Data Analytics

Why organisations work with Tim Ringo A practitioner thesis on productivity, not a survey of the field. Solving the Productivity Puzzle won the HR & Management category at the Business Book Awards because it sets out a specific operating model for connecting engagement, performance and learning, rather than describing the problem. Three decades inside the firms that built the modern HR function: Accenture, IBM and SAP SuccessFactors, including global leadership of IBM’s 1,500-strong Human Capital Management consulting practice and EMEA leadership at SAP SuccessFactors. A rare combination of HR strategy and workforce analytics credentials, evidenced by Calculating Success, his Harvard Business Review Press book on workforce analytics co-authored with Carl Hoffmann and Eric Lesser. Recognised peer authority: named to HR Magazine’s Most Influential HR Thinkers list in 2022, alongside the people the audience is reading. A working point of view on AI in the workplace from someone who has run global HR technology programmes, not a commentator new to the topic. Biography highlights Named to HR Magazine’s HR Most Influential Thinkers, 2022. Author, Solving the Productivity Puzzle (Kogan Page); Category Winner, HR & Management, Business Book Awards. Co-author, Calculating Success (Harvard Business Review Press), on workforce analytics. Former Vice President and Global Leader, IBM Human Capital Management consulting practice. Former Vice President for EMEA, SAP SuccessFactors. Chartered Fellow of the CIPD; BSc, Fisher College of Business, The Ohio State University. Biography Most large organisations now spend more on HR technology, engagement programmes and learning platforms than at any point in their history. Productivity has not followed. Tim Ringo’s work begins where that gap sits, and treats it as a design problem inside the people function rather than a cultural mood. His 2020 book Solving the Productivity Puzzle, published by Kogan Page, won the HR & Management category at the Business Book Awards. The argument is operational: engagement, performance management and learning have to be wired together, and supported by analytics, before any productivity number moves. His earlier book with Carl Hoffmann and Eric Lesser, Calculating Success, was published by Harvard Business Review Press and helped to define what serious workforce analytics looks like inside an enterprise. The credibility behind the work is built over three decades. Ringo led IBM’s global Human Capital Management consulting practice, with more than 1,500 consultants worldwide, ran SAP SuccessFactors HR advisory across Europe, the Middle East and Africa, and spent sixteen years as an executive partner in Accenture’s Human Performance service line. He is a Chartered Fellow of the CIPD and was named to HR Magazine’s Most Influential HR Thinkers list in 2022. For senior HR audiences, that mix is unusual. Ringo can move from a board conversation about AI in the workforce to a working session on engagement metrics or HR technology investment, and bring the same operating language to both. His view on generative AI at work is a practitioner’s view, formed inside the systems that the rest of the function relies on. Key speaking topics Workforce productivity and engagement Digital HR transformation Workforce analytics Generative AI in the workplace Employee experience and retention Workforce wellbeing strategy HR technology investment Ideal for CHROs, CPOs and HR directors leading productivity, engagement or HR technology agendas Executive teams reviewing return on HR technology and workforce analytics investment HR leadership conferences, CHRO summits and people analytics events Boards considering the workforce implications of generative AI Audience outcomes A clearer view of where productivity is actually lost inside the organisation, and which HR levers move it. A working model for connecting engagement, performance and learning to business outcomes. A practical sense of what good workforce analytics looks like, and what most organisations are still missing. An informed perspective on how to introduce generative AI to the workforce without losing trust or governance.

