Introducing the LIS MBA
The LIS MBA is for people who want to understand the world we’re in and lead better within it.
Any MBA could say that, but in this piece, we’re going to try to show what that really means and why it’s hard for traditional programmes to do it.
Our world is typified by change. And much of that change is ‘nonlinear’. It proceeds in fits and starts. It comes slowly and then all at once. One day something is on the horizon, and then it’s our new reality. Conflicts. Financial crises. Pandemics. But also: medical breakthroughs. New technologies. Social revolutions.
Our world is also (and relatedly) complex. People, organisations, places, nations, and ecosystems are interdependent.
Most of us have been brought up with a form of science that teaches us to see a simpler world. To focus on what is static. To break things down and look at them one by one. To see the parts rather than the whole. This approach may be necessary for step-by-step progress of basic science, but it is poor preparation for organisational leaders. In place of reductionism alone, we need it combined with systemism.1
The LIS MBA positions systems thinking and system science not as add-ons, but at its core. It teaches these approaches not in the abstract, but in relation to the real range of natural and artificial systems that organisations depend on, drawing on our faculty’s expertise from across the arts and sciences.
LIS MBAs will learn to see more of the world around them and identify risks and opportunities for their organisations. They will develop and practise foresight and repeatedly review past predictions to identify their misconceptions and blind spots, learning to give an honest appraisal of where things went wrong and changes have to be made. They will learn to work with different logics and languages, recognise incommensurabilities, find points of integration and communicate a shared way forward.
Grasping a shifting terrain
The degree is based around six 'shifts': complexity, energy, intelligence, ecosystems, trust and longevity. Each represents a fundamental feature of our world that is undergoing important change.
The nature of these changes differs: complexity is increasing, whilst trust is decreasing; intelligence is morphing rapidly whilst energy supply is not changing quickly enough; natural ecosystems are depleting whilst man-made ones are growing, and human longevity is extending in some contexts but dramatically at risk in others.
Yet whatever the direction, these shifts are linked in that each is a change that will impact the rest of our lives. Trends, technologies, strategies, and targets come and go, but these shifts are here to stay.
Shift #1 Complexity
Complexity describes relationships or systems made up of many interacting parts, giving rise to emergence of new phenomena that have new properties and behaviours going beyond that of the parts. In the context of complexity, cause and effect become difficult to trace and consequences are hard to predict.2
Increasing complexity is a long-term trend. The connectedness of modern systems via transport, communication technologies, and digitalisation has created more and more phenomena which are characterised by complexity.3
But this trend is reaching a tipping point: increases in computing power are bringing new methods into policy-making and corporations aimed at taming complexity.4 Complexity is no longer just an abstract concern but one that we can analyse and work with – up to a point. This is a development with broad implications for Strategy and Management, demanding dynamic, simulation-based approaches.
This shift introduces a key set of usable qualitative and computational complexity methods to consider their potential and limits. It also asks us to face the human and leadership implications of complexity: if cause and effect are not linked as we’d like to believe, what does this mean for our personal missions and purpose?
Shift #2 Energy
The energy transition – the shift from fossil fuels to renewable energy sources – is a shift we might all welcome, but one that demands a vast scale of proactive change. It requires new materials, new infrastructure, new technologies, and new behaviours. Every sector needs to engage with and understand its implications.
Studying the energy transition provides a way into Finance and Economics that emphasises market dynamics over equilibrium. It illustrates the challenges for new entrants, the role for governments, regulation and infrastructure, and how new innovations are funded, priced and embedded. The complexity of renewable energy markets provides a model and provocation for any efforts at regenerative innovation and market transformation.
Ultimately, the study of Energy provides an understanding of Operations, from the ground up. Whether measured in kilowatts, joules, calories, or CO2 uptake, energy is the foundation of any business process. The study of energy focuses us on first principles and identifying the potential for efficiencies, circularity, and exchange.
