Video communications provider, Zoom, IPO'd earlier this week with the shares gaining 72% on opening day. There was a lot of negative chatter about this from the technology wags on social media. "It's in the same market as Microsoft Teams and Cisco WebEx, who would invest in this also-ran?"
Investors in Zoom are buying shares in a company that turns a profit, grew 119% year over year in 2018, has tightly controlled research and development costs and no debt. No. Debt. Zoom is a rare thing, a technology unicorn run by adults who are not using debt as rocket fuel to power a frantic grab for market share. While Zoom is overvalued the reason it is overvalued is that investors looked at a well-run technology company in a growing segment and decided they wanted in fast.
While it is in the same market as both MS: Teams and WebEx the difference is that as an investor you can invest in the growth of video communications, collaboration and conferencing for businesses when you buy Zoom shares. Something you can't do with those other two products. You can't invest in Microsoft Teams as you're buying Azure cloud growth when you buy Microsoft shares. Azure growth is a great thing to buy but it isn't video communications. Neither can you invest in WebEx, you're buying the cash flows from Cisco's networking business when you buy Cisco shares.
If Zoom has a major problem on the horizon it's the unrealistic expectations of their day one public shareholders. Best of luck Zoom team, you're going to need a few more years of 100% plus year over year growth to keep your new owners happy at the price they've set. They're hoping your Midas touch will create much more gold for them in the future.
Unlike the assemblers that Intel supplies, that is those companies in the PC, server and IT equipment markets, Intel spends a significant amount of time on maximising its use of assets. Those multibillion-dollar fabrication facilities where tight control of the manufacturing process has long provided them with a competitive advantage over fabless semiconductor rivals. How it uses those assets has changed, but not for the better.
In 2016 Intel made a drastic accounting modification which is indicative of a change in the fundamentals of their business. In its financial statements Intel increased the duration of machinery depreciation from four years to five years, burnishing their financials by $1.5 billion with the stroke of a pen as in their opinion the machinery and the facilities which house them now kept their value for 12 months longer.
In the modern history of the company massive capital expenditure took place before major leaps in microprocessor technology. Intel which for years delivered two generations of microprocessor on the same process had now chosen to deliver three generations of processor before spending the money required to make the next major technological leap.
Extending the depreciation horizon may just look like a creative accounting trick, and it is, but it is also symptomatic of a short-term view when it comes to running the business. It is great for earnings today but in Intel's case it comes at the expense of technological investment for the future. Intel is spending less and this will be reflected in microprocessors with less differentiation, and therefore less customer value, between generations.
This deceleration of investment means Intel is vulnerable but as of yet there is no one of the scale required to exploit that vulnerability. Will this change? Probably, but it is difficult to see who can threaten Intel so directly that it will force them to re-evaluate their current strategy of investing less in technology over the longer term. Intel, trapped by its overwhelming success in the x86 processor market, and with industry recognised aggressive corporate antibodies forcing out those insiders who are looking to change the company, could already be in the midst of an ongoing decades long decline. A corporate giant falling in slow motion.
Competitors have established leadership positions in markets adjacent to Intel's general-purpose computing roots but face a problem of where they go next. ARM's stranglehold on mobile processor designs for example has not translated into datacentre success. But power efficient devices are proliferating while x86 workloads continue to consolidate on fewer processors. First with on premises virtualisation and now in the public cloud with compute time billed by the second.
While Intel has racked up a number of failures in its attempt to ride the mobile/power efficient wave it was right for Intel to exit the 5G modem business earlier this week. When it was clear the product line would not generate a Return On Net Assets at a level required to justify the manufacturing effort spent, the correct decision was to withdraw from the business. A significant number of new ventures undertaken by corporations turn out to be failures and end in a rout. While you should cut any losses quickly such failures are acceptable because it means someone somewhere is trying something different.
What Intel's new unique ideas are, their difference that will drive growth for the next five or 10 years, is unclear. One thing that is clear what with the one-time Chief Financial Officer, Bob Swan, now promoted to Chief Executive Officer it should be expected that asset management will become even more aggressive. Could we see four generations of Intel microprocessor made using the same fabrication process as Intel's long term technological investment is dialled down even further? That's possible.
