Talent's Quantum Leap

Why building a transformational team will be similar to building a quantum computer

If you haven’t been paying attention to quantum tech, now may be the time to start. According to CB Insights, 2021 was a record year for quantum tech funding, with nearly $1B invested this past year alone (an increase of over 100% from 2020). Complementing funding in the space are movements by tech giants such as Google, IBM, Intel, Amazon, & Microsoft, all of whom are solidifying places for themselves in this quantum race by building their own quantum computers and developing applications for enterprise use cases. So… why the hype? Well, quantum computing has the power to revolutionize both industries and the world as we know it. From expediting drug R&D to cybersecurity encryption, the potential of quantum computing is so vast that even experts have a hard time conceptualizing the full extent of what quantum computing’s impact could look like.

You may be asking yourself, what does quantum computing have to do with the future of talent? On the surface, comparing the two may seem like a stretch, but taking a deeper lens to each can draw a spooky (see what I did there?) number of parallels between the two.

A brief introduction to quantum computing

I would like to preface this section by saying that in no way am I an expert in quantum mechanics or computing, but I do find each to be fascinating. If you’re looking for a great intro video to quantum computing, I found this 10-minute video by Quanta Magazine on YouTube to be incredibly informative.

The idea of quantum computing really started in the 1980s when quantum physicist – Richard Feynman – realized that classical computers cannot keep pace with the increasing complexity of quantum calculations. Feynman found that the relationship between quantum additions and the cost to run simulations was exponential, meaning that for every quantum particle that he added to his simulations, the cost to run those simulations grew exponentially. As such, Feynman wanted to build a tool that was made up of quantum elements so that the quantum realm could be adequately explored. Hence, the introduction of quantum computing.

Whereas traditional computing relies on bits to store & process lines of information, quantum computing relies on qubits. Unlike bits, which can only hold a value of 0 or 1, qubits can simultaneously be 0, 1, or a linear combination of 0 and 1. If you’re scratching your head for how that can be, then you’re not the only one. As Scott Aaronson, a theoretical computer scientist at UT Austin, puts it, “Quantum mechanics, at its core, is a change to the rules of probability. And this is also where the power of quantum computing comes from – from these different rules of probability than the ones that we’re used to.” Two quantum concepts that help explain this are superposition and entanglement.

Superposition

John Chiaverini, a researcher at the MIT Lincoln Laboratory’s Quantum Information and Integrated Nanosystems Group, describes superposition as the phenomenon when, “A quantum particle can act as if it’s in two places at once.” A particle being in two places at once would be improbable by our typical rules of probability, but remember, we’re not playing by our rules of probability. Applying superposition to quantum computing, superposition is the state in which a qubit exists prior to being measured, and – to oversimplify it – relates to the fact that a qubit can simultaneously be a 0, a 1, or a 0 & 1.

Entanglement

When multiple qubits are in a closed state of superposition, they relate to one another through entanglement. John Preskill, a Richard P. Feynman Professor of Theoretical Physics at CalTech, describes entanglement as the characteristic correlations among parts (qubits) of a quantum system. He describes entanglement like a book: when you look at the pages one-at-a-time, what you read doesn’t result in any useful information. This is because information is not encoded on the individual pages themselves, but rather in the correlations among the pages. To get the full picture, one must read the book to collectively observe many pages at once. Similarly, to measure a quantum system, one must collectively observe the probabilities of many possible outcomes.

The limitations of classical computing

Quanta Magazine provides a great example for understanding the limitations of classical computing. Let’s say one had a 10-qubit computer. This qubit computer could store 2^10 (or 1024) values in parallel, in which a classical computer would require 16,000 bits (or 2 KB) to describe that entangled configuration.

Now let’s say one had a 500-qubit computer. To describe that entangled configuration, a classical computer would need more bits than there are known atoms in the universe, which reaffirms Feynman’s theory that classical computers aren’t scalable enough to simulate complex quantum simulations.

For reference, the largest quantum computer to-date is 256 qubits, which was built by QuEra Computing, a Boston startup comprised of MIT and Harvard physicists.

The difficulties of building a quantum computer

Without the ability to measure the information of the outputs of qubits, quantum computers are of no use. However, entangled states are so delicate that when a quantum system is measured, it collapses back to a classical state. Aaronson says, “if anything carries away information about whether a qubit is 0 or 1, then the effect of the qubit will be exactly as if someone had measured it,” meaning the quantum state will collapse back to a classical state.

To measure information of the outputs of qubits, quantum systems require interference. Scientists can manifest interference in quantum systems by leveraging quantum algorithms, which use qubit gates to increase the probability of seeing one of the right answers. Because we don’t know in advance what the right answer is when diving into a quantum problem, one of the difficulties of building quantum algorithms is how to generate the right interference to increase probabilities for seeing the right answers. It’s quite a paradox, but large advances have been recently made in the study and application of quantum algorithms.

Quantum computing summary

Quantum computing will help us solve complex problems that current computers are unable to. As the world becomes increasingly complex or as we look to solve problems that are incredibly complicated, quantum computing will be a necessary tool for helping us arrive at the right answers. However, quantum computing relies not just on qubits (paradoxical values that can be 0s, 1s, or a linear combination of 0s & 1s), but measuring qubits when in an entangled state. One of the difficulties of measuring entangled states is that any measurement of that state (any release of information) will revert the quantum state back to a classical state. With that in mind, for quantum computers to be useful, they need complex quantum algorithms that increase the probabilities of seeing the right answers, but creating these algorithms is incredibly difficult to do because we don’t know what the right answers should look like when going into the problem.

Sounds simple, right?

