While the Covid-19 pandemic was a period of binge-watching Netflix and toilet-paper roll shortages, it was also a time where we witnessed a wave of digital transformation due to the heavy shift towards online services. During lockdowns, customers around the globe relied on e-commerce and other online activities to satiate their spending habits. Thus, in response to this surge in demand, tech companies over-hired employees. However, they did not anticipate that this surge in demand for popularized services would cool-down as customers returned to offices and their offline lives. Today, companies are correcting the hiring rush that happened in the tech industry during the pandemic at the expense of employees.
Working in companies across the tech industry was considered a sustainable career path. However, in an era of economic fluctuation it no longer appears to be so stable in the face of thousands of layoffs in big tech companies. Although January is not yet over, we are seeing layoffs overtake the tech industry even worse that the 1990s recession.
Google just announced that they will be cutting 12,000 jobs – that is 6% of their staff. Facebook plans to layoff 50,000 employees from their ranks. Microsoft are revisiting their core business goals 2020 digital-era spending; they already cut 10,000 of their workers as a result. Amazon has also “eliminated” 18,000 positions, which juxtaposes with their previous decision to almost double their workforce during 2020 pandemic lockdowns.
Other than correcting the hiring mania that happened during the pandemic; the increase in interest rates, high inflation levels and the fear of the economy going into recession has forced overstaffed companies to act. The uncertain state of the economy is predicted to cause a fluctuation in consumer spending with lower advertising investment in tech companies as a result. Thus, tech leaders are merely responding to the events of the world such as going back to face-to-face activities and possibly facing economic downturn.
Many predict that the worst is yet to come, however as of the first month of 2023, the widespread belief that there will be an unrelentingly rapid rise of internet services has already been disproven. Now workers across the globe are reaping the consequences.
On the 27th October, current Credit Suisse (CS) CEO Ulrich Körner announced to shareholders the latest restructuring plan his bank will undertake to regain the share value it has lost in the last few years. A series of scandals, stemming from poor risk management and permissive governance, has led to Credit Suisse’ share price falling close to 60% in the last year. The restructuring plan is the second attempt at stabilising the bank in the last two years, with the former CEO Thomas Gottstein announcing a similar plan before leaving due to pressure from scandals and poor performance.
The latest restructuring plan involves downscaling the investment bank significantly and focusing on Credit Suisse’ strong wealth and asset management businesses. The investment bank will look to offload capital in the volatile securities business and focus more on mergers and acquisitions as well as capital markets. The restructuring will require an additional $4 billion from investors. An external memo released described the investment bank reshuffle as “CS First Boston is expected to be more global and broader than boutiques, but more focused than bulge bracket players”. Critically, the investment bank will spin off into an independent firm, and will be renamed CS First Boston in a nostalgic bow to its banking history.
The recent flurry of scandals began in March 2020, when then CEO Tidjane Thiam was forced to resign after an investigation had found that the bank had hired private detectives to spy on the former head of wealth management Iqbal Kahn after he had left Credit Suisse for competitor UBS. Credit Suisse tried to downplay the event, but further investigation from the Swiss regulator FINMA found that there had been seven other incidents of spying between 2016 and 2019, and stated that there were serious organisational shortcomings within the bank.
A year later, Credit Suisse was marred in further controversy when British financier Greensill Capital collapsed. Greensill Capital was a supply chain finance firm, providing interim finance to businesses that need to pay suppliers in advance. This allowed banks such as Credit Suisse to sell Greensill’s debt to investors. The debt was advertised as low risk due to the fact that the underlying credit was insured. However, in March 2021, Greensill Capital collapsed after its insurance provider stopped underwriting its debt. This led to Credit Suisse freezing $10 billion worth of funds which were not fully repaid, losing a significant amount of money for clients in its asset management division.