The battle between the United States government and Huawei is a battle between the United States and China for control over the development and direction of wireless technologies. The Internet may not be forever, political moves in the game between the United States and China guarantee that the Internet will mutate in coming years as a result of this infrastructure conflict and future conflicts at every control point.
In telecommunications technology there are five major players of note, Ericsson, Nokia Networks, Huawei, ZTE and Qualcomm. Respectively, these companies are proxies for the economic ambitions of Europe, China and the United States. Holding a key position above the others the United States, represented by Qualcomm, provides intellectual property which underpins all the other offerings. This has worked out well for Europe which though jealous of Silicon Valley's success has always embraced its innovations, but China chafes under the influence Qualcomm's intellectual property provides the United States as it allows the US to dictate terms. Making Qualcomm irrelevant is a Chinese strategic objective.
In 2018 the United States, having discovered that China's ZTE had shipped products to Iran and North Korea containing Qualcomm technology, banned all US technology exports to ZTE with the result that ZTE faced ruin. At the time China was refusing to sign off on Qualcomm's $39 billion acquisition of European semiconductor provider NXP, the ZTE ban had the upside of being a potential lever to get the deal moving again. When the US lifted the ban on exports to ZTE it was expected that China would reciprocate by allowing the NXP acquisition to take place. China did not reciprocate forcing Qualcomm to scrap its acquisition plans, much to the consternation of the United States government.
With the extradition of Huawei's CFO from Canada to the United States in process, again for shipping products to Iran and North Korea containing Qualcomm technology but also for hiding the money trail, we see the political game escalate but might ask the question should the United States be allowed to decide who gets 5G wireless? China appears to be asking that question, a lot, and if it develops its own answer to Qualcomm what might happen to standards?
The Internet was a US phenomenon that spanned the world, everyone got in line behind technology decisions made in the United States but would the United States and its Western allies get behind technology decisions made in China? If they would not could we see the beginning of a fracture in infrastructure which will lead to a split in the Internet? A United States led alliance facing off against a Chinese led alliance, the primaries of both engaged in battles for control over all layers of infrastructure and at every software control point.
Qualcomm is now considered to be such a strategic part of long-term United States objectives that the Department of Defence has begun intervening in domestic investigations of Qualcomm's business practices. Likewise China's commitment to Huawei is clear. Two sides have chosen their champions, as per usual Europe has no plan to put the wood behind one arrow but soon enough it would not be surprising to see an Ericsson – Nokia Networks merger slide on through the European Commission without an eyebrow raised by the Commissioner for competition. Stability is something the EU always prefers.
After decades of use it would be a mistake to assume the Internet is stable because it is successful. The fact it is so successful makes it of interest to those looking to further their own political, economic and social goals. If those goals require that the Internet be split into incompatible pieces you should assume governments are working towards that relentlessly.
At its core Artificial Intelligence is about teaching computers to do what humans can do with the expectation that computers will do those things better. Examining the history of technological progress it is possible you will not live long enough to see Artificial Intelligence change the world. Assuming AI is something that will change the world and that is in no way assured.
In a best case scenario Artificial General Intelligence (AGI) will be system capable of tapping the sum of human knowledge to answer questions which are currently beyond us and generate ideas which we are incapable of. AGI relies on a breakthrough yet to be made so in the near term we can expect that slivers of task specific Artificial Intelligence will be embedded into software, services and products in the same fashion that databases are now embedded in the such things. There was a time when the very idea of a database in your home or in your hand was ridiculous but now task specific databases are embedded throughout a multitude of devices people own or interact with.
In 2014 one of the more popular books bought by technology industry executives was The Second Machine Age. In The Second Machine Age the authors, Brynjolfsson & McAfee, propose that advances in software design and computational power are doing for thinking what the steam engine did for manual labour. To the authors true innovation is in combining things that already exist in different ways to create new outcomes. Add AI to a vehicle and gain the benefits of self driving vehicles.
