The Real-Time Computer Complex (RTCC) is located at the NASA Mission Control Center in Houston, TX.
In 1962, the RTCC housed several IBM large-scale data processing mainframe digital computers.
Think of the RTCC as the computing brain that processes mountains of data to guide nearly every portion of a NASA spaceflight mission. Flight controllers and engineers in the Mission Control Center depended on the RTCC.
On April 11, 1970, a portion of the Apollo 13 command service module exploded while it was halfway to the moon. Numerous voices from flight controllers in the Mission Control room desperately attempted to ascertain how serious the situation was while communicating with the astronauts aboard the Apollo 13 command module.
NASA Flight Director Gene Kranz directs his Mission Control team by clearly and firmly saying, “OK, listen up … Quiet down, people. Procedures, I need another computer up in the RTCC.”
The quick thinking and resourcefulness of NASA flight controllers and engineers, along with the courage and professionalism of the Apollo 13 astronauts, resulted in their safe return to earth.
Credit for their safe return should also be acknowledged to the five high-performance IBM System/360 Model 75 computers in the RTCC.
About 16 years earlier, the 1954 IBM 704 digital mainframe computer operated using a low-level assembly language and a high-speed magnetic core storage memory, replacing the electrostatic tube storage used in previous IBM computers.
In 1957, Sputnik 1, Earth’s first artificial satellite, was tracked during its orbit around the planet by two IBM 704 computers.
In 1959, the IBM 1401 mainframe computer was built using a high-level programming language with FORTRAN (Formula Translation/Translator) computer language coding system created by IBM programmer John Backus in 1957 and tested on the IBM 704.
Backus said FORTRAN took what had previously required 1,000 machine statement instructions to be written in only 47 statements, significantly increasing computer programmer productivity.
In 1961, NASA launched two crewed Mercury suborbital flights. IBM 7090 computers installed in NASA Ames Research Center assisted engineers and mission flight controllers by quickly performing thousands of calculations per second.
The 1965 NASA Gemini spacecraft’s 59-pound onboard digital guidance computer was manufactured by IBM. It used a 7.143-hertz processor clock and could execute more than 7,000 calculations per second.
In 1969, IBM’s computer reliability was credited with keeping Apollo 12 on its proper trajectory after a potentially catastrophic event.
On Nov. 14, 1969. About 37 seconds after the Apollo 12 Saturn V rocket left the launchpad from Cape Canaveral, two lightning bolts struck it, knocking out all of the command module’s onboard instrumentation systems and telemetry with Mission Control in Houston.
“What the hell was that?” shouted Apollo 12 command module pilot Richard Gordon after lightning struck the Saturn V rocket traveling at 6,000 mph.
Fortunately, two-way radio communications were still functioning between Mission Control and the command module spacecraft.
“I just lost the whole platform,” Apollo 12 mission commander Charles Conrad Jr. radioed Mission Control. “We had everything in the world drop out,” he added.
The static discharge from the lightning caused a voltage outage, knocking out most of the Apollo 12 command module control systems, including the disconnection of its vital telemetry communications link with Mission Control.
Loud, overlapping voices could be heard in Mission Control as engineers and flight controllers worked on what course of action to take.
Fortunately, the Apollo 12 Saturn V rocket did not deviate from its planned trajectory. Instead, the IBM 60-pound Launch Vehicle Digital Computer (LVDC) housed inside the Instrument Unit section of the rocket’s third stage contained the required processing power to continue the Saturn V’s programmed course.
Meanwhile, Mission Control engineers saw strange data pattern readings on their control screens and desperately worked to find a solution.
NASA Mission flight controller and engineer John Aron recalled similar data patterns during simulation tests. He remembered it meant the Signal Conditioning Electronics were down.
“Flight, try SCE to AUX,” Aaron recommended to Mission Flight Director Gerry Griffin.
Griffin instructed the recommendation to be radioed to the astronauts in the command module.
One minute after the lightning strike, Mission Control radioed the astronauts in the Apollo 12 command module with the following:
“Apollo 12, Houston. Try SCE to Auxiliary. Over.”
There was a brief pause as the astronauts heard what they thought was the acronym “FCE” instead of “SCE.”
“Try FCE to Auxiliary. What the hell is that?” Conrad questioned Mission Control.
“SCE – SCE to Auxiliary,” Mission Control slowly repeated with emphasis.
Apollo 12 pilot astronaut Alan Bean was familiar with the SCE switch inside the command module. So, turning around in his seat, he flipped SCE to AUX, which restored and normalized the command module instrumentation data and telemetry transmissions.
Apollo 12 was able to complete its mission to the moon, thanks in significant part to the reliability of the IBM LVDC and, of course, Aaron’s “SCE to AUX.”
In 1962, science fiction writer Arthur C. Clarke witnessed a demonstration in Bell Labs where its scientists used the IBM 7094 computer to create a synthesized human voice singing the song “Daisy Bell (Bicycle Built for Two).”
This demonstration by the IBM computer inspired Clarke to write a much-remembered scene in the 1968 science fiction movie “2001: A Space Odyssey” featuring the somewhat sentient “Heuristically programmed ALgorithmic” computer known as the HAL 9000.
In the movie, the HAL 9000 computer is singing “Daisy Bell (Bicycle Built for Two)” while deactivating to inoperability as astronaut David Bowman removes its computing modules.
For the record, the HAL 9000 was not an IBM computer.
Wendy Chen is the CEO of Omnistream, a retail automation company helping retailers bring joy to consumers
Every innovator, at some point, faces the same challenge. You’ve built a revolutionary mousetrap, but you need to convince people to actually take a chance on your product—and stop using whatever solution they’re currently using to keep the rodent population under control.
That’s a tough sell because, by definition, your new product is unproven. Even if you’ve been around a while and you have a clear record of success, and even if you can show how much ROI your product will generate on paper, customers quite reasonably worry about the potential for things to go wrong.
To drive things forward, it’s important to build your sales pipeline—and even your product itself—with your customers’ pain points in mind. Here are five ways to convince your customers to bet on innovation and take a chance on your product:
Understand The Friction
It isn’t enough to show your buyer that your product is better than the alternative. You need to understand and account for the friction that keeps them from wanting to make changes. That isn’t just conservatism—it’s a rational disinclination toward any sort of change.
Some industries, some companies and some product categories bring more inherent friction than others. It’s up to you to understand that and find ways to lubricate the wheels and create momentum for change.
Minimize The Risk
The biggest source of friction, of course, is the risk inherent in trying something new. If there’s a working product in place, then making any change brings a non-zero chance that things will stop working—and that usually ends with someone getting fired. Understandably, people in positions to make these decisions often prioritize minimizing risk rather than maximizing value, and it’s up to you to account for that fact.
One smart approach: Instead of trying to sell customers on a widespread rollout, offer to run a low-cost, low-risk pilot project. My company is a retail tech solutions vendor, and we often use pilot projects or small-scale tests with a handful of stores across one or two product categories to convince potential customers to try us out. We then measure their incremental growth and resulting store-level profitability having used our solutions against control stores.
Keep Costs Low
Nobody wants to spend money on unproven technology, and no matter how great your product, every customer will view it as unproven until they’ve seen it delivering consistent results for their specific use-case. Finding creative ways to keep costs low, especially during the early stages, is vital.
Some SaaS companies now use consumption-based pricing, rather than regular monthly subscriptions, to reassure customers they’ll only pay for what they use. Others, like my company, peg our price to the increased performance we deliver. It's important to do everything necessary to make sure your retail clients succeed, so they know they’re always coming out ahead.
It’s also important to ensure your product plays nicely with legacy infrastructure and is complementary to your existing investments: It doesn’t matter how great your product is if it requires your customer to completely rebuild their backend IT or POS systems. Simple integration into your existing core systems ensures a speedy execution. Another great option is to offer a modular offering, which allows customers to choose only the processes they want to ensure full integration into your entire existing supply chain, retail planning and forecasting systems.
Help Your Advocates Communicate Your Value
As the saying goes, nobody gets fired for buying IBM. Your goal during the pilot project is to develop advocates for your product—people at all levels, from end-user to the C suite—who are willing to stick their necks out and say your product is worth implementing more broadly.
To do that, you need to ensure you’re delivering at all levels of the organization: Change management support for the implementation team, a streamlined experience for users, real benefits (results) for their supervisors and clear metrics that document your product’s value and allow it to be easily communicated up the command chain.
Make Your Pilot Scalable
Once you’ve secured buy-in for your product, you need to be able to communicate a clear strategy for scaling up the pilot and delivering broader value. This needs to be baked into the DNA of your pilot: If you’ve focused on a handful of stores for one to two product categories, for instance, then make it easy to add a couple more stores or categories—or quickly scale up and add entire regions.
