Three practices can help differentiate successful companies from those that struggle to gain traction.
Internet of Things (IoT) technologies have evolved rapidly in recent years and continue to change how we interact with our surroundings. For companies, IoT brings new ways to monitor and manage objects in the physical world, while massive new streams of data offer better avenues for decision making (often mediated by machines). The steady fall in prices of sensors and communications technologies, combined with a parallel rise in understanding of how they can be applied, have raised the strategic importance of IoT. As we have shown elsewhere, this can produce immense value in settings ranging from retail and healthcare to manufacturing and technology.
Despite the promise, we continue to see substantial differences in how well companies apply IoT in their businesses. Targeting IoT applications correctly and managing them effectively is far from easy, leaving many companies stuck and unable to move beyond pilots. To better understand what differentiates successful initiatives from struggling ones, we surveyed IoT executives at 300 companies—those that have moved beyond experiments and have scaled up IoT use in their businesses.1 We asked them about the practices that directly support their IoT strategy, as well as other factors that may influence it, and sorted leaders from laggards based on their self-reported economic impact from IoT.2 We found that while a number of IoT “habits” play a role in successes, three are particularly relevant for C-level executives who may be considering heavier investment in IoT or searching for reasons their programs have failed to gain traction. Den Rest des Beitrags lesen »
Organizations in every region and industry are automating at least some business processes, yet only a slight majority have succeeded at meeting their targets, according to a new McKinsey Global Survey on the topic.1 As advances in artificial intelligence, software robotics, machine learning, and innovative technology platforms enable businesses to redefine processes, workplace automation is expected to provide a significant opportunity for improvements in performance and efficiency.2 Indeed, three-quarters of all respondents say their companies have already begun to automate business processes or plan to do so within the next year. The results also suggest which practices best support a successful automation effort: making automation a strategic priority, deploying technologies systematically, decentralizing governance, ensuring the IT function’s involvement, internalizing automation’s costs and benefits, and prioritizing workforce management.
Automation, a global phenomenon
Across regions and industries, the survey results suggest that automating businesses is a global phenomenon (Exhibit 1). A majority of all respondents (57 percent) say their organizations are at least piloting the automation of processes in one or more business units or functions. Another 38 percent say their organizations have not begun to automate business processes, but nearly half of them say their organizations plan to do so within the next year.3 Across regions, respondents in developing markets are just as likely as their peers to report automation activity. Den Rest des Beitrags lesen »
The CEOs of Ping Identity, Plaid, and Tink share their views on the prospects for open banking and the pressing need for players to develop a data and customer strategy.
The notion of open banking has been central to financial services dialogue for many months, fueled in part by the buildup to the EU’s revised Payment Services Directive(PSD2). We define “open banking” as a model in which banking data is shared between two or more unaffiliated parties to deliver enhanced capabilities to the marketplace. For more on recent movements related to PSD2, see sidebar, “PSD2 and open banking.”
Progress toward data sharing has differed by region depending on market structures, regulatory environments, and consumer attitudes toward privacy and security. Varied interpretations of the word open from both industry firms and consumers are also shaping approaches to this new model. Use cases range from new interfaces for financial data, alternative underwriting and lending, facilitating new payments streams, and the opening of ecosystems. (See “Remaking the bank for an ecosystem world,” October 2017.) Den Rest des Beitrags lesen »
Early AI adopters are starting to shift industry profit pools. Companies need strong digital capabilities to compete.
The diffusion of a new technology, whether ATMs in banking or radio-frequency identification tags in retailing, typically traces an S-curve.Early on, a few power users bet heavily on the innovation. Then, over time, as more companies rush to embrace the technology and capture the potential gains, the market opportunities for nonadopters dwindle. The cycle draws to a close with slow movers suffering damage.1
Our research suggests that a technology race has started along the S-curve for artificial intelligence (AI),a set of new technologies now in the early stages of deployment.2 It appears that AI adopters can’t flourish without a solid base of core and advanced digital technologies. Companies that can assemble this bundle of capabilities are starting to pull away from the pack and will probably be AI’s ultimate winners. Executives are becoming aware of what is at stake: our survey research shows that 45 percent of executives who have yet to invest in AI fear falling behind competitively. Our statistical analysis suggests that faced with AI-fueled competitive threats, companies are twice as likely to embrace AI as they were to adopt new technologies in past technology cycles.3
Competing in the AI economy: An interview with MIT’s Andrew McAfee
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AI has arrived, but are companies ready for it? According to an MIT scientist, executives are underestimating the speed, scope, and scale of the disruption it will bring.