This is an optimistic book which takes great pains to point out that quality-of-life improvements will not be distributed evenly and there will be losers from this ongoing cognitive revolution. In the opinion of the authors the greatest gains in productivity, wealth creation, and social good lie ahead but we must remember to bring everyone along. This is a book where technology not only saves the world but makes a better for everyone and regardless of the strength of the ideas proposed between its covers that is a very appealing vision for people working in the IT industry.
The antithesis of the second machine age would be The Rise and Fall of American Growth. Written by Robert J. Gordon this proposes that life began improving dramatically for people through a series of great inventions, such as electricity and the networked home. It is an example of our focus on Information and Communication Technology that the idea of a networked anything would involve Ethernet but in this case the networks are those of electricity and indoor plumbing. Electrification brought light and the mechanical automation of repetitive chores into the home, while indoor plumbing provided freshwater for consumption and as importantly increased public health through better sanitation.
In Gordon's view the century of unprecedented growth between 1870 and 1970 was an outlier and not something that will be easily repeated. Using the example of the internal combustion engine Gordon proposes that important inventions do not have an immediate impact and must be adapted and disseminated. In the case of the internal combustion engine it took nearly 50 years before tractors replaced horses on farms. The greatest inventions have shown that the process of dissemination is slow but provides steady increases in living standards over a long time.
In Gordon's research the development of the Internet and other related Information and Communication Technologies created a surge in productivity between 1994 and 2004 which then tailed off dramatically. Unlike the inventions in the century of unprecedented growth the dissemination of the Internet did not create a significant increase in living standards. In Gordon's view the algorithm is no match for the assembly line when it comes to making people's lives better. Artificial intelligence may be able to quickly identify what is a cancerous growth in a patient and what is not, but delivering untainted water to where billions of people live and taking away their waste has saved and will continue to save orders of magnitude more people.
This is not to say there is no value in Artificial Intelligence but Gordon's view is that we have already exited an unprecedented cycle of intellectual achievement and quality of living increases throughout the 20th century, and we are now returning to incremental increases in living standards we have known throughout human history. Artificial General Intelligence, where computers can truly do things humans can do and do them better, still eludes us. Accepting that any breakthrough in this field would take time to be adapted and disseminated we see there are decades between the creation of the first AGI system and the adoption of AGI systems throughout society.
Artificial Intelligence may change everything and introduce the long boom of the second machine age, or with a lot of the hard work to increase living standards already done in the 20th century it may just provide incremental improvements to our lives by being task specific. But the clock does not start ticking on the societal impact of artificial intelligence until we have a major breakthrough.
Today AI can beat the best DOTA2 players, OpenAI Five playing 180 years worth of DOTA2 games every day and using what it has learned to demolish human players in the arena, but if you change the game those simulated decades of experience become worthless. The breakthrough we are looking for may come from gameplaying artificial intelligence but that breakthrough is not artificial intelligence which can only play games. The clock hasn't started yet and the decades required for adaptation and dissemination will not begin until it does.
How will we know when artificial intelligence has made a true impact on society? When it starts telling us things we do not like to hear.
Until the beginning of December the common wisdom has been that the equity markets have another 12 months of growth before the current multi-year bull run draws to a close. That has gone from being informed opinion to a desperate hope in just a few weeks. Could we be facing into a recession starting in 2019? It is probable that is the case.
As defined by the National Bureau of Economic Research a period of recession is a significant decline in economic activity spread across the economy, lasting more than a few months, normally visible in real GDP, real income, employment, industrial production, and wholesale retail sales.
Functioning economies expand and grow with more people (Consumers) born in developing countries while the people in developed countries become more productive. A recession is where this tide goes out, people consume less, businesses produce less, and productivity falls as people lose their jobs. Recessions are typically short lived, the average being a year in duration, but they are such a hard reset that it takes many years to return to the point where the recession began.
McKinsey conduct a regular global survey of Chief Financial Officers and Chief Executive Officers around the world. Their current report shows that the majority of survey respondents currently hold very unfavourable views of the economies their companies operate in. Over the next six months these executives predict that conditions will deteriorate even further. Trade wars and political instability cited as the two main areas of worry. The news plays up riots in Paris and the US verses China but these ideas have taken deep root in the heads of people who juggle tens or hundreds of billions is assets.