Why organisations work with James Hardy He has run growth on both sides of the platform divide, leading EMEA for Alibaba and now global retail at Flutterwave, so he can argue marketplace strategy from inside the operating model, not from a consultancy slide. He co-founded Avenue51, the platform that won the Queen’s Award for Enterprise in 2020 and The Guardian Start Up of the Year in 2016, which gives him founder credibility on selling Western brands into China. He frames e-commerce as ecosystem competition, not site optimisation, which reframes how boards think about platform dependency, payments infrastructure and customer data. He is one of the very few speakers who can speak with operator authority on Africa as a commercial market, via Flutterwave’s role as the continent’s largest fintech. Biography highlights Head of Global Retail & Market Development at Flutterwave, Africa’s largest fintech. Former Head of Europe, Middle East and Africa at Alibaba.com. Co-founder of Avenue51, the UK platform that helped Western brands enter China. Avenue51 won the Queen’s Award for Enterprise, International Trade, in 2020 and The Guardian Small Business Showcase Start Up of the Year in 2016. Named in the Financial Times Leap 100. MBA, Melbourne Business School; earlier career as a solicitor at Mishcon de Reya and Travers Smith, then General Counsel at Next 15, Bite Communications and Text 100. Biography Alibaba and Amazon are not the same business and never have been. One is a vertical operator that buys, stocks and ships. The other is a payments-and-data ecosystem that lets merchants sell. Hardy ran EMEA for Alibaba, and the distinction shapes how he advises Western brands on international growth. Before Alibaba, he co-founded Avenue51, the UK platform that helped European brands build market share in China through Tmall and the Alibaba marketplaces. Avenue51 won The Guardian Small Business Showcase Start Up of the Year in 2016, and the Queen’s Award for Enterprise, International Trade, in 2020. His Financial Times Leap 100 listing came out of that period. He now runs global retail and market development at Flutterwave, Africa’s largest fintech, which gives him a live operator’s view of where commerce, payments and platform competition are heading next. That perspective is rare on the speaker circuit. Most e-commerce speakers come from one platform, one geography, or one consultancy lens. Hardy has been an operator inside Alibaba, a founder selling Western brands into China, and is now building consumer and SME revenue across Africa. His earlier career was legal, with stints as a solicitor at Mishcon de Reya and Travers Smith and General Counsel roles at Next 15, Bite Communications and Text 100. That background shows up in how he handles questions on platform terms, data sovereignty and the contractual asymmetry between brands and marketplaces. Key speaking topics International e-commerce and retail globalisation Alibaba and Amazon: comparative platform strategy Marketplace and ecosystem business models China market entry for Western brands African commerce and fintech infrastructure Data-driven decision-making in commercial strategy Corporate innovation and startup operating models Ideal for CCOs, CMOs and heads of ecommerce planning for international or marketplace expansion Boards weighing platform dependency, marketplace risk and channel strategy Brand and retail leadership teams entering China, the Gulf or Africa Corporate innovation leads to working on ecosystem and platform plays Audience outcomes A clearer view of where Alibaba and Amazon are genuinely different, and what that means for marketplace strategy A working model for assessing platform dependency as a board-level risk Operator-level perspective on entering China and African markets without ceding the customer relationship Sharper questions for the leadership team on payments, data and ecosystem economics

Why organisations work with Caroline Criado-Perez She built the public evidence base on the gender data gap. Invisible Women sits on the desks of regulators, engineers, and policy teams in more than thirty languages and is the default reference when the question is raised. She has won both the Royal Society Science Book Prize and the FT and McKinsey Business Book of the Year for the same work, a combination almost no other author can claim, and one that signals her rigour to both technical and commercial audiences. She translates the gender data problem into concrete operating examples: car crash test dummies, medical dosing, voice recognition, AI training data, urban infrastructure, workplace tools. Audiences leave with