The turmoil of March 2021 did not end there for Credit Suisse, when Archegos Capital Management, a family office and client of CS’ prime brokerage business defaulted. This led to losses of $5.5 billion for Credit Suisse, who were the worst affected of the bulge bracket banks by the default. Other investment banks had suffered losses, but these had been limited due to other banks to settling some of their positions with Archegos prior to the default. David Soloman, CEO of Goldman Sachs, stated that “We identified the risk early and took prompt action consistent with the terms of our contract with the client”, praising the risk management of his firm.
An independent report into the incident criticised Credit Suisse for focusing too much on short-term profit maximisation and not recognising the extreme risk-taking behaviour of Archegos. As a result of both losses, Credit Suisse had to raise an additional $1.9 billion in capital from investors to sure up its balance sheet.
The current Chair of CS, Axel Lehmann, admitted in May of this year that CS has failed to be proactive in risk management and that the scandals that have plagued the bank cannot be perceived as isolated incidents. The current restructuring plan intends to limit the sources of risk, but it is likely that a complete reform of how CS assesses risk is also necessary to limit any future scandals.
The use of First Boston to define the new “boutique bracket” investment bank is an interesting strategical move. First Boston was a US-based investment bank, which was first partially acquired by Credit Suisse in 1988, with the acquisition being completed fully in 1996. The bank was renamed Credit Suisse First Boston, commonly referred to as CSFB.
CSFB was a significant competitor in the late 90s, gaining success underwriting IPOs for many high-tech companies. CSFB operated as a bulge bracket investment bank and was officially integrated into Credit Suisse in 2005. Many banks were chasing the universal bank model at the time, making this integration sensible. The might of the original CSFB is in contrast with the new CSFB, which is being downsized to offer a more bespoke service than bulge bracket banks.
If the restructuring takes place as planned, it will be interesting to see how well the investment bank can attract clients due to its reduced offering of services. Direct comparisons in the market are Jeffries and PJT Partners, who have experienced sustained profitability in recent years. However, the detachment of the bank from consumer deposits will make CSFB’s balance sheet more unstable, and the significant losses experienced in 2021 cannot be repeated if the new investment bank is to survive.
CSFB made its name in the late nineties and early naughties, when high risk-taking was rewarded with significant profit and compensation. However, severe risk-taking has led the investment bank to its knees, and it is clear that prudent risk management is necessary. This new risk strategy of CSFB will need to be significantly different from that of the original investment bank.
The recent turmoil has left Credit Suisse vulnerable to a takeover, with rumours of a merger between CS and UBS intensifying. The actions of the new management team will likely decide the future of the bank. A repeat of previous missteps may lead to the vanishing of the Credit Suisse name, let alone First Boston.
Givedish is a social enterprise working with restaurants and cafes to tackle food insecurity, both nationally and globally. For every GiveDish meal sold, a meal is donated to those in need! Cian McGlynn and Olwyn Patterson discuss the story behind their social start-up.
How does it work?
A GiveDish meal can be purchased at any of GiveDish’s partner restaurants: Bread 41, Mad Yolks, Chimac, and most recently, Sumaki. The social enterprise partners with Mary’s Meals; a school-feeding programme owned and run by community volunteers in countries to provide free meals. With Mary’s Meals, it costs €18.30 to feed a child for a school year. GiveDish breaks down this cost to fund the free meals provided by Mary’s Meals. On GiveDish’s website, viewers can see the number of meals donated by each partner restaurant. In September alone, GiveDish’s three partner restaurants donated 1,096 meals – and this is only the start!
The Team
Cian is a second-year Global Business student who became involved with Trinity Entrepreneurial Society. After a few months with the society, he decided to participate in LaunchBox, making his dream to set up a business a reality.
Olwyn is a third-year MSISS student who always had a desire to make something of her creativity. She fondly recounts that as a child that she used to make loom-band bracelets with her friends to sell at charity day in school. Now, she tie-dyes jumpers, socks and t-shirts to sell for charity on Instagram. Upon starting in Trinity, she began to think “about business and entrepreneurship more seriously” and realised that she “could have a larger impact through business than just donating money myself.”