There are many potential measurements that can be used to forecast a recession but since economics is what happens inside people's heads it can be a good idea to start there first. In the heads of the Chief Financial Officers of some of the most prestigious companies in the world the outlook is grim. These men and women sign the cheques for technology spending, when they snap their cheque books shut that sound is heard everywhere in the IT industry.
It's not awful for technology vendors, technology winners tend to use recessionary periods to tighten up processes that have gotten loose and invest for the future. That strategy of spending on development when others are timid can position you well when budgets grow and CFOs start spending again. Much as they might try no company can cost cut their way to lasting success. Intelligence, execution and timing are still the major factors and the first two tend to need all the help they can get from IT vendors.
While executives have a pessimistic view of 2019, consumer spending is holding at the moment. House purchases, which are the largest purchases the general public tends to make, proceed apace and have not shown any signs of slowing yet. That said, between the volatility in the global markets and increasing pessimism of top executives we have two visible warning lights on the dashboard. It will not take much to light up some more of them in 2019.
For the good of the information technology industry, and those employed in it, AWS must continue to offer an increasingly complex portfolio of services. The more effort it takes an organisation to use AWS effectively, the more jobs it creates for other people. This undue burden on AWS customers is a job creation program for everyone else. AWS is a giant star orbited by partner companies of various sizes and countless individuals, this is the AWS economy.
According to Gartner worldwide IT spending is $3.7 trillion, this is more than twice the size of the global oil industry at $1.7 trillion, and five times the size of the international metals and minerals market at $660 billion. IT spending is not just people buying things, it includes people doing things. The smiles of server and storage vendors have become a rictus of panic in trying to convince everyone their businesses are doing fine when they are not, the real spending is happening elsewhere.
While vendors capture most of the economic value from their intellectual property there is an expansive ecosystem of higher revenue but lower margin services provided around that intellectual property. This is a technological economy and every new service AWS offers increases the overall size of the AWS economy.
Independent software vendors selling products that use or run on AWS, consultants and system integrators who wrangle AWS for organisations and those developers who deploy code on AWS are all beneficiaries of the AWS economy. They are employed to do things AWS customers cannot or do not wish to do themselves. If AWS was easy and something organisations did not have to think about these other members of the AWS economy would not exist.
How large is the AWS economy? That is unknown but we can get a sense of how large it might be by looking at a peer. In 2017 Salesforce.com estimated that for every one dollar Salesforce earned the economy that operates around Salesforce made $3.67. For every one turn of the Salesforce crank the connected flywheel spun nearly four times.
By Salesforce’s estimates, between 2016 and 2022 Salesforce will facilitate the creation of 3.3 million jobs and generate $859 billion in new business revenue. Salesforce pitch this as an example of how Salesforce helps companies perform better. But it’s also a lot of consultants and sales people buying plane tickets, booking hotel rooms and going to see Salesforce customers to sell them products which integrate with Salesforce.
Is the AWS economy now measured in the billions? Yes. Hundreds of billions? Well, if it is not there yet it will be soon. Every new service for customers to make sense of and integrate with adds hundreds of millions of dollars to the AWS economy.
Andy Jassy will take the stage this week and will fire off a volley of new features. He may throw another service or five on the pile of ~90. He’ll probably mention something about databases, because Larry Ellison has been living rent free in Andy’s head for a while now.
Focusing on databases is good because if Oracle’s Autonomous Database strategy pays off, where automation does things junior DBAs used to, it will probably cost some junior Oracle DBAs their jobs. Those junior DBAs will look for other places to sell their time and a lot of them will land on whatever AWS is offering because that is where the future growth is. These will be new members of the AWS economy.
Amongst the noise and endless queues in Las Vegas this week do not forget that the more difficult it becomes to read the eye chart that is AWS’s service offerings, the better it is for members of the AWS economy.
So sit back, relax and listen to what the sages at Amazon have to say. Then know that many people elsewhere will be hired to make sense of it all..