For bonus points, make your product more valuable as it scales. You’ve shown your product works across a couple of locations—but can you offer additional learnings and customer insights as you bring more locations into your network? You’ll also need to show willingness to customize your product in order to serve your customers’ unique needs and fringe cases and stay aligned with their own strategy for growth, so they’re motivated to lean into the relationship as they expand.
We’re raised to view innovators as mavericks—people who think differently and change the world by the sheer force of their creativity and contrarianism. But the reality is that innovation is a team sport, and it’s only by convincing other people to join your mission that you’ll be able to win top-to-bottom buy-in and truly bring your product to scale. To succeed as B2B software innovators, we need to spend as much time thinking about how to turn our customers into innovators as we do on planning our own innovations.
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A survey by IBM Security has revealed that data breaches are higher-impact and costlier than ever before, with the global average reaching an all-time high of $4.35 million.
Conducted on behalf of IBM by the Poneman Institute, the 2022 Cost of a Data Breach Report was based on in-depth analysis of real-world data breaches experienced by 550 organisations globally between March 2021 and March 2022.
The report showed breach costs rising by nearly 13 per cent over the past two years, with the results suggesting the incidents may also be contributing to the rising costs of goods and services, with 60 per cent of surveyed organisations reportedly having raised their product or services prices due to a breach.
The survey also showed that 83 per cent of those studied had experienced more than one data breach in their lifetime. Another factor shown to be rising over time was the aftereffects of breaches lingering long after they occur, with 50 per cent of breach costs incurred more than a year after a breach.
Other key findings of the report revealed that ransomware victims who decide to pay threat actors’ random demands only incurred $610,000 less in breach costs than those who chose not to pay.
The study shows that 80 per cent of critical infrastructure organisations studied don’t adopt ‘zero trust’ strategies, seeing average breach costs rise to $5.4 million – a $1.17 million increase compared with those who do.
Immature cloud security practices in clouds – with 43 per cent reporting only being in the early stages of applying security measures to the cloud - resulted in $660,000 higher breach costs on average than organisations with mature security across their cloud environments.
Commenting on the report, Charles Henderson, global head of IBM security X-force, said: “This report shows that the right strategies coupled with the right technologies can help make all the difference when businesses are attacked.”
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Could artificial intelligence (AI) help companies meet growing expectations for environmental, social and governance (ESG) reporting?
Certainly, over the past couple of years, ESG issues have soared in importance for corporate stakeholders, with increasing demands from investors, employees and customers. According to S&P Global, in 2022 corporate boards and government leaders “will face rising pressure to demonstrate that they are adequately equipped to understand and oversee ESG issues — from climate change to human rights to social unrest.”
ESG investing, in particular, has been a big part of this boom: Bloomberg Intelligence found that ESG assets are on track to exceed $50 trillion by 2025, representing more than a third of the projected $140.5 trillion in total global assets under management. Meanwhile, ESG reporting has become a top priority that goes beyond ticking off regulatory boxes. It’s used as a tool to attract investors and financing, as well as to meet expectations of today’s consumers and employees.
But according to a exact Oracle ESG global study, 91% of business leaders are currently facing major challenges in making progress on sustainability and ESG initiatives. These include finding the right data to track progress, and time-consuming manual processes to report on ESG metrics.
“A lot of the data that needs to be collected either doesn’t exist yet or needs to come from many systems,” said Sem J. de Spa, senior manager of digital risk solutions at Deloitte. “It’s also way more complex than just your company, because it’s your suppliers, but also the suppliers of your suppliers.”
That is where AI has increasingly become part of the ESG equation. AI can help manage data, glean data insights, operationalize data and report against it, said Christina Shim, VP of strategy and sustainability, AI applications software at IBM.
“We need to make sure that we’re gathering the mass amounts of data when they’re in completely different silos, that we’re leveraging that data to Excellerate operations within the business, that we’re reporting that data to a variety of stakeholders and against a very confusing landscape of ESG frameworks,” she said.
According to Deloitte, although a BlackRock survey found that 92% of S&P companies were reporting ESG metrics by the end of 2020, 53% of global respondents cited “poor quality or availability of ESG data and analytics” and another 33% cited “poor quality of sustainability investment reporting” as the two biggest barriers to adopting sustainable investing.
Making progress is a must, experts say. Increasingly, these ESG and sustainability commitments are no longer simply nice to have,” said Shim. “It’s really becoming kind of like a basis of what organizations need to be focused on and there are increasingly higher standards that have to be integrated into the operations of all businesses,” she explained.
“The challenge is huge, especially as new regulations and standards emerge and ESG requirements are under more scrutiny,” said De Spa. This has led to hundreds of technology vendors flooding the market that use AI to help tackle these issues. “We need all of them, at least a lot of them, to solve these challenges,” he said.
On top of the operational challenges around ESG, the Oracle study found 96% of business leaders admit human bias and emotion often distract from the end ESG goals. In fact, 93% of business leaders say they would trust a bot over a human to make sustainability and social decisions.
“We have people who are coming up now who are hardwired for ESG,” Pamela Rucker, CIO advisor, instructor for Harvard Professional Development, who helped put together the Oracle study. “The idea that they would trust a computer isn’t different for them. They already trust a computer to guide them to work, to provide them directions, to tell them where the best prices are.”
But, she added, humans can work with technology to create more meaningful change and the survey also found that business leaders believe there is still a place for humans in ESG efforts, including managing making changes (48%), educating others (46%), and making strategic decisions (42%).
“Having a machine that might be able to sift through some of that data will allow the humans to come in and look at places where they can add some context around places where we might have some ambiguity, or we might have places where there’s an opportunity,” said Rucker. “AI gives you a chance to see more of that data, and you can spend more time trying to come up with the insights.”
Seth Dobrin, chief AI officer at IBM, told VentureBeat that companies should get started now on using AI to harness ESG data. “Don’t wait for additional regulations to come,” he said.
Getting a handle on data is essential as companies begin their journey towards bringing AI technologies into the mix. “You need a baseline to understand where you are, because you can make all the goals and imperatives, you can commit to whatever you want, but until you know where you are, you’re never gonna figure out how to get to where you need to get to,” he said.
Dobrin said he also sees organizations moving from a defensive, risk management posture around ESG to a proactive approach that is open to AI and other technologies to help.
“It’s still somewhat of a compliance exercise, but it’s shifting,” he said. “Companies know they need to get on board and think proactively so that they are considered a thought leader in the space and not just a laggard doing the bare minimum.”
One of the key areas IBM is focusing on, he added, is helping clients connect their ESG data and the data monitoring with the genuine operations of the business.
“If we’re thinking about business facilities and assets, infrastructure and supply chain as something that’s relevant across industries, all the data that’s being sourced needs to be rolled up and integrated with data and process flows within the ESG reporting and management piece,” he said. “You’re sourcing the data from the business.”
Deloitte recently partnered with Signal AI, which offers AI-powered media intelligence, to help the consulting firm’s clients spot and address provider risks related to ESG issues.
“With the rise of ESG and as businesses are navigating a more complex environment than ever before, the world has become awash in unstructured data,” said David Benigson, CEO of Signal AI. “Businesses may find themselves constantly on the back foot, responding to these issues reactively rather than having the sort of data and insights at their fingertips to be at the forefront.”
The emergence of machine learning and AI, he said, can fundamentally address those challenges. “We can transform data into structured insights that help business leaders and organizations better understand their environment and get ahead of those risks, those threats faster, but also spot those opportunities more efficiently too – providing more of an outside-in perspective on issues such as ESG.”
He pointed to exact backlash around “greenwashing,” including by Elon Musk (who called ESG a “scam” because Tesla was removed from S&P 500’s ESG Index). “There are accusations that organizations are essentially marking their own homework when it comes to sorting their performance and alignment against these sorts of ESG commitments,” he said. “At Signal, we provide the counter to that – we don’t necessarily analyze what the company says they’re going to do, but what the world thinks about what that company is doing and what that company is actually doing in the wild.”
Deloitte’s de Spa said the firm uses Signal AI for what it calls a “responsible value chain” – basically, provider risk management.
“For example, a sustainable organization that cleans oceans and rivers from all kinds of waste asked us to help them get more insight into their own value chain,” he said. “They have a small number of often small suppliers they are dependent on and you cannot easily keep track of what they’re doing.” With Signal AI, he explained, Deloitte can follow what is happening with those companies to identify if there are any risks – if they are no longer able to deliver, for example, if there is a scandal that puts them out of business, or if the company is causing issues related to sustainability.”
In one case, Deloitte discovered a company that was not treating their workers fairly. “You can definitely fight greenwashing because you can see what is going on,” he said. “You can leverage millions of sources to identify what is really happening.”