examples they recognise from their own organisation. She has actually changed policy. The Jane Austen banknote and the Millicent Fawcett statue are her campaigns; the credibility she brings to a corporate room is built on shifting state institutions, not commentary. Biography highlights Author, Invisible Women: Exposing Data Bias in a World Designed for Men, winner of the 2019 Royal Society Science Book Prize and the 2019 FT and McKinsey Business Book of the Year. OBE for services to equality and diversity, 2015. Author, Do It Like a Woman, profiling pioneering women globally. Founder of the campaigns that put Jane Austen on the Bank of England £10 note and Millicent Fawcett’s statue in Parliament Square. Liberty Human Rights Campaigner of the Year, 2013; Finland’s HÄN Honour, 2020; winner of the inaugural Unwin Award, 2025. Honorary doctorates from the University of Lincoln, the University of Westminster, and The Open University. Host of the Visible Women podcast with Tortoise Media; writes the Invisible Women Substack newsletter. Biography The crash test dummy used to certify most cars on the road is modelled on the body of an average male. Medical drug trials, voice recognition systems, office temperatures, and stab vests share a similar history. Invisible Women assembled this evidence into a single argument and made it impossible to ignore. Caroline Criado-Perez wrote the book that did this. It won the Royal Society Science Book Prize and the FT and McKinsey Business Book of the Year in the same year, a dual recognition that signals scientific rigour and commercial relevance at once. It has been translated into more than thirty languages and is used by policymakers, engineers, and product teams looking for a defensible account of where their data is incomplete. Her credibility with corporate audiences comes from changing institutions, not commenting on them. She ran the campaign that placed Jane Austen on the Bank of England £10 note. She campaigned for the Millicent Fawcett statue in Parliament Square, the first statue of a woman to stand there. An OBE, a Liberty Human Rights Campaigner of the Year award, and the inaugural Unwin Award are the public record of work that altered what the state chose to put in front of its citizens. Her current focus is on the operating consequences of the data gap for businesses making decisions about AI, product design, workforce policy, and customer experience. Through her Invisible Women Substack and Visible Women podcast with Tortoise Media, she continues to surface the specific cases where missing data on women becomes a material business risk. Key speaking topics The gender data gap Bias in AI training data and algorithmic systems Inclusive product and service design Workforce data and policy design Gender bias in medical and safety research Campaigning, influence, and institutional change Ideal for CHROs, chief diversity officers, and people analytics leaders auditing workforce data Heads of product, design, and data science teams in consumer-facing or safety-critical industries AI and machine learning leaders responsible for model bias and training data quality Boards and ESG committees reviewing how the organisation evidences its claims about inclusion Audience outcomes A working vocabulary for naming where the gender data gap shows up in their own products, policies, and decisions A clear view of the commercial and safety risks created by data that under-represents half the customer or workforce base Specific examples from medicine, automotive, technology, and infrastructure that translate the problem into terms their teams will recognise An understanding of how AI inherits and amplifies existing data bias, and what that means for governance A grounded sense of how institutional change actually happens, drawn from campaigns that succeeded

Why organisations work with Sandra Wachter Her Counterfactual Explanations framework – co-developed at Oxford and adopted in production by Google, IBM, Microsoft, Accenture, and Vodafone – gives organisations a legally defensible method for explaining algorithmic decisions to the individuals they affect, not just to internal audit teams. Her Conditional Demographic Disparity (CDD) bias test demonstrated that 13 of 20 widely used bias detection tools fail EU non-discrimination standards. Amazon and IBM implemented CDD in their cloud services; it was deployed in 2024 to expose systemic bias in the Dutch national education system, resulting in a ministerial apology and formal reform. She works at the precise intersection of legal standards and technical metrics – meaning she can tell risk and compliance