New products are adopted slowly if they are adopted at all. The expectation that Google Cloud's AI offerings would generate a monsoon of new revenue, within the five year horizon Diane Greene referenced frequently, has proven to be incorrect.
This cost Diane her job.
Google Cloud Platform (GCP), under Diane's leadership, has attempted to leapfrog its cloud competition by selling the superiority of GCP's AI offerings. But Google are early and have dramatically overestimated the speed of AI adoption.
Product adoption can be measured. 3M corporation is one of the most innovate companies in the world and how they measure the success of that innovation is in how much revenue it returns to their business. This is a good measure of success for any technology company. In Transforming a Legacy Culture at 3M: Teaching an Elephant How to Dance, the New Product Vitality Index (NPVI) is shown as a 3M measure of sales generated from products introduced during the past five years.
At 3M's highest performing point, its NPVI has not exceeded 35%. Out of more than 50,000 products touching different parts of our lives, two thirds of their revenue comes from products that are more than five years old. For companies not as successfully innovative as 3M, an NPVI of 3%-5% of revenue is common.
New products are adopted slowly if they are adopted at all, and AI is being adopted slower than Google Cloud needs it to be.
While GCP's financials are opaque in Alphabet's earning reports there is no visibly increasing GCP/AI bounce in Google's revenue. Not in the way AWS and Azure have clearly contributed to their parent operations.
AWS and Azure built their leads selling infrastructure and platform as a service offerings making it understandable that Google would look for a point of differentiation. AI has been the wrong point of differentiation. While AI will diffuse throughout new products over time, being built in the way embedded databases were, this adoption time will be long.
Changing business leaders will not alter Google Cloud's market position because it does not change its point of differentiation. Finding a differentiator with an adoption timeline that works for Google, and works against its competitors, will be what will earn Thomas Kurian his compensation.
Or if he too gets it wrong, it'll earn Thomas a severance package..
IBM is buying RedHat because IBM has fewer potential customers today than it had in the early 1970s. You can buy companies, but you can’t buy time and time is IBM’s enemy because every passing second acts against IBM’s business model by killing off IBM's best customers.
According to the US National Bureau of Economic Research, in 1976 there were nearly 5000 publicly listed companies, approximately 23 public firms per million US inhabitants. These companies have long been the bedrock on which IBM’s technology and professional services businesses were built.
When these companies first needed a computer, they bought a mainframe. When the PC and client server computing waves swept through firms IBM was there with the hardware, software and services required to put a PC on every desk and a server in every small data centre. When the internet hit, IBM had an e-business strategy on paper for CIOs to read and an army of IBM Global Services consultants to implement that strategy if the CIO cut them a purchase order.
IBM helped publicly traded firms make sense of technological change. Then, slowly at first, the worst thing happened. Globalisation and the Internet began murdering IBM’s customers.
That company making plumbing fixtures in their own factories in the US went out of business because its customers could order the same fixtures slightly cheaper and in higher volume from Asia with just a few clicks. As time ticked on hundreds of that company's publicly traded peers joined them on the funeral pyre of companies that are delisted and go out of business.
In 2016 the number of publicly listed companies had declined from 5000 in 1976 to approximately 3,600. As the US population continued to grow and consumer demand surged, a vast swath of existing and potential IBM customers withered and died. Where there once were 23 companies per million US inhabitants now there are 11 and falling.
In 1975, 109 firms accounted for half of all the profits booked by publicly traded firms, this year just 30 firms booked half of the profits. More customers giving more money to a smaller and smaller number of companies. Every one of the massive tech platform companies is in the top ten. Those platform companies not looking to buy anything from IBM today or tomorrow.
Near term, in the Enterprise IT market you can either become one of the trillion Dollar platform holders or be a company that uses those platforms to provide something of value to customers. RedHat has been moving towards trying to provide something of value. IBM has realised they will never be a platform holder of the size IBM requires to sustain itself, so the RedHat deal is their attempt to get onto those hyper-scale platforms and provide something of value to customers of any size.