As sustainability and other ESG-related regulations begin to proliferate around the world, AI and smart technology will continue to play a crucial role, said Deloitte’s de Spa. “It’s not just about carbon, or even having a responsible value chain that has a net zero footprint,” he said. “But it’s also about modern slavery and farmers and other social types of things that companies will need to report on in the next few years.”
Going forward, a key factor will be how to connect and integrate data together using AI, said IBM’s Dobrin. “Many offer a carbon piece or sell AI just for energy efficiency or supply chain transparency,” he said. “But you need to connect all of it together in a one-stop-shop, that will be a total game-changer in this space.”
No matter what, said Rucker, there is certainly going to be more for AI-driven tools to measure when it comes to ESG. “One of the reasons I get excited about this is because it’s not just about a carbon footprint anymore, and those massive amounts of data mean you’re going to have to have heavy lifting done by a machine,” she said. “I see an ESG future where the human needs the machine and the machine needs the human. I don’t think that they can exist without each other.”
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I've written many times about having joined the investment industry in 1969 when the "Nifty Fifty" stocks were in full flower. My first employer, First National City Bank, as well as many of the other "money-center banks" (the leading investment managers of the day), were enthralled with these companies, with their powerful business models and flawless prospects. Sentiment surrounding their stocks was uniformly positive, and portfolio managers found great safety in numbers. For example, a common refrain at the time was "you can't be fired for buying IBM," the era's quintessential growth company.
I've also written extensively about the fate of these stocks. In 1973-74, the OPEC oil embargo and the resultant recession took the S&P 500 Index down a total of 47%. And many of the Nifty Fifty, for which it had been thought that "no price was too high," did far worse, falling from peak p/e ratios of 60-90 to trough multiples in the single digits. Thus, their devotees lost almost all of their money in the stocks of companies that "everyone knew" were great. This was my first chance to see what can happen to assets that are on what I call "the pedestal of popularity."
In 1978, I was asked to move to the bank's bond department to start funds in convertible bonds and, shortly thereafter, high yield bonds. Now I was investing in securities most fiduciaries considered "uninvestable" and which practically no one knew about, cared about, or deemed desirable... and I was making money steadily and safely. I quickly recognized that my strong performance resulted in large part from precisely that fact: I was investing in securities that practically no one knew about, cared about, or deemed desirable. This brought home the key money-making lesson of the Efficient Market Hypothesis, which I had been introduced to at the University of Chicago Business School: If you seek superior investment results, you have to invest in things that others haven't flocked to and caused to be fully valued. In other words, you have to do something different.
In 2006, I wrote a memo called Dare to Be Great. It was mostly about having high aspirations, and it included a rant against conformity and investment bureaucracy, as well as an assertion that the route to superior returns by necessity runs through unconventionality. The element of that memo that people still talk to me about is a simple two-by-two matrix:
|Conventional Behavior||Unconventional Behavior|
|Favorable Outcomes||Average good results||Above average results|
|Unfavorable Outcomes||Average bad results||Below average results|
Here's how I explained the situation:
Of course, it's not easy and clear-cut, but I think it's the general situation. If your behavior and that of your managers are conventional, you're likely to get conventional results - either good or bad. Only if the behavior is unconventional is your performance likely to be unconventional... and only if the judgments are superior is your performance likely to be above average.
The consensus opinion of market participants is baked into market prices. Thus, if investors lack the insight that is superior to the average of the people who make up the consensus, they should expect average risk-adjusted performance.
Many years have passed since I wrote that memo, and the investing world has gotten a lot more sophisticated, but the message conveyed by the matrix and the accompanying explanation remains unchanged. Talk about simple - in the memo, I reduced the issue to a single sentence: "This just in: You can't take the same actions as everyone else and expect to outperform."
The best way to understand this idea is by thinking through a highly logical and almost mathematical process (greatly simplified, as usual, for illustrative purposes):
A certain (but unascertainable) number of dollars will be made over any given period by all investors collectively in an individual stock, a given market, or all markets taken together. That amount will be a function of (a) how companies or assets fare in fundamental terms (e.g., how their profits grow or decline) and (b) how people feel about those fundamentals and treat asset prices.
On average, all investors will do average.
If you're happy doing average, you can simply invest in a broad swath of the assets in question, buying some of each in proportion to its representation in the relevant universe or index. By engaging in average behavior in this way, you're guaranteed average performance. (Obviously, this is the idea behind index funds.)
If you want to be above average, you have to depart from consensus behavior. You have to overweight some securities, asset classes, or markets and underweight others. In other words, you have to do something different.
The challenge lies in the fact that (a) market prices are the result of everyone's collective thinking and (b) it's hard for any individual to consistently figure out when the consensus is wrong and an asset is priced too high or too low.
Nevertheless, "active investors" place active bets in an effort to be above average.
Investor A decides stocks as a whole are too cheap, and he sells bonds in order to overweight stocks. Investor B thinks stocks are too expensive, so she moves to an underweighting by selling some of her stocks to Investor A and putting the proceeds into bonds.
Investor X decides a certain stock is too cheap and overweights it, buying from investor Y, who thinks it's too expensive and therefore wants to underweight it.
It's essential to note that in each of the above cases, one investor is right and the other is wrong. Now go back to the first bullet point above: Since the total dollars earned by all investors collectively are fixed in amount, all active bets, taken together, constitute a zero-sum game (or negative-sum after commissions and other costs). The investor who is right earns an above-average return, and by definition, the one who's wrong earns a below-average return.
Thus, every active bet placed in the pursuit of above-average returns carries with it the risk of below-average returns. There's no way to make an active bet such that you'll win if it works but not lose if it doesn't. Financial innovations are often described as offering some version of this impossible bargain, but they invariably fail to live up to the hype.
The bottom line of the above is simple: You can't hope to earn above-average returns if you don't place active bets, but if your active bets are wrong, your return will be below average.
Investing strikes me as being very much like golf, where playing conditions and the performance of competitors can change from day to day, as can the placement of the holes. On some days, one approach to the course is appropriate, but on other days, different tactics are called for. To win, you have to either do a better job than others of selecting your approach or executing on it or both.
The same is true for investors. It's simple: If you hope to distinguish yourself in terms of performance, you have to depart from the pack. But, having departed, the difference will only be positive if your choice of strategies and tactics is correct and/or you're able to execute better.
In 2009, when Columbia Business School Publishing was considering whether to publish my book The Most Important Thing, they asked to see a demo chapter. As has often been my experience, I sat down and described a concept I hadn't previously written about or named. That description became the book's first chapter, addressing one of its most important topics: second-level thinking. It's certainly the concept from the book that people ask me about most often.
The idea of second-level thinking builds on what I wrote in Dare to Be Great. First, I repeated my view that success in investing means doing better than others. All active investors (and certainly money managers hoping to earn a living) are driven by the pursuit of superior returns.
But that universality also makes beating the market a difficult task. Millions of people are competing for each dollar of investment gain. Who'll get it? The person who's a step ahead. In some pursuits, getting up to the front of the pack means more schooling, more time in the gym or the library, better nutrition, more perspiration, greater stamina, or better equipment. But in investing, where these things count for less, it calls for more perceptive thinking... at what I call the second level.
The basic idea behind second-level thinking is easily summarized: In order to outperform, your thinking has to be different and better.
Remember, your goal in investing isn't to earn average returns; you want to do better than average. Thus, your thinking has to be better than that of others - both more powerful and at a higher level. Since other investors may be smart, well-informed, and highly computerized, you must find an edge they don't have. You must think of something they haven't thought of, see things they miss, or bring insight they don't possess. You have to react differently and behave differently. In short, being right may be a necessary condition for investment success, but it won't be sufficient. You have to be more right than others... which by definition means your thinking has to be different.
Having made the case, I went on to distinguish second-level thinkers from those who operate at the first level:
First-level thinking is simplistic and superficial, and just about everyone can do it (a bad sign for anything involving an attempt at superiority). All the first-level thinker needs is an opinion about the future, as in "The outlook for the company is favorable, meaning the stock will go up."
Second-level thinking is deep, complex, and convoluted. The second-level thinker takes a great many things into account:
What is the range of likely future outcomes?
What outcome do I think will occur?
What's the probability I'm right?
What does the consensus think?
How does my expectation differ from the consensus?
How does the current price for the asset comport with the consensus view of the future, and with mine?
Is the consensus psychology that's incorporated in the price too bullish or bearish?
What will happen to the asset's price if the consensus turns out to be right, and what if I'm right?
The difference in workload between first-level and second-level thinking is clearly massive, and the number of people capable of the latter is tiny compared to the number capable of the former.
First-level thinkers look for simple formulas and easy answers. Second-level thinkers know that success in investing is the antithesis of simple.