Shift #3 Intelligence
The robots are now well and truly here, at least when it comes to knowledge work. The era of pitting machine against human intelligence is giving way to visions of more integrated human-machine interaction.5 This shift demands knowledge of the workings, energy supply and regulation of large language models, as well as approaches beyond machine learning. To see beyond hype, leaders need sufficient technical knowledge to have in-depth conversations about particular models, particular uses, and their implications.6
To make good decisions about where to utilise and develop artificial intelligence, we need clear ideals about the nature and purposes of intelligence overall. The breadth of human intelligence is not well-captured by psychometric assessments that imply intelligence is captured by a particular performance.7 Benchmarking AI on such tests is unlikely to lead to the most productive usages.
Instead, this block understands intelligence in the ability to adapt and uses examples of collective intelligence to illustrate what this means in practice. From this, leaders working in specific sectors can develop a sharper picture of what forms of intelligence are most adaptive in their context and where machine learning might supplement human capabilities.
This shift ultimately takes a revised approach to traditional questions of Organisational design, Human resource management, and Strategy, asking: how can we optimise human-machine intelligence in a given organisation – and to what end?
Shift #4 Trust
Trust is the fundamental ingredient of social institutions. Markets, financial systems, democratic and judicial processes rely on sustained, widespread trust.8
Yet we’ve seen overall declines in trust in government, business, and the media.9 The consequences of this are far-reaching. For individual businesses, brand trust has become more complex, as some consumers are paying attention to many more different aspects of a company’s behaviour.10 At the societal level, comparative research suggests that a shift from high-trust to low-trust societies undermines economic activity.11 All indicators suggest that the proliferation of generative AI will undermine dispositions of trust,12 which in turn may be a key inhibitor of the development of AI technologies.13
Humans cannot afford - cognitively or financially - to have to think carefully about every decision we make. If we cannot rely on institutions or trusted third parties, the result is far too few decisions being made and overall inertia, lack of action, lack of investment, and low productivity. We need to be able to create new forms of trust, through culture, institutional innovation or technologies.
This shift demands that we look carefully at the relationships between Governance, Accounting and Marketing, and reconsider how organisations relate to wider publics. How do organisations prove their value to an audience? What are the role of new reporting mechanisms, greater transparency through AI, or more human connection?
Shift #5 Ecosystems
A shift in trust ripples throughout the social world. Shifts in ecosystems impact the wider encompassing natural world: a world that we are, of course, part of.14 Organisations are part of economies and societies that are nested in and rely on a global ecosystem made up of many, many interconnected microsystems.15
Multiple natural ecosystems are now at risk of collapse.16 The implications are seen in increased ‘natural’ disasters, and consequent effects on refugee crises, supply chains, and destabilising inequalities. As with Intelligence, the Ecosystem shift focuses us on interactions between human and non-human activity. And as with Energy, the necessary shift is one from resource depletion to regeneration. This is vast work, touching every kind of production.17
An ecosystem perspective also provides us with a way to understand healthy growth and scale. Biomimicry - taking inspiration from ‘nature’ to address design challenges - is now everywhere, not least in the way that we might create new forms of organisation modelled on ecosystems. The ecosystem shift then is how we become more integrated into the natural world, changing what we do and how we do it.
Shift #6 Longevity
The shift in longevity is typically heralded in terms of increased lifespans, but the most significant longevity shift is the change from short to long time horizons. Fifty years or so into the liberal market economy pivot to shareholder value and profit maximisation as the steering wheels of business, there is widespread dissatisfaction with the ensuing behaviours of short-termism and associated cultures of consumerism and waste. From multiple cycles of efforts to rethink the purpose and societal role of business, we have triple bottom lines, ESG, and public benefit companies. What of these will stand the test of time? Where are the opportunities for organisations to focus on creating value that lasts?