A brief introduction to transformational teams

In Harvard Business Review’s (HBR) most recent issue, the article Reinventing Your Leadership Team raises some interesting points. In it, the authors argue that in this increasingly complex world, digitization – although a priority – is table stakes and not a competitive advantage. Rather, to build competitive advantages in this new age, companies must build leadership teams that are geared for transformation. Yet building transformational teams relies on finding leaders who can balance a set of paradoxical expectations.

The six paradoxical expectations

In the article, Strategy& outlines six paradoxical elements expected of leaders in this new day and age. These aptly named archetypes are the strategic executor, the tech-savvy humanist, the high-integrity politician, the humble hero, the globally minded localist, and the traditioned innovator.

Let’s look at the strategic executor, for example. Strategy& describes the strategic executor as having “bold, ambitious ideas as well as the practical capabilities needed to realize visions.” The authors go on to say that whereas it used to be good enough for a leader to be either a visionary or an operator, it is no longer the case – transformational leaders need to be both.

The significant proficiency gaps

In the article, one can find the results of a 2021 global survey conducted by Strategy&, in which the firm asked 515 businesspeople the following two questions about the six paradoxical archetypes:

1. Are both elements of each paradoxical archetype critical to your organizations’ future success?

2. Are your organization’s leaders good or best-in-class at balancing both paradoxical elements?

What is concerning is the significant proficiency gaps that are represented in the respondents’ answers.

The two archetypes that are most critical to future organizational success are also the two archetypes that have the largest proficiency gaps.

The two archetypes that are most critical to future organizational success are also the two archetypes that have the largest proficiency gaps. While 96% of respondents agreed that strategic executors would be critical components of their organizations’ future successes, only 51% felt that leaders in their organization were proficient in balancing the paradoxical elements of a strategic executor. Similarly, 90% of respondents agreed that tech-savvy humanists will be critical components of their organizations’ future successes, yet only 39% responded that their organization’s leaders are proficient in balancing those paradoxical needs. That represents a 45% and a 51% proficiency gap, respectively, in the two most critical archetypes for driving future success.

The power of collective leadership

In recognizing these gaps, the authors of the article state that addressing the leadership gaps won’t mean solely building up individual executives’ skills. Rather, companies will need to improve collective leadership – and do so quickly. This is because we’re seeing a fundamental shift in value creation: companies will be forced to, “switch from competing with rivals to cooperating with partners in networks and ecosystems to create value in ways that no single organization can manage alone.” Doing such will require a fundamental shift in perspective and require leaders to challenge every element of their company. Rather than solely focusing on siloed areas of responsibility, leaders must work as a team to not just design the future of the organization, but also navigate their org towards it.

What building transformational teams and quantum computers have in common

Just as we’re not entirely sure what the full potential of quantum will bring, so – too – are we not entirely sure what the full potential of transformational teams in this new day-and-age will look like. However, each will be necessary for solving incredibly complex problems and creating exponential value in this new age. So, what does building a transformational team and building a quantum computer have in common?

The paradoxical elements of leadership are like qubits

Whereas the leaders of yesterday could either be one element of the paradox or the other, today’s leaders will be expected to balance these paradoxical elements to drive value in this increasingly complex world. Similarly, just as bits were ample for computing the solutions to many of yesterday’s challenges, we will need qubits to guide us to the right solutions to today and tomorrow’s incredibly complex problems.

Perhaps, then, we shouldn’t call executive-level roles in our organizations leadership positions, but instead leadership superpositions – especially if we expect these leaders to have the superpower of balancing paradoxical needs.

Collective leadership is like quantum entanglement

Just as when multiple qubits are entangled when related to one another in a closed state of superposition, so – too – are leaders entangled when working collectively with one another. Let’s apply Preskill’s book example of entanglement to collective leadership. Each leader on a team can author his or her own page. However, each page alone won’t make anywhere near as much sense as all the pages together. The cohesion of the narrative in its entirety will drive exponentially more value than a single page of that narrative could ever drive alone.

The formula for building a team is like building a quantum algorithm

In the HBR article, the authors note, “no high-performing leadership team we know was built overnight, nor did it do everything perfectly.” If we knew what the optimized state of value creation should look like in this new day-and-age, then we’d be able to reverse-engineer the algorithm to build the necessary teams to get there. However, we do not know what that truly optimized state of transformative value is. The reality is that it’s contingent on a variety of factors that are going to be different for each company. This is similar to the difficulty of building quantum algorithms: because we don’t know what the right answer is in advance when diving into a quantum problem, the difficulty of building a quantum algorithm is how to generate the right interference to increase probabilities for seeing the right answers.

Just as quantum theorists aren’t blindly taking shots to build these algorithms, neither should firms take shots in the dark to build their leadership teams. Strategy& provides a great four-part framework in the article for how companies should build their leadership teams and recommends that companies need to work on all parts of this framework simultaneously – not sequentially – because each part reinforces one another.

Summary

We live in an increasingly complex world, and if we want to start driving novel value in this new age, then we’re going to need to build new engines to help us make that happen. Whether those engines are quantum computers or transformative teams, there are lessons and similarities that we can take away from each to help guide us for getting on the right path quickly. But it should be known that building either of these engines is no easy feat, and we’re not going to get the answer right the first time. It should also be known that it takes perceptive people who are betting on the future to make this happen.

Just as quantum computers are not going to be useful for everyone, so – too – are transformative teams not going to relevant for all companies. However, companies that are looking to shape the future should begin thinking about how they can take a quantum leap for building their leadership teams to add value today, as yesterday’s approaches will no longer work.

The good news is that you don’t need to be a quantum theorist to make this happen. You just need to start soon and move quickly to increase the probability of finding the right answer. And if it’s any consolation, just as you may struggle to truly understand quantum mechanics, I imagine that quantum theorists would struggle in a similar manner when it comes to building transformative teams.