Speaking about difficulty reminds me of an important idea that arose in my discussions with my son Andrew during the pandemic (described in the memo Something of Value, published in January 2021). In the memo's extensive discussion of how efficient most markets have become in exact decades, Andrew makes a terrific point: "Readily available quantitative information with regard to the present cannot be the source of superior performance." After all, everyone has access to this type of information - with regard to public U.S. securities, that's the whole point of the SEC's Reg FD (for fair disclosure) - and nowadays all investors should know how to manipulate data and run screens.
So, then, how can investors who are intent on outperforming hope to reach their goal? As Andrew and I said on a podcast where we discussed Something of Value, they have to go beyond readily available quantitative information with regard to the present. Instead, their superiority has to come from an ability to:
better understand the significance of the published numbers,
better assess the qualitative aspects of the company, and/or
better divine the future.
Obviously, none of these things can be determined with certainty, measured empirically, or processed using surefire formulas. Unlike present-day quantitative information, there's no source you can turn to for easy answers. They all come down to judgment or insight. Second-level thinkers who have better judgment are likely to achieve superior returns, and those who are less insightful are likely to generate inferior performance.
This all leads me back to something Charlie Munger told me around the time The Most Important Thing was published: "It's not supposed to be easy. Anyone who finds it easy is stupid." Anyone who thinks there's a formula for investing that guarantees success (and that they can possess it) clearly doesn't understand the complex, dynamic, and competitive nature of the investing process. The prize for superior investing can amount to a lot of money. In the highly competitive investment arena, it simply can't be easy to be the one who pockets the extra dollars.
There's a concept in the investing world that's closely related to being different: contrarianism. "The investment herd" refers to the masses of people (or institutions) that drive security prices one way or the other. It's their actions that take asset prices to bull market highs and sometimes bubbles and, in the other direction, to bear market territory and occasional crashes. At these extremes, which are invariably overdone, it's essential to act in a contrary fashion.
Joining in the swings described above causes people to own or buy assets at high prices and to sell or fail to buy at low prices. For this reason, it can be important to part company with the herd and behave in a way that's contrary to the actions of most others.
Contrarianism received its own chapter in The Most Important Thing. Here's how I set forth the logic:
Markets swing dramatically, from bullish to bearish, and from overpriced to underpriced.
Their movements are driven by the actions of "the crowd," "the herd," and "most people." Bull markets occur because more people want to buy than sell, or the buyers are more highly motivated than the sellers. The market rises as people switch from being sellers to being buyers, and as buyers become even more motivated and the sellers less so. (If buyers didn't predominate, the market wouldn't be rising.)
Market extremes represent inflection points. These occur when bullishness or bearishness reaches a maximum. Figuratively speaking, a top occurs when the last person who will become a buyer does so. Since every buyer has joined the bullish herd by the time the top is reached, bullishness can go no further, and the market is as high as it can go. Buying or holding is dangerous.
Since there's no one left to turn bullish, the market stops going up. And if the next day one person switches from buyer to seller, it will start to go down.
So at the extremes, which are created by what "most people" believe, most people are wrong.
Therefore, the key to investment success has to lie in doing the opposite: in diverging from the crowd. Those who recognize the errors that others make can profit enormously from contrarianism.
To sum up, if the extreme highs and lows are excessive and the result of the concerted, mistaken actions of most investors, then it's essential to leave the crowd and be a contrarian.
In his 2000 book, Pioneering Portfolio Management, David Swensen, the former chief investment officer of Yale University, explained why investing institutions are vulnerable to conformity with current consensus belief and why they should instead embrace contrarianism. (For more on Swensen's approach to investing, see "A Case in Point" below.) He also stressed the importance of building infrastructure that enables contrarianism to be employed successfully:
Unless institutions maintain contrarian positions through difficult times, the resulting damage imposes severe financial and reputational costs on the institution.
Casually researched, consensus-oriented investment positions provide the little prospect for producing superior results in the intensely competitive investment management world.
Unfortunately, overcoming the tendency to follow the crowd, while necessary, proves insufficient to guarantee investment success... While courage to take a different path enhances chances for success, investors face likely failure unless a thoughtful set of investment principles undergirds the courage.
Before I leave the subject of contrarianism, I want to make something else very clear. First-level thinkers - to the extent they're interested in the concept of contrarianism - might believe contrarianism means doing the opposite of what most people are doing, so selling when the market rises and buying when it falls. But this overly simplistic definition of contrarianism is unlikely to be of much help to investors. Instead, the understanding of contrarianism itself has to take place at a second level.
In The Most Important Thing Illuminated, an annotated edition of my book, four professional investors and academics provided commentary on what I had written. My good friend Joel Greenblatt, an exceptional equity investor, provided a very apt observation regarding knee-jerk contrarianism: "... just because no one else will jump in front of a Mack truck barreling down the highway doesn't mean that you should." In other words, the mass of investors aren't wrong all the time, or wrong so dependably that it's always right to do the opposite of what they do. Rather, to be an effective contrarian, you have to figure out:
what the herd is doing;
why it's doing it;
what's wrong, if anything, with what it's doing; and
what you should do about it.
Like the second-level thought process laid out in bullet points on page four, intelligent contrarianism is deep and complex. It amounts to much more than simply doing the opposite of the crowd. Nevertheless, good investment decisions made at the best opportunities - at the most overdone market extremes - invariably include an element of contrarian thinking.
There are only so many syllabus I find worth writing about, and since I know I'll never know all there is to know about them, I return to some from time to time and add to what I've written previously. Thus, in 2014, I followed up on 2006's Dare to Be Great with a memo creatively titled Dare to Be Great II. To begin, I repeated my insistence on the importance of being different:
If your portfolio looks like everyone else's, you may do well, or you may do poorly, but you can't do differently. And being different is absolutely essential if you want a chance at being superior...
I followed that with a discussion of the challenges associated with being different:
Most great investments begin in discomfort. The things most people feel good about - investments where the underlying premise is widely accepted, the exact performance has been positive, and the outlook is rosy - are unlikely to be available at bargain prices. Rather, bargains are usually found among things that are controversial, that people are pessimistic about, and that have been performing badly of late.
But then, perhaps most importantly, I took the idea a step further, moving from daring to be different to its natural corollary: daring to be wrong. Most investment books are about how to be right, not the possibility of being wrong. And yet, the would-be active investor must understand that every attempt at success by necessity carries with it the chance for failure. The two are absolutely inseparable, as I described at the top of page three.
In a market that is even moderately efficient, everything you do to depart from the consensus in pursuit of above-average returns has the potential to result in below-average returns if your departure turns out to be a mistake. Overweighting something versus underweighting it; concentrating versus diversifying; holding versus selling; hedging versus not hedging - these are all double-edged swords. You gain when you make the right choice and lose when you're wrong.
One of my favorite sayings came from a pit boss at a Las Vegas casino: "The more you bet, the more you win when you win." Absolutely inarguable. But the pit boss conveniently omitted the converse: "The more you bet, the more you lose when you lose." Clearly, those two ideas go together.
In a presentation I occasionally make to institutional clients, I employ PowerPoint animation to graphically portray the essence of this situation:
A bubble drops down, containing the words "Try to be right." That's what active investing is all about. But then a few more words show up in the bubble: "Run the risk of being wrong." The bottom line is that you simply can't do the former without also doing the latter. They're inextricably intertwined.
Then another bubble drops down, with the label "Can't lose." There are can't-lose strategies in investing. If you buy T-bills, you can't have a negative return. If you invest in an index fund, you can't underperform the index. But then two more words appear in the second bubble: "Can't win." People who use can't-lose strategies by necessity surrender the possibility of winning. T-bill investors can't earn more than the lowest of yields. Index fund investors can't outperform.
And that brings me to the assignment I imagine receiving from unenlightened clients: "Just apply the first set of words from each bubble: Try to outperform while employing can't-lose strategies." But that combination happens to be unavailable.
The above shows that active investing carries a cost that goes beyond commissions and management fees: heightened risk of inferior performance. Thus, every investor has to make a conscious decision about which course to follow. Pursue superior returns at the risk of coming in behind the pack, or hug the consensus position and ensure average performance. It should be clear that you can't hope to earn superior returns if you're unwilling to bear the risk of sub-par results.
And that brings me to my favorite fortune cookie, which I received with dessert 40-50 years ago. The message inside was simple: The cautious seldom err or write great poetry. In my college classes in Japanese studies, I learned about the koan, which Oxford Languages defines as "a paradoxical anecdote or riddle, used in Zen Buddhism to demonstrate the inadequacy of logical reasoning and to provoke enlightenment." I think of my fortune that way because it raises a question I find paradoxical and capable of leading to enlightenment.
But what does the fortune mean? That you should be cautious because cautious people seldom make mistakes? Or that you shouldn't be cautious, because cautious people rarely accomplish great things?
