitcoin is not surprising given that its market value surged from less than $20 billion to more than $200 billion over the course of 2017.1 Yet Bitcoin is only the first application of blockchain technology that has captured the attention of government and industry.

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ConsumerLab Report Ericsson – 10 Hot Consumer Trends 2018

Imagine you have just arrived home from work. You wave your hand, and the lamp turns on, flashing the light in greeting. The home speaker begins to play music, but when you give it an exasperated look, it turns off. You make a coffee, but grimace because it’s too bitter. The coffee machine immediately offers to add sugar or milk.

Two things are conspicuously absent from this vision of a not-too-distant future. One is an appliance with switches and knobs, and the other is a smartphone full of remote control apps. Our research indicates that consumers are increasingly moving towards a paradigmatic shift in how they expect to interact with technology. Ever more things are becoming connected, but the complexities of how to control them all are a different matter.

On the one hand, alternative yet equally good user interface solutions for simple functions have existed for much longer than we’ve had electronic gadgets. A Westerner who experiences an Asian meal for the first time soon finds out that the user interface to that meal is a pair of chopsticks rather than a knife and fork. On the other hand, mass-market acceptance of digital technology has made the proliferation of user interfaces practically infinite. Every new device with a screen adds new user interface variations, which are then multiplied by the number of apps within each gadget.

Today you have to know all the devices. But tomorrow all the devices will have to know you. If consumers continue to be faced with the prospect of learning and relearning how to use devices in the face of an ever-increasing pace of technological change, they will become increasingly reluctant to buy in to the future. We might already be close to that breaking point. The current generation of “flat” user interfaces do not use 3D effects or embellishments to make clickable interface elements, such as buttons, stand out. It is difficult for users to know where to click. As a result, they navigate web pages 22 percent slower.1 For this reason, our trends for 2018 and beyond focus on various aspects of more direct interaction between consumers and technology.

With 5G, connectivity is set to become ubiquitous. This might sound simple, but it involves a huge technology upgrade; devices must be able to relay complex human interaction data to cloud-based processing, and respond intuitively within milliseconds. The Internet of Things (IoT) must provide interoperability between all devices, and allow for mobility. Network availability also needs to be maintained, so that devices do not suddenly go offline and lose their human-like capabilities.

More: www.ericsson.com