A proliferation of smart sensors – about 50 billion of them – will be installed by 2023, transforming nearly everything into a computing device. Data from these sensors, coupled with AI and predictive analytics, will deliver higher efficiencies with better prediction, says C3 IoT CEO Tom Siebel. In a recent interview, this longtime student of computing and CRM pioneer explains what his platform does for large organizations such as the Pentagon and global energy firms and why healthcare will benefit the most:
Medicine today, it’s about rules-based systems, which is a very blunt instrument. But tomorrow we’ll know what’s going to happen. We’ll be able to take care of people now, with preventative measures, rather than on the surgical operating table later, when the disease is far too advanced. The socio-economic implications of that are huge.
At our Spring BoardExcellence Meeting, we heard how companies can go on the offensive in assessing digital risk. Where should management start? By mapping critical assets, says cybersecurity expert Daniel Miessler, who observes that very few businesses do this comprehensively. In fact, Miessler thinks hiring people to maintain a real-time list of assets could save organizations money:
If we want to make a real difference in security, let’s get the entire industry to use a single metric: the accuracy and freshness of the Asset & Data Inventory. … Now put in every security leader’s deck that the goal is to get to 95% accuracy with daily/weekly updates within 6 months. And the cost is simply hiring 1-3 people who are dedicated to this task. That would reduce breaches, and it would cost infinitely less than the dumpster fire of products we constantly purchase and deploy for millions of dollars a year.
If millions are spent on defense, what is the true cost of a cyberbreach to a company? A team of economists studied 150 disclosed cyberattacks to quantify the actual effect on a firm’s bottom line. In Bloomberg, Peter Orszag dissects the findings:
The average loss in market capitalization following an attack is about 1 percent, with larger losses when personal financial information is involved and smaller losses when that’s not the case. On average, a hack involving personal financial information generates a loss of a little under $1.5 billion in market value.
What behaviors signal declining CEO performance? Deflection, disengagement from execution, and protecting obstructionist executive team members, says board advisor Ram Charan, who spoke at our G100 Next Generation Leadership meeting earlier this month. Charan offers board directors useful guidance on how to proactively investigate these concerns:
Directors should gather four kinds of data: consumer-related information (such as the rate of market erosion, or the average purchase size compared with that of the past); causes of margin decline, especially gross margins; data related to execution, such as delays in product launches; and data on talent, such as turnover statistics. … This inquiry goes beyond most boardroom presentations, showcasing not just the numbers but relevant nonfinancial information.
Genuine transparency between the board and management is more often wish than reality – but not at Netflix. CEO Reed Hastings invites directors to observe monthly and quarterly senior management meetings and offers full access to internal systems. Hastings also revamped the quarterly board memo, now a 20 to 40-page narrative with embedded links to supporting data and analysis. In his words:
The memo is shared among all the VPs, the top 90 executives, and so it’s a way of alignment because I backbone it and captain it, but there are a bunch of sections written by the specialist in the functions. That is shared, the whole management team reads this, and they all have access to the board memo. … Directors then have full-view rights across the company’s documents, so they just click and explore and click and explore to see the analysis of various programs. It’s all interconnected.
Automation? Think again. Trade policy had the greatest impact on job displacement in US manufacturing, with evidence showing the decline correlates directly with China’s entry into the WTO. Groundbreaking – and largely overlooked – research from Upjohn Institute economist Susan Houseman reveals how policymakers missed the real story of productivity gains because the computer and electronic sector profoundly skewed industry
The research evidence points to trade and globalization as the major factors behind the large and swift decline of manufacturing employment in the 2000s. The collapse was not simply part of a long-term trend of decline in manufacturing’s employment share. And although manufacturing processes continue to be automated, there is no evidence that the pace of automation in the sector accelerated in the 2000s; if anything, research comes to the opposite conclusion.
Hospitals, utilities, and transportation providers in China are deploying government-backed brain surveillance programs at scale, directly monitoring employees’ emotional and mental states using AI. South China Morning Post details what this looks like in practice:
Deayea, a technology company in Shanghai, said its brain monitoring devices were worn regularly by train drivers working on the Beijing-Shanghai high-speed rail line, one of the busiest of its kind in the world. The sensors, built in the brim of the driver’s hat, could measure various types of brain activities, including fatigue and attention loss with an accuracy of more than 90 per cent, according to the company’s website. If the driver dozed off, for instance, the cap would trigger an alarm in the cabin to wake him up.
China’s relentless data collection march may not be as valuable as anticipated, counters Pedro Domingos, a machine learning advocate, computer science professor, and bestselling author of The Master Algorithm. Domingos explains why he is less optimistic about the benefits of China’s AI strategy:
China’s advantage is the huge data pool which fuels machine learning. Europe’s advantage is the diversity of its people. If I had to choose between Europe or China as the pool of data to learn from I might choose Europe because in China, the data are often more homogeneous and redundant. … The quality and security of data may [also] be lower – even if the volume is much bigger.
Earlier this month, G100 Companies hosted a dinner for CEOs, board directors, and executives with noted economist and author Tyler Cowen. Our wide-ranging conversation touched on the link between productivity and mobility, the state of autonomous driving, and the stagnant US service sector. You can read our brief summary here. An excerpt:
Life expectancy has fallen for two consecutive years. This decline is the first of its kind in the U.S. since the 1960s. Opioids alone do not explain this rise in mortality, yet the crisis will likely pull life expectancy down for a third consecutive year. Our current state puts us closer to Costa Rica and Turkey than Britain and France.