Moving from a short-term to long-term mindset is not only an organisational challenge. It is a deeply personal one. With the technological conditions in place for rapid and profound changes in how we work, coupled with a collective hope for lifespans that might continue into our eighties and beyond, how might we evolve the role of both work and leisure in our lives? What do the Arts, Humanities and Sciences together teach us about what forms of value most endure? And what organisational forms allow us to create and distribute this value in fair and truly sustainable ways?
By stepping back from the current business disciplines, we can look afresh at the traditional teachings on Governance, Finance, Human Resource Management, and Accounting, and focus on how the frontiers of each of these fields offer the pieces of business models and practices for the long-term.
What about everything else?
We’ve chosen these six shifts as fundamental features of our world with broad implications, as well as routes into advanced understanding of business and management.
Each shift is also an example of complexity at work. Energy, intelligence, trust, ecosystems and longevity are each phenomena that arise from interacting parts in only partially trace-able ways. They cannot be bought, sold, switched on or off, or legislated for. Guiding these shifts in positive directions demands a special kind of leader.
There are of course some other candidates for such shifts: power, value, love – pick your abstraction. But we stand by this set as offering as powerful lenses for the current organisational context.
The next section of this essay details how we will bring the shifts to life and make them the context in which to develop into a more capable, more wide-ranging leader.
The shifts as live cases
Cohorts study the shifts in six 10-week terms involving weekly virtual seminars with selected experts. Each term is bookended by immersive, onsite experiences where the cohort applies key practices with a set of partner organisations. Through this structure, they develop a set of core skills:
#1 Future problem framing
The launch for each shift includes a day-long session of problem discovery and framing. Drawing from their own organisational contexts and alongside LIS partner organisations, cohorts will explore the contemporary state of the shift. By focusing on emerging issues and the interactions between them, they will refine tractable problem framings using approaches developed at LIS. Individuals will then select one of these to pursue during the term.
This approach to problem framing is guided by foresight and anticipation methods: methods to support systematic reasoning about possible and probable futures. This involves a good grasp of current system dynamics and how these might unfold and interact over time, informed by analysis of current data and imagination to speculate.
#2 Interactional expertise
The knowledge required of a leader is not the same as that required of an academic or technician: it is the big picture understanding to weigh up what counts as relevant considerations, and sufficient understanding of each relevant area to ask good questions about it. This sufficient understanding is what’s called ‘interactional expertise’, and it can be recognised in the ability to ask precise and meaningful questions of field experts.18 This type of expertise is becoming even more valuable in the context of generative AI.19 Weekly seminars promote students’ ability to rapidly develop and test this form of expertise, by giving them opportunity to probe leading experts in different aspects of the shifts. All students will be required to submit questions, students will evaluate each others’ questions, and take turns in chairing sessions and leading the questioning.
#3 Range and relevance realisation
Each shift culminates in a day-long ‘crit’, where students and LIS partners bring work-in-progress. Students are evaluated not on the state of their work but on the quality of feedback they give to others: the desirable skills to develop are the ability to rapidly understand someone else’s context and needs and identify a relevant angle or perspective. In epistemological terms, this has been called ‘relevance realisation’.20 Naming it in this way helps to clarify what kind of thing this part is aiming, but as with many ‘higher-order’ capabilities (communication, critical thinking), it is a cluster of skills and dispositions that also rely on an appropriate range of background knowledge.
By range we mean the breadth of awareness of what is and what might be. Broadening this awareness involves meeting new fields of intellectual and practical knowledge and being equipped to engage with them. Range is of great value because it provides the basis to see what is relevant to a given problem or circumstance and to see more risks and opportunities, including second-, third-order etc. In the context of readily accessible human or automated knowledge retrieval, range is the key differentiator which allows someone to know what knowledge to access at any given time.
#4 Synthesis
Rigorous, disciplined synthesis is one of our specialities at LIS. Rather than studying single common cases or texts, LIS MBA students will practise taking deep dives into different perspectives on a question and then working to integrate these viewpoints as a cohort.