The fortune can be read both ways, and both conclusions seem reasonable. Thus the key question is, "Which meaning is right for you?" As an investor, do you like the idea of avoiding error, or would you rather try for superiority? Which path is more likely to lead to success as you define it, and which is more feasible for you? You can follow either path, but clearly not both simultaneously.
Thus, investors have to answer what should be a very basic question: Will you (a) strive to be above average, which costs money, is far from sure to work, and can result in your being below average, or (b) accept average performance - which helps you reduce those costs but also means you'll have to look on with envy as winners report mouth-watering successes. Here's how I put it in Dare to Be Great II:
How much emphasis should be put on diversifying, avoiding risk, and ensuring against below-pack performance, and how much on sacrificing these things in the hope of doing better?
And here's how I described some of the considerations:
Unconventional behavior is the only road to superior investment results, but it isn't for everyone. In addition to superior skill, successful investing requires the ability to look wrong for a while and survive some mistakes. Thus each person has to assess whether he's temperamentally equipped to do these things and whether his circumstances - in terms of employers, clients and the impact of other people's opinions - will allow it... when the chips are down and the early going makes him look wrong, as it invariably will.
You can't have it both ways. And as in so many aspects of investing, there's no right or wrong, only right or wrong for you.
The aforementioned David Swensen ran Yale University's endowment from 1985 until his passing in 2021, an unusual 36-year tenure. He was a true pioneer, developing what has come to be called "the Yale Model" or "the Endowment Model." He radically reduced Yale's holdings of public stocks and bonds and invested heavily in innovative, illiquid strategies such as hedge funds, venture capital, and private equity at a time when almost no other institutions were doing so. He identified managers in those fields who went on to generate superior results, several of whom earned investment fame. Yale's resulting performance beat almost all other endowments by miles. In addition, Swensen sent out into the endowment community a number of disciples who produced enviable performances for other institutions. Many endowments emulated Yale's approach, especially beginning around 2003-04 after these institutions had been punished by the bursting of the tech/Internet bubble. But few if any duplicated Yale's success. They did the same things, but not nearly as early or as well.
To sum up all the above, I'd say Swensen dared to be different. He did things others didn't do. He did these things long before most others picked up the thread. He did them to a degree that others didn't approach. And he did them with exceptional skill. What a great formula for outperformance.
In Pioneering Portfolio Management, Swensen provided a description of the challenge at the core of investing - especially institutional investing. It's one of the best paragraphs I've ever read and includes a two-word phrase (which I've bolded for emphasis) that for me reads like sheer investment poetry. I've borrowed it countless times:
...Active management strategies demand uninstitutional behavior from institutions, creating a paradox that few can unravel. Establishing and maintaining an unconventional investment profile requires acceptance of uncomfortably idiosyncratic portfolios, which frequently appear downright imprudent in the eyes of conventional wisdom.
As with many great quotes, this one from Swensen says a great deal in just a few words. Let's parse its meaning:
Idiosyncratic - When all investors love something, it's likely their buying will render it highly-priced. When they hate it, their selling will probably cause it to become cheap. Thus, it's preferable to buy things most people hate and sell things most people love. Such behavior is by definition highly idiosyncratic (i.e., "eccentric," "quirky," or "peculiar").
Uncomfortable - The mass of investors take the positions they take for reasons they find convincing. We witness the same developments they do and are impacted by the same news. Yet, we realize that if we want to be above average, our reaction to those inputs - and thus our behavior - should in many instances be different from that of others. Regardless of the reasons, if millions of investors are doing A, it may be quite uncomfortable to do B.
And if we do bring ourselves to do B, our action is unlikely to prove correct right away. After we've sold a market darling because we think it's overvalued, its price probably won't start to drop the next day. Most of the time, the hot asset you've sold will keep rising for a while, and sometimes a good while. As John Maynard Keynes said, "Markets can remain irrational longer than you can remain solvent." And as the old adage goes, "Being too far ahead of your time is indistinguishable from being wrong." These two ideas are closely related to another great Keynes quote: "Worldly wisdom teaches that it is better for the reputation to fail conventionally than to succeed unconventionally." Departing from the mainstream can be embarrassing and painful.
Uninstitutional behavior from institutions - We all know what Swensen meant by the word "institutions": bureaucratic, hidebound, conservative, conventional, risk-averse, and ruled by consensus; in short, unlikely mavericks. In such settings, the cost of being different and wrong can be viewed as highly unacceptable relative to the potential benefit of being different and right. For the people involved, passing up profitable investments (errors of omission) poses far less risk than making investments that produce losses (errors of commission). Thus, investing entities that behave "institutionally" are, by their nature, highly unlikely to engage in idiosyncratic behavior.
Early in his time at Yale, Swensen chose to:
minimize holdings of public stocks;
vastly overweight strategies falling under the heading "alternative investments" (although he started to do so well before that label was created);
in so doing, commit a substantial portion of Yale's endowment to illiquid investments for which there was no market; and
hire managers without lengthy track records on the basis of what he perceived to be their investment acumen.
To use his words, these actions probably appeared "downright imprudent in the eyes of conventional wisdom." Swensen's behavior was certainly idiosyncratic and uninstitutional, but he understood that the only way to outperform was to risk being wrong, and he accepted that risk with great results.
To conclude, I want to describe a exact occurrence. In mid-June, we held the London edition of Oaktree's biannual conference, which followed on the heels of the Los Angeles version. My assigned subject at both conferences was the market environment. I faced a dilemma while preparing for the London conference because so much had changed between the two events: On May 19, the S&P 500 was at roughly 3,900, but by June 21 it was at approximately 3,750, down almost 4% in roughly a month. Here was my issue: Should I update my slides, which had become somewhat dated, or reuse the LA slides to deliver a consistent message to both audiences?
I decided to use the LA slides as the jumping-off point for a discussion of how much things had changed in that short period. The key segment of my London presentation consisted of a stream-of-consciousness discussion of the concerns of the day. I told the attendees that I pay close attention to the questions people ask most often at any given point in time, as the questions tell me what's on people's minds. And the questions I'm asked these days overwhelmingly surround:
the outlook for inflation,
the extent to which the Federal Reserve will raise interest rates to bring it under control, and
whether doing so will produce a soft landing or a recession (and if the latter, how bad).
Afterward, I wasn't completely happy with my remarks, so I rethought them over lunch. And when it was time to resume the program, I went up on stage for another two minutes. Here's what I said:
All the discussion surrounding inflation, rates, and recession falls under the same heading: the short term. And yet:
We can't know much about the short-term future (or, I should say, we can't dependably know more than the consensus).
If we have an opinion about the short term, we can't (or shouldn't) have much confidence in it.
If we reach a conclusion, there's not much we can do about it - most investors can't and won't meaningfully revamp their portfolios based on such opinions.
We really shouldn't care about the short term - after all, we're investors, not traders.
I think it's the last point that matters most. The question is whether you agree or not.
For example, when asked whether we're heading toward a recession, my usual answer is that whenever we're not in a recession, we're heading toward one. The question is when. I believe we'll always have cycles, which means recessions and recoveries will always lie ahead. Does the fact that there's a recession ahead mean we should reduce our investments or alter our portfolio allocation? I don't think so. Since 1920, there have been 17 recessions as well as one Great Depression, a World War and several smaller wars, multiple periods of worry about global cataclysm, and now a pandemic. And yet, as I mentioned in my January memo, Selling Out, the S&P 500 has returned about 10½% a year on average over that century-plus. Would investors have improved their performance by getting in and out of the market to avoid those problem spots... or would doing so have diminished it? Ever since I quoted Bill Miller in that memo, I've been impressed by his formulation that "it's time, not timing" that leads to real wealth accumulation. Thus, most investors would be better off ignoring short-term considerations if they want to enjoy the benefits of long-term compounding.
Two of the six tenets of Oaktree's investment philosophy say (a) we don't base our investment decisions on macro forecasts and (b) we're not market timers. I told the London audience our main goal is to buy debt or make loans that will be repaid and to buy interests in companies that will do well and make money. None of that has anything to do with the short term.
From time to time, when we consider it warranted, we do vary our balance between aggressiveness and defensiveness, primarily by altering the size of our closed-end funds, the pace at which we invest, and the level of risk we'll accept. But we do these things on the basis of current market conditions, not expectations regarding future events.
Everyone at Oaktree has opinions on the short-run phenomena mentioned above. We just don't bet heavily that they're right. During our exact meetings with clients in London, Bruce Karsh and I spent a lot of time discussing the significance of the short-term concerns. Here's how he followed up in a note to me:
...Will things be as bad or worse or better than expected? Unknowable... and equally unknowable how much is priced in, i.e. what the market is truly expecting. One would think a recession is priced in, but many analysts say that's not the case. This stuff is hard...!!!