The coming threat, for many IT providers not just IBM, is the next death wave to rip through the existing publicly traded companies. Amongst the financially living there are shambling zombie firms which have been lurching from one cash flow problem to the next under the darkness of creative accounting.
Mortally wounded due to the financial crisis and global competition, they shuffle onwards because of the cheap debt sloshing around the global financial system. Now that quantitative easing has tapered off across the globe, the low interest money drying up, rising debt interest rates will send these companies to their final death. Bankruptcy follows unsustainable debt payments and IBM’s potential customer pool will shrink even further as these zombie firms are shown to be flat broke.
RedHat is not a perfect deal, it has its own challenges, but it’s a deal that can be done with the financial resources IBM has today. There is no time for IBM to attempt another organic growth spurt, cognitive computing (Watson) was IBM’s in-house attempt to build a bridge to a prosperous future, IBM has failed in this effort. The idea was good but in business perfect execution of a mediocre idea results in profits. IBM had poor execution and that’s why cognitive computing has been a bust for them.
You can buy companies, but you can’t buy time. Buying RedHat is an attempt to buy the results of the time RedHat has spent on solutions to get customers up and running on the hyper-scale platforms. IBM’s customers are the names rolling across the stock market tickers, but that list shortens every year. With the RedHat deal it is IBM’s hope that a potential IBM customer is anyone of any size trying to get work done on the hyper-scale platforms.
It could work.
It could also be the death rattle of an industry pioneer.
But what a way to go out...
Hell is not a finance meeting, some of the more technically inclined may suspect it is but they are missing out on an invaluable opportunity to assist their co-workers. As a technologist even if you have no experience with business finance your objective in any meeting where financial numbers are presented to you is to ask insightful questions.
The least financially inclined technologist should pay attention to the trinity of metrics; growth, customer sentiment and employee engagement. You will hear these numbers mentioned in isolation frequently, but they should be examined together as they represent the past, the present and the future of your business. How a product you are working on has grown, if customers are enthusiastic about it and if employees are happy to be working with one another shows you the health of your organisation.
If one of those three is under performing, or has swung to negative numbers, a focused management intervention is required. If two of the three are under performing/negative a replacement of some of the current management is required. If all three are under performing/negative a transformational leader will be required to replace the current management, replace much of the mid-level management and refocus the business on what it can do best.
Every organisational transformation, where a battered and demoralised company is rescued just before it plunges into the abyss, is a story of the warning lights of the trinity being ignored. "Good employees do not want to work here, customers did not like the products we offered, and growth evaporated." Properly measured growth, customer sentiment and employee engagement do not lie about your company’s prospects even if a bad management team does.
While the trinity will tell you if your company is on the road to greatness or the road to ruin, other financial numbers can be abstract. Inside of organisations how financial numbers are derived tends to be cloaked in secrecy. This is because finance is as much of an art as a science and if you saw the process by which the numbers are assembled you may have questions, if not objections.
A financial presentation to a meeting you are in is your chance to ask questions and, if required, to object. For someone without ongoing exposure to business finance discussions the key concept is that the value in financial numbers is only in their comparison. What is the difference between two data points of the same financial metric taken over time? Is something increasing or decreasing as time passes? What does that mean? Is it expected to continue as is, decelerate or accelerate? Why?
Observation will inform you as to what numbers more experienced attendees care about and regardless of how dense a set of financial numbers might look to you only a handful of key numbers will matter. Ask questions about these numbers and do not fear them as you cannot break them.
Looking at results you want to compare what was projected against what happened last month or last quarter. Results are in the past, you can only learn from why they are different. Discussing projections or budgetary requests involves checking assumptions about the future. Does what you know about the past or what you suspect about the future align with what the presenter is telling you? Dig into the differences.
During budgetary requests people tend to ask for money they want and not what they require. Take it upon yourself to find out what is required through questioning the requestor because each budgetary request is more of a negotiation than a statement of fact. What you are looking at should be treated as an opening offer and the information you are gathering through questioning is information to make a counter offer.
When it comes to making people offers, headcount of salaried employees is also a metric worth examining whenever the opportunity arises. Who is getting what budget to hire new employees and are those new employees being placed in growth areas? You can spot managerial empire builders when new headcount starts appearing in places that are not connected to the growth areas of the business.