Where they are now
Cian and Olwyn took part in Trinity’s Launchbox, with their start-up, GiveDish, winning 3rd Prize. Launchbox is an accelerator run by Tangent every summer, where ten teams are given office space and €10,000 to work on a start-up. Cian and Olwyn believe that they met some of the coolest and most interesting people through Launchbox. Great speakers such as Dan Hobbs from Protex AI, and Eric Risser from Artomatix (both Launchbox alumni), worked with the start-up groups.
During the interview, Cian and Olwyn revealed that they came up with their enterprise idea “by chance”. Having entered LaunchBox with a “completely different idea”, the team pivoted after some early discovery and research different business models. One of their mentors, Conor Leen (founder of Stampify), introduced them to a Canadian company with an interesting model and, after conducting some customer discovery, the team were set on taking action.
With regards to the name of the business, the team experimented by typing “as many variations of names that could work into GoDaddy to see if the domain was available”, before finding givedish.com to be perfect. They have since changed their domain to givedish.org, however, can still be found at the original givedish.com domain.
Currently, GiveDish is working on building a software application with some help from a developer, as well as slowly refining their processes and making it more transparent. Furthermore, they are looking to help locally; with the rising cost of living, there are problems on Ireland’s doorstep that must be addressed.
GiveDish’s vision is to make donations seamless for people and increase the ease and convenience of donating by making donation part of a daily activity. GiveDish also solves the problem of decreasing profit margins for restaurants by increasing sales of higher profit-margin items. This is achieved primarily through social media; gaining new followers and new partners, and ultimately, donating more meals.
Plans for the future
GiveDish’s goal is to donate 1 million meals to children in need. The social enterprise have many more partners in the works and will continue to tackle food insecurity both globally and in Ireland. To keep up to date with how many meals GiveDish donate, keep an eye on their website.
Just this month, Tesla revealed a prototype of their humanoid robot, Optimus. This latest project will have an AI-chip powered brain, cameras for eyes, microphones for ears, and the capacity to walk and carry 9 kilograms per hand, amongst other things.
This alongside other developments are proof of the mergence of artificial intelligence (AI) as one of the most exciting technological innovations in the world of business. Even now with its technology still in its relative infancy, AI is driving people around, delivering packages, trading securities, and translating languages. Its breath-taking abilities are starting to shape a lion’s share of industries. A hotly contested debate of late is how the relationship between human intelligence and Artificial Intelligence will play out as AI adoption grows. Will it be one of competition and conflict, or will we see eye-to-eye with our AI counterparts?
Intelligentia
The word intelligence derives from the Latin word intelligentia meaning “the action or faculty of understanding”. What does it mean to understand? Oscar Wilde wrote that “to define is to limit”, and hence I think we must interpret intelligence in a rather broad and fluid sense. Intelligence cannot be categorised as a single characteristic or competency and so we should recognise that the abilities and understanding possessed by humans and robots are different. When it comes to comparing AI and Humans, we must consider them differently too.
Talos, Turing & Siri
The concept of intelligent robots stems as far back as the presence of automatons like Talos and Pandora in Greek mythology. Talos was constructed by Hephaestus to help King Minos of Crete guard the island from invaders while Pandora was essentially an ‘all-gifted’ robot. Where philosophy would then mull the presence of artificial beings, science fiction would imagine and depict it with more colour and drama. But in 1950, Alan Turing began to bring the art to life when he discussed how to build intelligent machines and test this intelligence in his seminal paper ‘Computing Machinery and Intelligence.’ Five years later, the Dartmouth Summer Research Project on Artificial Intelligence catalysed AI research for the following decade.
However, in the 1970s, AI development entered its first winter in the 1970s where funding completely dried up, before a small boom in research and development occurred in the 1980s, followed by a second AI winter. IBM Deep Blue becoming the first computer to beat a world chess champion in 1997 was a critical point in the evolution of the technology. The same year, speech recognition software developed by Dragon Systems was implemented in Windows. In the mid-2000’s we saw widespread adoption and exploration of AI by Big Tech culminating in products like the Google search engine, Google Translate, Siri, facial recognition, and Alexa.