teams not only what accountability requires but how to measure whether systems actually deliver it. As a member of the European Parliament Working Group on AI Liability and the World Bank Task Force on Access to Justice and Technology, she tracks how regulatory frameworks are being written in real time, giving organisations visibility into requirements before they become mandatory. Her research has shifted institutional practice at the NHS and MHRA, which are revising medical device licensing standards using her findings on the unintended consequences of common group fairness measures – a concrete precedent for how her work moves from publication to policy. Biography highlights Professor of Technology and Regulation, Oxford Internet Institute, University of Oxford; Humboldt Professor of Technology and Regulation, Hasso Plattner Institute Leads the Governance of Emerging Technologies (GET) Research Programme at Oxford Co-developer of Counterfactual Explanations (now deployed by Google, IBM, Microsoft, Accenture, and Vodafone) and the Conditional Demographic Disparity (CDD) bias test (implemented by Amazon and IBM; applied in the Netherlands education reform, 2024) Published in Science Robotics, Nature Electronics, and Nature Reviews Physics; cited over 20,000 times (Google Scholar) Alexander von Humboldt Foundation Research Award (2025, €3.5M); O2RB Excellence in Impact Award (2018, 2021); Computer Weekly Women in UK Tech Award (2021); Privacy Law Scholar Award (2019); CognitionX AI Ethics Award (2017, 2023) Policy roles: European Parliament Working Group on AI Liability; World Bank Task Force on Access to Justice and Technology; WEF Global Futures Council on Values, Ethics and Innovation; UNESCO; UK Police Ethics Guidance Group Previously Visiting Professor, Harvard Law School; Research Fellow, The Alan Turing Institute Media profiles in the Financial Times, Wired, New York Times, BBC,Guardian, Harvard Business Review, Reuters, Time Magazine, and MIT Technology Review Biography Sandra Wachter is Professor of Technology and Regulation at the University of Oxford’s Oxford Internet Institute and Humboldt Professor at the Hasso Plattner Institute. She leads Oxford’s Governance of Emerging Technologies Research Programme – work that sits not in the space of ethical aspiration but in the harder territory of legal standards and technical verification. The tools her research has produced are in use at scale. The Counterfactual Explanations framework she co-developed is deployed in production by Google, IBM, Microsoft, Accenture, and Vodafone. Her Conditional Demographic Disparity (CDD) bias test – built after demonstrating that 13 of 20 commonly used bias tools fail EU non-discrimination law – was adopted by Amazon and IBM in their cloud services. In 2024, CDD was used to expose systemic bias in the Dutch national education system; the Dutch Minister of Education apologised and initiated formal reform. The NHS and MHRA have revised their medical device licensing practices using her findings on the consequences of widely applied group fairness measures. Her publications appear in Science Robotics, Nature Electronics, and Nature Reviews Physics, and she has been cited over 20,000 times. Awards include the Alexander von Humboldt Foundation Research Award (2025, €3.5M), the O2RB Excellence in Impact Award (2018, 2021), the Privacy Law Scholar Award (2019), and the CognitionX AI Ethics Award (2017, 2023). She sits on the European Parliament Working Group on AI Liability, the World Bank Task Force on Access to Justice and Technology, the WEF Global Futures Council on Values, Ethics and Innovation, and the UK Police Ethics Guidance Group, and was previously Visiting Professor at Harvard Law School. For boards and risk leaders, her most immediate value is diagnostic: the gap between what organisations say their AI governance achieves and what the regulatory and technical evidence supports is larger than most assume. She has spent a decade building the instruments to measure that gap precisely. Key speaking topics AI governance and regulation Algorithmic accountability and explainability Algorithmic bias and non-discrimination law Generative AI and legal liability The EU AI Act and regulatory compliance Profiling, inferential analytics, and data protection Platform regulation and internet governance Ideal for Boards and C-suite teams making AI adoption and governance commitments Chief Data Officers and technology leadership teams designing accountability frameworks Legal, compliance, and risk leaders responsible for AI deployment decisions Public sector and regulatory audiences shaping AI policy