The most rudimentary understanding of the financial position of your company, or your division or your product organisation will help you made better decisions about your career. That is the self interest part but when it comes to working with your team remember:
Finance is as much about people as it is about numbers, when you examine both you can help your co-workers make competent financial decisions which can benefit you all.
The common wisdom is to not put up with talented jerks in the workplace. Who needs to work with know it all jackasses whose behaviour is usually met with eye rolls in meetings? Yet you still find them in every organisation. There is a reason for their ongoing ubiquity and that reason is a lottery jackpot.
There are three genetic super lottery jackpots in life. Being physically more attractive to others, having a level of physical prowess beyond the ordinary or having superior cognitive ability (IQ). If a person cannot make a living from their appearance or from professional sports it is IQ that is by far the best predictor of their performance at other types of work.
In The relation between emotional intelligence and job performance: A meta-analysis (O’Boyle, Humphrey, Pollock, et. al, 2011) researchers examined more than 1000 studies to see if Emotional Intelligence (EQ) had an impact on job performance. Having examined EQ, personality traits and cognitive ability it was their conclusion an increased level of EQ did improve job performance. While their study identified interesting things about EQ, in the table below you should note the outsized performance resulting from cognitive ability, IQ, relative to what they were testing for with EQ.
While the social sciences are undergoing a replication crisis, studies whose results cannot be replicated correctly being tagged as being suspect at best if not out rightly fraudulent in other cases, IQ as a performance predicator replicates consistently. The higher your IQ the greater the chance you will be one of the few employees that makes a contribution so substantial to the organisation around you that it will be a lasting contribution.
Just as many of us do not look like models or movie stars, nor can we break sporting records, there are levels of workplace performance below extraordinary. The trick to optimising your performance is finding the best environment to do what you are good at and then do it consistently. This can be personally rewarding so long as you keep stretching yourself to do things currently just beyond your grasp.
The higher the IQ the more ambiguity you can deal with in your job and jobs with high levels of ambiguity at their frontiers pay quite well. As you move down the IQ scale it is unambiguous repetitive jobs which deliver the best workplace performance from individuals with lower IQs. Like those with higher IQs there is satisfaction from doing such jobs well, but repetitive jobs pay modestly or poorly.
Automation will decimate most repetitive jobs and there is no pathway to jobs with higher ambiguity for those of a lower cognitive ability. Last week in the US at the Dallas Fed conference executives from Fortune 500 employers admitted that they are targeting repetitive, low ambiguity jobs for elimination by automation.
Realising this means hard times for many there was mention of providing Nano-degrees to move people to higher skilled jobs, but we already have colleges pumping out as many highly skilled new graduates as the work market can absorb. Automation is the next major social problem looming on the horizon.
Now we come to the talented jerk. Books have been written as to why you should not hire super smart people with noxious personalities and those books raise good points. Jerks can wreak havoc with teams they are in and make cross team collaboration more like trench warfare rather than a mutually productive relationship. But here is the crux of it, while you cannot make substantial changes to a person's cognitive capability (IQ) you can make them much more rewarding for other people to deal with (EQ).
Properly designed coaching interventions focused on EQ have been found to improve the social and interpersonal skills of those being coached by about 25% (Peterson, D.B., Measuring change: A psychometric approach to evaluating individual coaching outcomes., 1993.) These results also replicate consistently making them science and not wishful thinking.
Accepting that a higher IQ does translate to higher workplace performance we can say that while you cannot take a talented jerk with a major psychological issue and fix them, you can take one and sand down the rough edges enough that they do not jab people when handled. Getting the talented jerk to accept the coaching is where you might need to use finesse but with those with a higher IQ demonstrably out performing others at work your EQ coaching investment today might pay off in measurable high performance for years.
Of course if the talented jerk does not acknowledge feedback from different sources telling them that change is required, does not accept the coaching or does not improve as a result of coaching they should be handed their hat and shown the door.
A tool that cannot be used effectively should be discarded, it only makes the worker harder.