Bruce's comment highlights another weakness of having a short-term focus. Even if we think we know what's in store in terms of things like inflation, recessions, and interest rates, there's absolutely no way to know how market prices comport with those expectations. This is more significant than most people realize. If you've developed opinions regarding the issues of the day, or have access to those of pundits you respect, take a look at any asset and ask yourself whether it's priced rich, cheap, or fair in light of those views. That's what matters when you're pursuing investments that are reasonably priced.
The possibility - or even the fact - that a negative event lies ahead isn't in itself a reason to reduce risk; investors should only do so if the event lies ahead and it isn't appropriately reflected in asset prices. But, as Bruce says, there's usually no way to know.
At the beginning of my career, we thought in terms of investing in a stock for five or six years; something held for less than a year was considered a short-term trade. One of the biggest changes I've witnessed since then is the incredible shortening of time horizons. Money managers know their returns in real-time, and many clients are fixated on how their managers did in the most exact quarter.
No strategy - and no level of brilliance - will make every quarter or every year a successful one. Strategies become more or less effective as the environment changes and their popularity waxes and wanes. In fact, highly disciplined managers who hold most rigorously to a given approach will tend to report the worst performance when that approach goes out of favor. Regardless of the appropriateness of a strategy and the quality of investment decisions, every portfolio and every manager will experience good and bad quarters and years that have no lasting impact and say nothing about the manager's ability. Often this poor performance will be due to unforeseen and unforeseeable developments.
Thus, what does it mean that someone or something has performed poorly for a while? No one should fire managers or change strategies based on short-term results. Rather than taking capital away from underperformers, clients should consider increasing their allocations in the spirit of contrarianism (but few do). I find it incredibly simple: If you wait at a bus stop long enough, you're guaranteed to catch a bus, but if you run from bus stop to bus stop, you may never catch a bus.
I believe most investors have their eye on the wrong ball. One quarter's or one year's performance is meaningless at best and a harmful distraction at worst. But most investment committees still spend the first hour of every meeting discussing returns in the most exact quarter and the year to date. If everyone else is focusing on something that doesn't matter and ignoring the thing that does, investors can profitably diverge from the pack by blocking out short-term concerns and maintaining a laser focus on long-term capital deployment.
A final quote from Pioneering Portfolio Management does a great job of summing up how institutions can pursue the superior performance most want. (Its concepts are also relevant to individuals):
Appropriate investment procedures contribute significantly to investment success, allowing investors to pursue profitable long-term contrarian investment positions. By reducing pressures to produce in the short run, liberated managers gain the freedom to create portfolios positioned to take advantage of opportunities created by short-term players. By encouraging managers to make potentially embarrassing out-of-favor investments, fiduciaries increase the likelihood of investment success.
Oaktree is probably in the extreme minority in its relative indifference to macro projections, especially regarding the short term. Most investors fuss over expectations regarding short-term phenomena, but I wonder whether they actually do much about their concerns and whether it helps.
Many investors - and especially institutions such as pension funds, endowments, insurance companies, and sovereign wealth funds, all of which are relatively insulated from the risk of sudden withdrawals - have the luxury of being able to focus exclusively on the long term... if they will take advantage of it. Thus, my suggestion to you is to depart from the investment crowd, with its unhelpful preoccupation with the short term, and to instead join us in focusing on the things that really matter.
Editor's Note: The summary bullets for this article were chosen by Seeking Alpha editors.
In April, Jim Hannon ascended to CEO at Altus Group after almost two years as president of Altus Analytics, a subsidiary. He’s looking to continue the company’s long policy of aggressive acquisition of proptech startups that feed its valuation, tax appeal, project management and due diligence platform for real estate investors and owners.
Founded in 2005, the publicly traded, Toronto-based Altus Group was an early proponent of providing real estate technology data as what it calls “intelligence as a service.”
Commercial Observer spoke with Hannon in late July from his home in Naples, Fla., about Altus’ role in the real estate investment and ownership world and about his views on proptech in the near and longer term.
The interview has been edited for length and clarity.
Commercial Observer: With a $2 billion market cap, Altus Group is a huge company in the proptech sector, and one with many services. As CEO, what’s your elevator pitch for Altus?
Jim Hannon: In a nutshell, we’re No. 1 in providing valuations via technology advisory services for commercial real estate. We are the No. 1 or 2 player in the core markets that we serve to make it easier to do tax appeals and have successful outcomes in lowering your taxes and getting better returns out of your assets.
We help developers determine when and where, or if, they should invest. And if they choose to invest, we help them project-manage large investments and development. So those are the things we do: valuation, tax appeal, project management, and due diligence. Our clients are investors, asset managers, developers, lenders, and, for the tax business, property owners.
Is Altus too large, or not large enough, for what you’re trying to accomplish as a technology source for your clients?
That’s an interesting observation. I started my career at IBM, so this doesn’t feel very large to me at all. Actually, it’s a very tight-knit community inside Altus. It came together through acquisitions over the years. But it feels like a tightly focused company from my chair compared to the size of the companies that I’ve been at.
How big is Altus in employees and revenue?
We have 2,600 employees. We’re in a blackout period right at the moment, so I can’t get too specific, but I can tell you that last year we did $625 million Canadian in revenue ($485 million today).
As you mentioned, Altus has grown quite a bit through acquisition. What does that look like these days? Is there more opportunity to acquire proptech startups that fit your platform, or have innovative startup opportunities slowed down?
There’s always opportunity to acquire proptech startups. We keep a close eye on the market, as well as on our capital structure, making sure we’re deploying investments in the right areas.
Last year, we did three significant acquisitions. We purchased a company in Paris called Finance Active. We’re heavily in the valuation business around equity investments in commercial real estate. Finance Active put us into the debt management side of those investments and it significantly increased the size of our international footprint.
In March of last year, we bought a company called Stratodem, which gave us an analytics engine and thousands of macroeconomic data points to pull into our advanced analytics. And, in November, we purchased a company in New York City called Reonomy, which gave us a significant amount of data on about 53 million commercial real estate assets in the U.S. It also gave us the underlying technology to link attributes of assets to the drivers of performance.
This year we purchased a tax technology company called Rethink Solutions, which gave us automated workflow and some predictive analytics capabilities for taxes, as well.
What made those proptech companies attractive to Altus?
On the tax side, we want technology that improves workflow, or improves the predictability of a successful outcome of a tax appeal. In the Canadian market, we’re the No. 1 commercial real estate tax appraisal adviser. So, basically, we help make the process of appealing tax assessment easier. In the U.K., we’re No. 1.
In the U.S., it’s hard to exactly get the size of the market, but our estimate is that we’re No. 2, but still in a single-digit type of market share. It’s a very fragmented market in the U.S. so acquisitions that can help us automate the processes or predict which assets are going to have the highest probability of a successful outcome is interesting technology for us. It allows us to expand our market to clients who want to self-serve, or have a lighter advisory touch if they choose, or if they want to leverage the expertise of our teams.
On the analytics side, our core franchises have been in commercial real estate valuations — mark to market. We are by far the leaders, whether it’s from a technology perspective with our Argus enterprise, our flagship product, or through our advisory services. As we generate valuations, we throw off a tremendous amount of exhaustive data, which allows us to look at the commercial real estate market and say, “OK, what drove performance of various types of assets?”
How do you see the industry in the midst of so much technological change?
The industry is at an inflection point. It feels very similar to me as financial services did over a decade ago, where there’s fantastic technology and expert services to go along with that technology, to say, “What just happened in the market? How do I get a better understanding of what’s going on around me?” The next step is, “Why did that happen?” We can draw correlations using our analytics technology, especially with our exact acquisitions. Then, most importantly, it’s, “What’s going to happen next? Where should I invest? Why should I invest? And how do I think about asset performance across vast portfolios of investments?” That’s where we were going with our acquisitions last year.
What is the most exciting thing you have found in becoming CEO?
It’s the opportunity to be in front of the whole industry. We’re very early in the adoption curve of advanced analytics, in thinking about the investment side of commercial real estate. There are great firms out there, they have their own data strategies, and some of them are significantly larger than we are.
But this is what we do: Investment firms should have data strategies, and we’re here to enable those data strategies for them. Putting together assets like Stratodem with Reonomy to create advanced offers, and pairing them with Argus and our advisory business, and even the data we split off in our tax franchise, there’s no other company in the world that has our data set and the potential to change this industry like we do. And it was just too much fun of an opportunity to pass on.
On the demand side, how do your clients view the adoption of proptech?
They’re hungry for it. If we put it in context of today’s economic situation: When you look at rising interest rates and headwinds, that’s going to change investment theses and the way owners think about how they maximize their return on their assets. They are focused on the tenant experience, as they should be. I think that side of the business has as much potential as our side, the investment and performance management side. There’s so much opportunity to Excellerate the services inside buildings and to bring all sorts of technology to bear in this current economic cycle.