and standards Audience outcomes A clear-eyed assessment of where current AI governance practices fall short of EU and UK legal standards – and why common assumptions about bias testing are insufficient Practical grounding in legally defensible tools for explainability and bias measurement, including frameworks already adopted by major technology companies Informed foresight into how the EU AI Act and emerging AI liability frameworks will affect deployment requirements Understanding of how generative AI creates specific new liabilities around hallucination, misinformation, and the emerging legal question of AI truthfulness The ability to distinguish between stated accountability commitments and governance that can withstand external scrutiny

Why organisations work with Ali Rebaie He reads AI adoption through anthropology and phenomenology, which exposes cultural and behavioural risks that pure technical assessments miss. He founded Rebaie Analytics Group in his early twenties and has since advised Fortune 500 clients across sectors on AI strategy, giving him pattern recognition across industries that a single-sector advisor cannot offer. Through Kiangle.ai he has built METIS, a generative AI scenario-planning platform, so his advice to boards comes from someone actively shipping the technology, not only commenting on it. He speaks to the human sciences side of AI, covering machine consciousness, decision intelligence, and the effects on children and future generations, which lets him hold a boardroom conversation that moves past tooling into governance and values. His analyst background, including a seat on the Boulder BI Brain Trust advisory board, gives him access to the vendor landscape most executives only see through sales decks. Biography highlights Founder and President, Rebaie Analytics Group, an AI and human sciences strategy and research firm with Fortune 500 clients. Founder of Kiangle.ai, Portugal-based, building METIS for generative AI scenario planning. Keynote speaker at MWC Barcelona and Hannover Messe. Advisory Board member, Boulder BI Brain Trust (BBBT). Developed an AI and Machine Learning for Engineering course hosted via UC Berkeley Global. Listed among the top 100 AI influencers globally (self-reported). Biography Enterprise AI projects fail more often on culture than on code. A model ships, a workflow changes, and the people working inside it start making decisions differently, often without anyone noticing until the results move. That is the territory Ali Rebaie works in. He runs Rebaie Analytics Group, the AI and human sciences strategy firm he founded in his early twenties, which now advises Fortune 500 clients on how to adopt AI without losing the judgement and cultural fabric that made them worth automating in the first place. His method treats AI rollout as an anthropological event, something that reshapes how a team thinks, decides, and relates, not only what it produces. The analytical background is substantive. He sits on the advisory board of the Boulder BI Brain Trust, the long-running industry analyst consortium, and developed an AI and Machine Learning for Engineering course hosted via UC Berkeley Global. That gives him a working view of the vendor landscape most executives only see through procurement cycles. The most recent work is operational. Through Kiangle.ai, his Portugal-based venture, he is building METIS, a generative AI scenario-planning platform that combines mathematical simulation with insights from human sciences to stress-test strategic decisions under uncertainty. Boards get an advisor whose views on AI governance are informed by the pressures of actually building one of these systems. Key speaking topics AI strategy and adoption Scenario planning and strategic foresight Decision intelligence Generative AI and enterprise risk Human sciences and AI Future of work and future skills AI governance and responsible technology Ideal for CIOs, CDOs, and CTOs scoping enterprise AI adoption beyond proof-of-concept. Boards and executive committees setting AI governance and risk posture. Strategy and transformation leads running scenario planning on AI-driven market shifts. Industry conferences on AI, data, and the future of technology. Audience outcomes A clearer read on how AI adoption changes behaviour and decision-making inside teams, not only workflows. A working vocabulary for AI scenario planning under genuine uncertainty. Sharper questions for vendors, framed by an analyst who has seen how the market actually sells. A considered position on AI governance that accounts for cultural and human consequences alongside technical ones.