And now in 2022, we are in the golden era of AI with sophisticated Machine Learning imitating how humans learn, quantum computing attempting to dramatically increase the power and speed of computing, and the embedment of AI in the Augmented Reality enhancing the experience of the metaverse. With these developments on the precipice of reshaping industries, experts are predicting that using AI at a large scale will add as much as $15.7 trillion to the global economy by 2030. In 2021 Venture Capital (VC) funding for AI start-ups reached an eye-watering $89.2 billion as investors and entrepreneurs look to realise the power of robots. We might hope that amidst all the hype surrounding the adoption of AI, that we, like Minos did with Talos, can firmly place our faith in AI. However, sceptics warn of a scenario more akin to opening Pandora’s box and unleashing its evils.
What’s Inside Pandora’s Box?
It is no surprise that VCs globally have invested billions into AI start-ups in recent years. With the mammoth funding it requires, the range of possibilities are almost beyond the scope of our wildest imagination. Tech giants such as Alphabet and Meta have pumped over $50 billion into R&D to build this brave new world of automation. You’ll find it in the chatbox providing you with “excellent customer service”, helping you to turn on the lights in your kitchen and keeping your home clean, amongst an array of other things. AI is transforming processes in healthcare too with robots pumping out vaccine development and drug design, enhancing quality of life, and possibly saving lives that otherwise would not have been saved.
Here in Ireland, we have companies like Manna Drone Delivery incorporating some AI to autonomously deliver coffees and pastries to people’s homes. And then there is the leveraging of AI in ‘Web 3.0’ ‘s move to decentralisation where it is now enabling some blockchain and token-based transactions.
We couldn’t have a conversation about cutting edge technology like AI without mentioning the wide-eyed futurist that is Elon Musk. Alongside, the development of Optimus and Tesla’s self-driving cars, there is the incredibly frightening neurotechnology of Musk’s Neuralink which wants to create an implantable brain chip to record the activity of the brain and improve human intelligence. With all these technologies, AI’s intelligence derives from their potential to learn and make decisions based on the data they are fed.
On the other hand, humans rely on a different kind of intelligence that is certainly more expansive and intuitive. Humans rely on memory but more critically, possess an emotional intelligence (EQ) that enables us to relate, adapt, empathise, and understand. The significance of EQ in the workplace was underlined by a study of 2,662 U.S. hiring managers which found that a whopping 71% of employers value EQ over IQ. If we consider the work of a nurse, the ability to show empathy, sympathy and compassion is fundamental to their ability to do their work competently. The same can be said for the work of solicitors, actors, comedians, and many other fields where humans cannot be outsmarted due to the essential personal and emotional element. There are also question marks surrounding AI’s ability to maintain the ethical standards that the human ability to empathise enables us to maintain. There was shock and great disappointment when Microsoft’s automated Twitter account, Tay, was easily coaxed by a user to publish a flurry of anti-Semitic tweets in 2016.
‘Never send a human to do a machine’s job’, a quote from the iconic film The Matrix. But is the doom-ridden depiction of AI in contemporary science fiction correct?
AI is impeccable at carrying out repetitive tasks. It does not tire in the same way that the human mind or body might. Automating these types of tasks makes a great deal of sense and achieves cost savings for businesses. AI also provides a solution to the distorted effect of cognitive biases that affect the decisions of managers every day, a challenge that management theorists have contested and theorised about for over 50 years. However, the lack of EQ and perhaps an understanding of ethics is an enormous challenge faced by AI and ultimately signifies a limit to their abilities. Returning to the earlier point, do we really expect that the costs saved from automating something like nursing will be worth the loss of personal human touch? There is also the fact that while those in Big Tech and business talk very bullishly of the plethora of opportunities that AI will generate, its presence is not as highly-anticipated by the public who have fears about ethical dilemmas, surveillance, and data privacy. A study by Ipsos found that only 50% of people trust companies that use AI as much as they trust other companies. The public response to Mark Zuckerberg’s 1 hour 17-minute-long video describing his grand plans for the metaverse was one of partial ridicule but also unease. Some of the scepticism might be borne from headlines like the World Economic Forum’s prediction of AI wiping out some 85 million jobs by 2025. Although people should be cognisant of the fact that this loss of jobs will be offset by new jobs servicing AI. Harari, author of Sapiens, predicts that the job market of 2050 “may well be characterised by human-AI cooperation”.