The process of integration and synthesis is where the rigour of interdisciplinary learning becomes apparent: to synthesise we have to properly grasp the distinctions between perspectives, clarify different disciplinary logics, languages and methods, and learn about different approaches to combine them.
Integration coaching
Alongside the whole cohort seminars, LIS MBAs meet each week in small groups for sessions focused on integration and practice. As with traditional coaching this is focused on an individual and their context and goals, but it also builds on what is being learned in the rest of the curriculum, providing means to integrate that learning into daily work and development.
Small group size and expert, intellectually broad coaches – who combine academic and industry experience and knowledge of adult development – provide the means for students to progress in their own cognitive development, strengthen their grasp of key scientific and philosophical concepts, and repeatedly practise applying skills to their own individual contexts.
In the LIS MBA, coaching focuses on three practices:
#1 Representation
The complexity of modern systems cannot be held in anyone’s head. Consequently, creating, commissioning and working with representations of systems are core skills for a modern leader.
Systems mapping is the counterpart of systems thinking, which focuses on relationships and interdependencies over siloes. LIS teaching systems mapping primarily in the form of causal loop diagrams. Whilst this is primarily a qualitative practice, systems modelling (or simulation) is a quantitative and computational approach the provides insights into system dynamics and feedback. LIS MBA students will practise their own individual mapping by hand, as well as gain familiarity with different forms of modelling and how to deploy simulation expertise in an organisation.
#2 Judgment
Decisions should be based on analysis, but analysis can only take us so far. It is not possible to model complex systems in their entirety, and most human and organisational challenges involve multiple, conflicting values that cannot be reconciled through analysis alone. Decisions about what actions to take (or not take) in an organisation or in a complex environment always rely on judgment. How does one develop good judgment?
Refining our judgment requires practise. LIS MBAs will be required to make weekly judgments about emerging situations, whether in their own work or in the core shifts they are studying. Each week they will review past judgments and reflect on whether there position has changed: perhaps because of a new perspective, new data, or a prediction that panned out differently. Individuals will be coached by faculty and their peers to gradually become more aware of their blind spots and misconceptions.
#3 Care
Care refers to a particular quality of attention. Leadership as a whole can be thought of as a care practice: taking account of the needs of a particular organisation, environment, or group and seeking to help it grow in healthy ways. Framing leaders’ work as care balances a focus on the day-to-day and the long-term: both are important. Integration coaching provides the space for peers to work on their care practice together: clarifying motivation, managing trade-offs and dilemmas, and cultivating social and emotional capacities to work through conflicts.
Demonstrating new capabilities
The LIS MBA is unique not just in what and how we teach but how we assess.
Assessment is not a prominent feature of most business education. There is a poor track record of evidence about what knowledge and skills students gain or retain by the end of their courses. More generally in the higher education field, many of the tasks set to assess students are now precisely those that can be done adequately using generative AI.
Our assessment approaches are designed to cover key dimensions of student learning and development in the programme.
Expert questioning requires students to have mastered a topic sufficiently to be able to ask a well-judged question of an academic or expert practitioner. Students will submit questions to experts both in writing and live via seminar sessions and ‘crits’ – in which partner organisations present ideas for critique. Questions will be evaluated on the extent to which they provide valuable new perspectives or reduce blind spots.
Progress testing is an approach used in medical schools to assess students’ scientific knowledge and clinical expertise. We will be the first MBA to adapt this approach to the scientific and technical knowledge of the MBA core. Students will be able to demonstrate their competence in key functional skills in accounting, finance, management and analytics. The test (with different questions) is taken multiple times over the degree, allowing students to accumulate the relevant skills across different modules.
Standardised assessments of complex decision-making are part of a suite of novel assessment methods available to LIS via our partnerships with advanced research organisations.21 Through our collaborations, we have the opportunity to evaluate growth in higher order capabilities and ‘soft’ skills (‘soft’ only in that they are too fuzzy for traditional assessment approaches).