It’s even more important to be thinking about productivity, efficiency and differentiation. The various proptech companies that are out there, they’re all coming at it with some angle on that. I think the owners understand that investments in technology are going to enable their future growth and the best outcomes with their tenants. We’re seeing strong demand. We’re in about 100 markets overall in six core countries — Canada, U.S., U.K., Germany, France and Australia — and we see the addressable market for those six countries alone at about a $5 billion opportunity. When you add in the rest of the world, our model says that globally it’s a $10 billion market.
What kinds of data questions are clients asking Argus about?
The first set of conversations that I had with CXO-level folks in the industry were surprisingly to me about just the core management of data. “How do I harmonize data from investments in three different countries to get a portfolio view?” I understood that problem. If this is where they’re at now, even the most advanced ones are still trying to figure out how do they corral their data and look at it on a country or global basis.
Then think about all the various attributes of performance. That’s a core problem across the industry, and the technology we’re building organically with the acquisitions that we executed last year directly addresses that problem.
Is there any particular sector of real estate that you’re concentrating on for your clients, whether it be construction or office or residential?
There’s a blurring of the lines that happens. We stick to our core strategy, which is commercial real estate. However, as investors are moving into single-family residential rentals as a commercial asset class, that changes our perspective on what is commercial. The legacy definitions don’t necessarily hold if you’re looking at it from an investor perspective. So that’s not where our core strength is, but we’re building up those analytics capabilities.
In our Stratodem acquisition, we actually picked up a tremendous amount of data on macro-residential information, which we built into our models. It informs the performance of commercial real estate assets. Across the classes of commercial real estate, we’re building up data and analytics on all of it. We have our tax practices. We look to target and segment into areas of growth like data centers or green energy.
For the rest of this year, or in the near future, how do you view the adoption and use of technology in real estate, and how will that affect Altus’ strategy?
I have to be careful to not answer a specific question about the rest of the year that could in any way come across as guidance. I’ll talk about the industry in general and our positioning. We’re in a great place. In markets that go up or down, you’re going to have investors either looking to buy or looking to sell. We’ve gone through various economic cycles over the last 15 years, and we are very resilient, because buyers and sellers are looking for that next piece of information to determine what they should do next.
We’ve been there with expert services, information and analytics capabilities, and the adoption of that technology is accelerating. That puts us in a great place as a trusted partner to many of the world’s largest investors.
Philip Russo can be reached at firstname.lastname@example.org.
Autism is known as a spectrum disorder because every autistic person is different, with unique strengths and challenges.
Varney says many autistic people experienced education as a system that focused on these challenges, which can include social difficulties and anxiety.
He is pleased this is changing, with exact reforms embracing autistic students’ strengths.
But the unemployment rate of autistic people remains disturbingly high. ABS data from 2018 shows 34.1 per cent of autistic people are unemployed – three times higher than that of people with any type of disability and almost eight times that of those without a disability.
“A lot of the time people hear that someone’s autistic and they assume incompetence,” says Varney, who was this week appointed the chair of the Victorian Disability Advisory Council.
“But we have unique strengths, specifically hyper focus, great creativity, and we can think outside the box, which is a great asset in workplaces.”
In Israel, the defence force has a specialist intelligence unit made up exclusively of autistic soldiers, whose skills are deployed in analysing, interpreting and understanding satellite images and maps.
Locally, organisations that actively recruit autistic talent include software giant SAP, Westpac, IBM, ANZ, the Australian Tax Office, Telstra, NAB and PricewaterhouseCoopers.
Chris Pedron is a junior data analyst at Australian Spatial Analytics, a social enterprise that says on its website “neurodiversity is our advantage – our team is simply faster and more precise at data processing”.
He was hired after an informal chat. (Australian Spatial Analytics also often provides interview questions 48 hours in advance.)
Pedron says the traditional recruitment process can work against autistic people because there are a lot of unwritten social cues, such as body language, which he doesn’t always pick up on.
“If I’m going in and I’m acting a bit physically standoffish, I’ve got my arms crossed or something, it’s not that I’m not wanting to be there, it’s just that new social interaction is something that causes anxiety.”
Pedron also finds eye contact uncomfortable and has had to train himself over the years to concentrate on a point on someone’s face.
Australian Spatial Analytics addresses a skills shortage by delivering a range of data services that were traditionally outsourced offshore.
Projects include digital farm maps for the grazing industry, technical documentation for large infrastructure and map creation for land administration.
Pedron has always found it easy to map things out in his head. “A lot of the work done here at ASA is geospatial so having autistic people with a very visual mindset is very much an advantage for this particular job.”
Pedron listens to music on headphones in the office, which helps him concentrate, and stops him from being distracted. He says the simpler and clearer the instructions, the easier it is for him to understand. “The less I have to read between the lines to understand what is required of me the better.”
Australian Spatial Analytics is one of three jobs-focused social enterprises launched by Queensland charity White Box Enterprises.
It has grown from three to 80 employees in 18 months and – thanks to philanthropist Naomi Milgrom, who has provided office space in Cremorne – has this year expanded to Melbourne, enabling Australian Spatial Analytics to create 50 roles for Victorians by the end of the year.
Chief executive Geoff Smith hopes they are at the front of a wave of employers recognising that hiring autistic people can make good business sense.
“Rather than focus on the deficits of the person, focus on the strengths. A quarter of National Disability Insurance Scheme plans name autism as the primary disability, so society has no choice – there’s going to be such a huge number of people who are young and looking for jobs who are autistic. There is a skills shortage as it is, so you need to look at neurodiverse talent.”
In 2017, IBM launched a campaign to hire more neurodiverse (a term that covers a range of conditions including autism, Attention Deficit Hyperactivity Disorder, or ADHD, and dyslexia) candidates.
The initiative was in part inspired by software and data quality engineering services firm Ultranauts, who boasted at an event “they ate IBM’s lunch at testing by using an all-autistic staff”.
The following year Belinda Sheehan, a senior managing consultant at IBM, was tasked with rolling out a pilot at its client innovation centre in Ballarat.
“IBM is very big on inclusivity,” says Sheehan. “And if we don’t have diversity of thought, we won’t have innovation. So those two things go hand in hand.”
Sheehan worked with Specialisterne Australia, a social enterprise that assists businesses in recruiting and supporting autistic people, to find talent using a non-traditional recruitment process that included a week-long task.
Candidates were asked to work together to find a way for a record shop to connect with customers when the bricks and mortar store was closed due to COVID.
Ten employees were eventually selected. They started in July 2019 and work in roles across IBM, including data analysis, testing, user experience design, data engineering, automation, blockchain and software development. Another eight employees were hired in July 2021.
Sheehan says clients have been delighted with their ideas. “The UX [user experience] designer, for example, comes in with such a different lens. Particularly as we go to artificial intelligence, you need those different thinkers.”
One client said if they had to describe the most valuable contribution to the project in two words it would be “ludicrous speed”. Another said: “automation genius.”
IBM has sought to make the office more inclusive by creating calming, low sensory spaces.
It has formed a business resource group for neurodiverse employees and their allies, with four squads focusing on recruitment, awareness, career advancement and policies and procedures.
And it has hired a neurodiversity coach to work with individuals and managers.
Sheehan says that challenges have included some employees getting frustrated because they did not have enough work.
“These individuals want to come to work and get the work done – they are not going off for a coffee and chatting.”
Increased productivity is a good problem to have, Sheehan says, but as a manager, she needs to come up with ways they can enhance their skills in their downtime.
There have also been difficulties around different communication styles, with staff finding some autistic employees a bit blunt.
Sheehan encourages all staff to do a neurodiversity 101 training course run by IBM.
“Something may be perceived as rude, but we have to turn that into a positive. It’s good to have someone who is direct, at least we all know what that person is thinking.”
Chris Varney is delighted to see neurodiversity programs in some industries but points out that every autistic person has different interests and abilities.
Some are non-verbal, for example, and not all have the stereotypical autism skills that make them excel at data analysis.
“We’ve seen a big recognition that autistic people are an asset to banks and IT firms, but there’s a lot more work to be done,” Varney says.
“We need to see jobs for a diverse range of autistic people.”
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We saw this play out with President Joe Biden’s bout with COVID-19: It takes longer than you might expect to test negative. Indeed, the CDC found, “Between 5 and 9 days after symptom onset or after initial diagnosis with SARS-CoV-2 infection, 54% of persons had positive SARS-CoV-2 antigen test results.”
The LA Times says the rule of thumb “five days and you are clear” is a misconception:
“If your test turns out to be positive after five days, don’t be upset because the majority of people still test positive until at least Day 7, to Day 10 even,” Dr. Clayton Chau, director of the Orange County Health Care Agency, said during a briefing Thursday. “So that’s the majority. That’s the norm.”