A war of every robot against every man?
As we mentioned before, intelligence is not black-and-white so we cannot easily identify a winner and nor should we want to. It is counterproductive to address AI and human intelligence by pitting the two against each other in a fight to the death unless we want our lives to actually transform into something reminiscent of a dystopian sci-fi film. Yes, the future of work will resemble something very unrecognisable but in this world of new jobs, the relationship between humans and AI will be one of collaboration where AI will support human productivity.
Companies will benefit from optimizing collaboration between humans and Artificial Intelligence. What it will come down to is striking the optimal balance between how the human element and the AI element can interact and synergise processes. I refute the suggestion that AI will be the last invention humanity will ever have to make. The discovery of AI will enable humans to deliver the next great wave of industry-defining and ground-breaking innovations. But be warned, it is pivotal that as we integrate the technology we align its goals to our own. If we do not manage our AI, we may well find ourselves witnesses of Hawking’s stark prediction of the end of humanity at the hands of Artificial Intelligence.
There has been much ado made about the winners and losers of the global COVID-19 pandemic and the subsequent lockdowns. Cluttering the pages of the Financial Times and The Economist, have been tales of rising stars in the technology space such as Tesla Inc., who not only enjoyed a 650% increase in their stock price but also for the first time in its 19 year history turned a profit, who were lauded for their ingenuity and tenacity to weather the economic turbulence. Concurrently, others who were not so fortunate like Chinese property developer Evergrande (which saw its share value fall by 95%) were pitied for their financial imprudence and misfortune. Many would have also believed that the energy sector had garnered a similar sort of attention, especially considering the current role energy prices play in the record rate of inflation that we, globally, are facing. However, I contend that we, in our obsession with the outlandish, have ignored nuanced developments elsewhere along the energy supply chain, in particular, the oil refinery and oil tanker industries.
Ailing Refinery Industry
An oil refinery is an industrial plant that transforms or refines crude oil into usable products such as gasoline, diesel, and jet fuel. Like many others before, the year 2019 was a lacklustre year for the industry. The international benchmark Brent Crude Oil prices hovered around $64 a barrel throughout the year, remaining suppressed due to heightened US production for domestic consumption and significant Chinese economic slowdown leaving an excess of oil in the market languishing in refinery storage facilities across Singapore, Saudi Arabia, and Russia. So, when international lockdowns struck in early 2020, the refineries were not in the healthiest of positions to handle such a shock.
Over the course of nine months, beginning with one of the sharpest drops in global stock market history, the refinery industry faced a totalising exogenous demand shock in the form of international travel bans, curtailed social events and diminished road traffic.
This shock, oppressed demand with reductions of over 9%, tailing that trend, production experienced a 6.6% contraction, further glutting the oil markets, causing oil prices to fall as low as $9 a barrel but averaging $42 a barrel (a fall of over 34%) for the year. Market contractions are not good, but as the previous graph shows, refineries reduced production to nearly match demand, so why were oil prices so low and how is this different from other business cycle downturns?
Recall that by the end of 2019, storage facilities were already brimming with oil. So, despite production and consumption tracking one another there was an out-sized amount of oil sloshing around global markets intensifying the price plunge. This caused significant revenue reductions, for global and national refineries, and the lowest profit margins, industry-wide, in 20 years.
Another point to note: refining millions of barrels of oil a day can be an expensive enterprise, worsened still by the fact that a large portion of these costs are upfront capital expenditures. Such is the case that unless refineries are operating at minimum, 80% production capacity, it is simply unaffordable to operate them and most owners in that situation either convert the refinery into a storage facility or exit the market entirely, and that is exactly what happened. Of the top ten oil refining countries, who represent 62% of global production, three have closed a portion of their refining capability indefinitely with a further 9 countries, not in the top ten, permanently shutting down greater than 15% of their production capacity.