It’s not just some far-off dream anymore. The promises and practical applications of artificial intelligence (AI) are here. In this interview with Andrew McAfee, principal research scientist at the Massachusetts Institute of Technology (MIT) and cofounder of the MIT Initiative on the Digital Economy, he explains how AI, and machine learning in particular, is quickly disrupting companies’ economic models, strategy, culture, and even the very nature of how they are structured and run. But there are opportunities for companies that can answer the call—and meet the needs and wants of consumers. An edited transcript of McAfee’s remarks follows.
Today’s digital disruption: Overstated or underappreciated? There are billions of people walking around with a supercomputer, by the standards of a generation ago, in their pocket. Those devices are connected to each other and to this thing that we call the Internet. And then, just within the past five or six years at most, all the promises made by the artificial-intelligence community have started to be delivered on. Den Rest des Beitrags lesen »
Artificial intelligence is a moving target. Here’s how to take better aim.
Artificial intelligence (AI) seems to be everywhere. We experience it at home and on our phones. Before we know it—if entrepreneurs and business innovators are to be believed—AI will be in just about every product and service we buy and use. In addition, its application to business problem solving is growing in leaps and bounds. And at the same time, concerns about AI’s implications are rising: we worry about the impact of AI-enabled automation on the workplace, employment, and society.
A reality sometimes lost amid both the fears and the headline triumphs, such as Alexa, Siri, and AlphaGo, is that the AI technologies themselves—namely, machine learning and its subset, deep learning—have plenty of limitations that will still require considerable effort to overcome. This is an article about those limitations, aimed at helping executives better understand what may be holding back their AI efforts. Along the way, we will also highlight promising advances that are poised to address some of the limitations and create a new wave of opportunities.
Reformers are trying to make up for generations of neglect
EVERY three months, Shahbaz Sharif, the chief minister of Punjab, gathers education officials around a large rectangular table. The biggest of Pakistan’s four provinces, larger in terms of population (110m) than all but 11 countries, Punjab is reforming its schools at a pace rarely seen anywhere in the world. In April 2016, as part of its latest scheme, private providers took over the running of 1,000 of the government’s primary schools. Today the number is 4,300. By the end of this year, Mr Sharif has decreed, it will be 10,000. The quarterly “stocktakes” are his chance to hear what progress is being made towards this and other targets—and whether the radical overhaul is having any effect.
For officials it can be a tough ride. Leaders of struggling districts are called to Lahore for what Allah Bakhsh Malik, Punjab’s education secretary, calls a “pep talk”. Asked what that entails, he responds: “Four words: F-I-R-E. It is survival of the fittest.” About 30% of district heads have been sacked for poor results in the past nine months, says Mr Malik. “We are working at Punjabi speed.” Den Rest des Beitrags lesen »
Perhaps the most unique aspect of this technology trend is that digital transformation is being driven from the top, personally mandated by the CEO. This is something new.
In the past 70 years of computing, the world advanced from the vacuum tube to the transistor to the semiconductor, from mainframe computing to minicomputing to personal computing to the Internet. Software evolved from bespoke custom programming to on-premises, packaged enterprise application software and then to software as a service (SaaS)—cloud-resident solutions. Among the fruits: increased productivity and profitability, a lower cost of operation, and economic growth.
I witnessed many of these tech-adoption cycles over the past 30 years. With the promise of performance improvements and productivity increases, such innovations were introduced to industry through the IT organization. Over months or years, and after multiple trials and evaluations, each gained the attention of the chief information officer, who was responsible for technology adoption. The CEO was periodically briefed on the cost and result. Den Rest des Beitrags lesen »
W. Brian Arthur is an external professor at the Santa Fe Institute and a visiting researcher at the System Sciences Lab at PARC (a Xerox company).
We are creating an intelligence that is external to humans and housed in the virtual economy. This is bringing us into a new economic era—a distributive one—where different rules apply.
A year ago in Oslo Airport I checked in to an SAS flight. One airline kiosk issued a boarding pass, another punched out a luggage tag, then a computer screen showed me how to attach it and another where I should set the luggage on a conveyor. I encountered no single human being. The incident wasn’t important but it left me feeling oddly that I was out of human care, that something in our world had shifted. Den Rest des Beitrags lesen »