With this range of assessments, we aim to get closer than any existing programme at evaluating what our students are really learning.
Beyond prestige
The MBA has become intertwined with the slippery educational quality of prestige: the notion that a particular degree and its holders are worthy of admiration.
Fun fact: prestige derives from the Latin ‘praestigium’, meaning ‘illusion’.
As we enter the second quarter of the 21st century, it’s high time we started looking under the hood of educational credentials and asking what they really confer. Educational programmes will always serve multiple functions and sorting and signalling will be among those, but we need degrees to be more than this. There is too much actual necessary knowledge that needs to be circulated, comprehended and acted upon.
The LIS MBA is designed to be a real education about real things. We trust it will meet its match in a founding cohort with real motivations to put it to use.
End notes:
1 For one overview account of this from LIS faculty Duncan Austin, see: https://bothbrainsrequired.com/wp-content/uploads/2020/06/From-Machine-to-Network-Final-PTS-February-2020.pdf
2 Importantly, this difficulty with prediction is not just due to a lack of data. See the work of LIS contributor Tim Davey on Incoherence: https://orcid.org/0000-0002-1082-7402
3 For a brief overview of ways of studying increasing complexity over the long-term, see: https://bigthink.com/13-8/techno-social-evolution/
4 A leading example is the use of ‘digital twins’, e.g.: https://www.turing.ac.uk/research/research-projects/complexity-twin-resilient-ecosystems and simpler varieties of agent-based models, e.g.: https://www.bankofengland.co.uk/quarterly-bulletin/2016/q4/agent-based-models-understanding-the-economy-from-the-bottom-up
5 For one version of this, see the work of LIS faculty member Niccolo Pescetelli: https://www.niccolopescetelli.com/
6 For an example of an interdisciplinary scholar bringing technical knowledge to bring enhanced professional (in this case legal) scrutiny to AI, see the work of LIS faculty member Emma Rengers: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3899991
7 The foundational work on humans’ ‘multiple intelligences’ comes from Harvard Professor and LIS Fellow Howard Gardner: https://www.multipleintelligencesoasis.org/
8 The classic work on this is Daron Acemoglu and James Robinson’s Why Nations Fail, an introduction to part of the body of work that saw them awarded the Nobel Prize for Economics in 2024.
9 https://www.edelman.com/trust/2025/trust-barometer
10 https://www.edelman.com/trust/2023/trust-barometer/special-report-brand-trust
11 The body of research underpinning the link between trust and economic outcomes is summarised at: https://ourworldindata.org/trust
13 https://hbr.org/2024/05/ais-trust-problem
14 This view can be framed in more economic (‘ecosystem services’) or more ecological terms. For an introduction to the ecological perspective from the perspective of an economist, see LIS faculty Duncan Austin: https://bothbrainsrequired.com/wp-content/uploads/2022/05/2021-02-Can-ESG-Grasp-What-Ecology-Says-Final-11-pages.pdf
15 This ecological perspective merges with the tradition in organisational theory to apply an ecological perspective to the functioning of organisations and markets, typified by Michael Hannan and John Freeman’s Organizational Ecology (1989). This approach has longstanding antecedents and many contemporary applications.
16 For an example of recent work on how researchers model risks of collapse, see: https://www.nature.com/articles/s41893-023-01157-x
17 For a partial overview, see the Dasgupta Review commissioned by the UK government: https://www.gov.uk/government/publications/final-report-the-economics-of-biodiversity-the-dasgupta-review
18 Interactional expertise is a core concept in our Cross-functional Leadership course: https://www.lis.ac.uk/professional/cross-functional-leadership
19 Whilst they don’t use the phrase ‘interactional expertise’, this perspective is developed in a recent paper from George Siemens and Mihnea Moldoveanu: https://arxiv.org/abs/2501.00867
20 A phrase coined by philosopher and psychologist John Vervaeke, see: https://academic.oup.com/logcom/article-abstract/22/1/79/1007787
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