Invigorated Tanker Market
A product (or clean) oil tanker is a ship designed for the bulk transportation of oil products, from refinery stations to consumers. Similar to the refinery industry, the product oil tankers were not in great form in 2019. With lowered levels of international consumption, demand for transportation of oil products was found lacking in the form of reduced volume transportation. This only sustained the financial under-performance of clean tankers, in comparison to other sections of the energy sector, that has been characteristic of the industry since 2015.
What came as a surprise, however, was the reversal of fate for industry players in 2020. One would have envisioned that with halted demand for oil product transport, reflected in the respective fall of 11.3% and 8.3% in world imports and exports of oil products in 2020, that product tankers would have had to endure deepened financial difficulty, but that was not the case.
As the above graph shows, on the five major clean tanker routes transport prices were essentially unchanged or even increased with the Middle East to the Far East route displaying rises of 14.5%. So, how did this come about?
Contangos, or the situation where current (or spot) oil prices are lower than predicted future oil prices, are the main culprit for the improved favour that clean tankers basked in. With the cascading crude oil -and hence product oil- prices, traders in the industry anticipated that future prices would be higher. Additionally, onshore storage facilities at/near refineries, at the time, were already scarce. Armed with this knowledge, traders furiously began to charter product tankers as floating storage spaces; for as long as the cost of storing the oil was not greater than the expected margin between spot and future prices, these traders were content to just wait for prices to increase.
The use of product tankers as temporary storage facilities is not a new phenomenon and also prominently featured during the recession of the late 2000s. What makes this instance unique is how long it was sustained. For months, as opposed to a few weeks, product tankers, especially those who transported oil along the routes with less traffic, just had their tankers soaking up revenue which had doubled in a week. Consequently, the fall in tanker supply meant that whatever product oil was transported could be serviced by a shrinking pool of tankers, shoring up spot rates for tankers.
Important Implications
The reverberations of this fascinating dynamic that occurred in 2020 will be felt for years to come, in forms I’m sure we have yet to fully comprehend. Nevertheless, I will attempt to detail two such consequences of that strange period on our current day.
The limited refinery production capacity coupled with the increased cost to transporting oil has caused frictions in the current provision of oil products through a self-sustaining price inflation spiral. When demand for oil products returned to pre-pandemic levels in 2021, as production was slow to catch up, the price of oil shot up, increasing demand for (and price of) gas, a close substitute. As gas is also an input to the production for product oils, this only further delayed oil production sending both the price of oil and gas ever-higher fuelling food price inflation and threatening energy poverty across the globe.
An unanticipated result of this development is Russia has been able to secure considerable financing of its war against Ukraine through the sale of oil and gas to at first Europe, but now, India and China as the price of oil and gas remains elevated.
On a more positive note, the energy insecurity has brought the green energy transition to the forefront of policy discussions. Not because relying more on renewable sources of energy is better for the environment, but because it contributes to energy independence and reduces geopolitical risk. If nations are able, through the production of sustainable domestic energy, to temper their reliance on foreign sources of energy they’re better able to not just prevent dizzying energy price inflation but also confront belligerent governments in a robust manner.
Conclusion
The addition of the COVID-19 pandemic to the growing list of Black Swan events, whilst spurring on the decline of the oil refinery industry and gifting product oil traders the opportunity to buy a barrel of oil (containing 158 litres) for the price of a Boojum burrito, is something to remember, I think a lot of good will ultimately come from it.
Although currently, we are suffering under serious economic and business environment instability, the pandemic and I am not sure we have overcome much of the chaos that has come from its immediate consequences, the opportunity for the long term re-orientation of our economic and commercial practices to be more aligned with our vision of what the world should be like is a reason to be optimistic.
Trinity Business Review 