Dr. Robert Kosnik, director of UC San Francisco’s occupational health program, said at a campus town hall in July that there’s an expectation people will test negative on Day 5 and can return to work the next day.
“Don’t get your hopes up,” Kosnik told his colleagues. “Don’t be disappointed if you’re one of the group that continues to test positive.”
In fact, some 60% to 70% of infected people still test positive on a rapid test five days after the onset of symptoms or their first positive test, meaning they should still stay in isolation, Kosnik said.
“It doesn’t significantly fall off until Day 8,” he said.
The California Department of Health gives clear guidance on what to do once you test positive for COVID-19:
If you test positive or have symptoms of COVID-19, you should stay away from others, even at home and even if you have been vaccinated. Isolate for at least 5 full days after your symptoms start, or after your first positive test date if you don’t have symptoms.
Ending isolation: You can end isolation after 5 days if you test negative (use an antigen test) on Day 5 or later – as long as you do not have a fever and your symptoms are getting better. If you still test positive on or after Day 5 or if you don’t test, isolate for 10 full days, and until you don’t have a fever. It is strongly recommended that you wear a well-fitting mask around others – especially when indoors – for 10 days, even if you stop isolating earlier.
For those of you who have been traveling this summer (maybe you attended a journalism conference or other big event) the guidelines say, “If you have been exposed to someone with COVID-19, even if you are vaccinated, test 3-5 days after your exposure. Isolate if you test positive. If you had COVID-19 in the last 90 days, only test if you have new symptoms, using an antigen test.” And let’s face it: If you have been anywhere more than 50 feet from your front door this summer, you have been exposed to someone who has COVID-19.
There are 7 million Americans who need insulin to control their diabetes. That number alone makes the Inflation Reduction Act important to a lot of your viewers/readers/listeners.
Two administrations representing both political parties have promised they would do something to control insulin prices. And once again, the plan is stalled in Congress.
Senate Democrats hoped to include a provision in the Inflation Reduction Act that would cap the cost of insulin at $35 not only for people with private healthcare but also for people who are covered by Medicare.
But because the legislation before the Senate over the weekend was a budget reconciliation bill, it had to comply with rules that the Senate Parliamentarian said made that provision out of line.
Democrats tried to keep the provision in the final legislation anyway, but it failed even with the support of seven GOP senators including Sens. Bill Cassidy (Louisiana), Susan Collins (Maine), Josh Hawley (Missouri), Cindy Hyde-Smith (Mississippi), John Kennedy (Louisiana), Lisa Murkowski (Alaska) and Dan Sullivan (Alaska).
The final vote was 57-43 but under Senate rules it needed 60 votes to pass.
Interestingly, more Republicans supported the proposal when Donald Trumped backed such a plan to limit the cost of insulin.
The Senate votes means that the plan heading for a House vote next caps out-of-pocket costs only for Medicare patients who use insulin, around a quarter of whom pay more than $35 per month right now. Some states have imposed a $30 monthly cap on insulin for some patients with private insurance.
Let me provide you an idea of how many people this affects. FierceHealthCare summarized the latest findings:
Kaiser Family Foundation looked at 2018 enrollee data for all individual and small group Affordable Care Act plans sold on and off the exchanges. It also looked at claims data from that year from people who had large employer coverage using IBM MarketScan data.
Overall, the analysis explored 110 million out of 160 million Americans with private insurance. Kaiser added that about 1 million people among those studied got an insulin prescription filled in 2018.
Researchers looked at how many enrollees paid more than $420 a year out-of-pocket on insulin, which is the average of $35 a month.
It found that 26% in the individual market and another 31% in the small group market paid more than $420 a year. The large employer market had only 19% of people who paid more than that figure annually, as this group tends to have lower deductibles and copayments.
People who work for smaller companies or employers and people who do not have employer-sponsored healthcare pay the most, as you would suspect.
The Kaiser Family Foundation says a $35-a-month cap on out-of-pocket insulin costs could benefit more than one in four Americans on the individual and small group markets and one in five in large employer-sponsored plans. Critics say insulin costs a few dollars to produce but for some people has become so expensive they are rationing their care.
Bloomberg reports that as women return to the office, they also are finding that old shoe-wearing habits are a big pain in the bunion.
Podiatrists are seeing an uptick in injuries brought on by a return to the office, in-person conferences and other professional events that require a return to more formal footwear. Dr. Miguel Cunha of Gotham Footcare in Manhattan said his offices have recently seen an influx of overuse injuries, from shin splints to plantar fasciitis, among patients wearing heels again after ditching them for two years. During the pandemic, lower levels of activity and going barefoot led to weakness and tightness of muscles and tendons
“Once the restrictions of the pandemic were lifted, many women resumed their use of heels for work without giving their body adequate time to transition back to their pre-pandemic activity levels,” Dr. Cunha said. For many, that’s led to intensified foot pain and discomfort.
“The body doesn’t like any kind of abrupt change,” said Dr. James Hanna, former president of the New York State Podiatric Medical Association. “Whenever you’re forced to do something all at once, suddenly you’re going back to the office, and now you’re wearing these shoes you haven’t worn in two years, that’s really like asking for trouble.”
During my time in Las Vegas last week for the NABJ/NAHJ convention, every conversation I had with cab drivers centered on the weather and water. As I watched fountains flow and thought of the water the skyscraping hotels must use, I was interested to learn how Vegas, oddly, may be modeling how other cities, desperate for water, may adapt.
CBS News found that the city is so dry that it is ripping up what little grass the city maintains.
A new law, the first of its kind in the nation, bans non-functional grass — defined as grass that is used to make roadways and roundabouts look good while serving no other purpose.
The city’s already pulled up about four million square feet of grass on public property so far this year, because thirsty green parkways are something they just can’t afford anymore. “The grass that you see behind me is not long for this world,” Mack told correspondent Tracy Smith. “In fact, within the next couple of months to a year, this grass will be completely eliminated, and it’ll be replaced with drip-irrigated trees and plants.”
And John Entsminger, the general manager of the Southern Nevada Water Authority said:
“Everything we use indoors is recycled. If it hits a drain in Las Vegas, we clean it. We put it back in Lake Mead,” Entsminger said. “You could literally leave every faucet, every shower running in every hotel room, and it won’t consume any more water.”
In the past two decades, Lake Mead has dropped a startling 180 feet due to a the ongoing megadrought, made worse by climate change and the rapid growth of cities and agriculture in the Southwest. Southern Nevada, though, has beaten the odds by cutting its overall water use by 26% while also adding 750,000 people to its population since 2002.
How is your community thinking about sustainability in parks, along highways and streets? As cities grow, what requirements are the communities placing on developers to keep sustainability in mind for what they plant and how much water the landscaping will require?
The Natural Resources Defense Council warns that even while attempting to save water, it is a bad idea to rip up greenspace. NRDC promotes “green infrastructure”:
Green infrastructure encompasses a variety of water management practices, such as vegetated rooftops, roadside plantings, absorbent gardens, and other measures that capture, filter, and reduce stormwater. In doing so, it cuts down on the amount of flooding and reduces the polluted runoff that reaches sewers, streams, rivers, lakes, and oceans. Green infrastructure captures the rain where it falls. It mimics natural hydrological processes and uses natural elements such as soil and plants to turn rainfall into a resource instead of a waste. It also increases the quality and quantity of local water supplies and provides myriad other environmental, economic, and health benefits—often in nature-starved urban areas.
And NRDC recommends that cities build rain gardens, which are between sidewalks and streets where runoff waters flows rather than flooding streets. NRDC points to porous sidewalks that “allows rainfall to seep through to underlying layers of pollutant-filtering soil before making its way to groundwater aquifers. Once installation costs are factored in, it can cost as much as 20 percent less up front than conventional pavement systems, and it can be cheaper in the long run to maintain.”
Journalists, the summer of 2022 has been jam-packed with floods and storms. The climate experts tell us worse is coming. America is spending billions on new infrastructure. Wouldn’t this be the time to adapt to anticipate our future rather than just react to the past?
As summers get hotter, homeowners may be tempted to ask, “Do we need a pool?” Thankfully the answer in my household has always been that our kids had friends who had pools and we lived fairly close to a nice public pool, so we avoided digging up the backyard. But now, this being 2022 and all, let me introduce you to the concept of a “plunge pool”: a shallow, maybe 10 by 20 feet in-ground tub that is enough to wallow in but not big enough to swim in. You avoid the expensive maintenance, and you cause less harm to tree roots for about half the price. The New York Times will show you pictures.
I have a heavy week of travel and teaching ahead so I will be away from the newsletter for a bit.
See you soon-ish.
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Al Tompkins is senior faculty at Poynter. He can be reached at email@example.com or on Twitter, @atompkins.