Why organisations work with Andreas Clenow He runs the strategies he teaches. ACIES is a working asset manager, not a consulting front. What audiences hear has been tested with real capital, not on a backtest deck. His books, Following the Trend, Stocks on the Move, and Trading Evolved, are reference texts on the CMT curriculum and inside multiple quant shops. Few practitioners can claim that level of influence on the field. He explains systematic investing in plain language that family offices, boards, and fintech founders can act on, without diluting the maths. He has done the operator’s job alongside the trader’s job: hedge fund co-founder, board member, fintech investor, former Reuters Global Head of quant analytics. He understands the business of asset management, not only the modelling. Biography highlights Chief Investment Officer and partner, ACIES Asset Management AG, Zurich Former Global Head of Equity and Commodity Quantitative Research, Reuters Author of Following the Trend (Wiley, 2012; 2nd edition 2022), Stocks on the Move (2015) and Trading Evolved (2019) Author of A Most Private Bank, a novel set inside Swiss private banking MSc Economics, School of Economics, Gothenburg University Keynote speaker at QuantCon NYC, QuantCon Singapore, Bloomberg events, and CMT Association programmes Biography Trend-following used to be a black box that institutional investors paid hedge funds to operate without ever seeing inside. Following the Trend, published by Wiley in 2012, opened the box. The book showed that the diversified managed futures industry runs on a small set of repeatable rules, and it remains a working reference inside CTA shops more than a decade later. Andreas Clenow wrote it as a working practitioner, not a commentator. He is Chief Investment Officer and partner at ACIES Asset Management AG in Zurich, having previously run global equity and commodity quantitative research at Reuters and co-founded hedge funds on both onshore and offshore structures. His follow-up books, Stocks on the Move on equity momentum and Trading Evolved on building strategies in Python, are now standard reading on the Chartered Market Technician programme and inside many quant teams. His argument with audiences is consistent. Most underperformance in capital allocation comes from discretion dressed up as analysis. The remedy is not more analysts. It is a rules-based process, tested across decades of data, with explicit risk budgets and an honest account of what the strategy will and will not do. That argument lands particularly well with family offices, boards of investment committees, and fintech founders trying to build scalable trading businesses, because Clenow has lived each of those roles. He has founded and sold companies, sat on boards, raised seed capital for a hedge fund, and managed institutional money through more than one cycle. The talks reflect that range: systematic investing, the economics of running a quant fund, and what separates a professional desk from a retail operation. Key speaking topics Systematic trend-following and managed futures Equity momentum strategies Quantitative trading and model design Asset management for family offices The business of running a hedge fund Risk budgeting and capital allocation under volatility Python and the modern quant stack Ideal for Family office principals, CIOs and investment committees Asset management and hedge fund leadership teams Fintech founders building systematic trading or wealth platforms Bank and brokerage quant and risk leadership Audience outcomes A clear view of how diversified trend-following actually works as a portfolio strategy, not as marketing language A working test for whether an internal strategy is systematic or discretion in a spreadsheet A realistic picture of the economics of running a quant fund: returns, drawdowns, capacity, and infrastructure Sharper questions to ask managers, vendors and internal teams about model risk and capital deployment

All About Elin Hauge artificial intelligence should be at the forefront of every leaders’ mind; because it will fundamentally change your business, significantly impact your life, and so that you can understand the technologies your kids take for granted. Artificial intelligence is probably the most disruptive technological development in human history, and it is ubiquitous; from the face recognition on your smartphone to advanced public surveillance, from food production to medical research, from online shopping to autonomous cars. In addition, other emerging technologies such as the internet of things, blockchain, and virtual reality complement and interact with Artificial intelligence to create even more immersive, complex, and disrupting products and services. According to Elin Hauge, understanding the basics of artificial intelligence should be as compulsory for any leader in 2022 as having a computer. Elin Hauge has built bridges between business and data-driven technologies for more than 20 years, with AI as her main area of focus since 2016. Through her work with business leaders and tech entrepreneurs, she has developed an exceptional ability to connect the dots between business strategy and the application of AI. She brings new perspectives to known challenges, relentlessly demystifying jargon and buzz words, and is always three steps ahead with her perspectives on sustainability, responsibility, and disruption. She has a humoristic, down-to-earth, and pragmatic approach to what is actually possible with AI here and now, what is responsible to do in the context of both your company and the society, and what you as decision-maker need to understand to make the right decisions. She systematically brings in the human perspective; “the future of artificial intelligence is not human less, it’s human more.” In her talks, she provides tangible and well-grounded recommendations for how to reap real benefits with AI, how to comply with regulations, and how to make AI an integral and sustainable part of your business or organization. Elin Hauge holds a MEng in Biophysics and Medical technology and a MSc in management Science and Operational Research. Her strong academic background from mathematics and physics, combined with broad business experience, provides a rock-solid foundation for her perspectives on the revolutionary opportunities and complex challenges with and around artificial intelligence. She has spent the last three years working in the tech startup landscape, mentoring hundreds of entrepreneurs across Europe on business strategy, commercialization and go-to-market.

Why organisations work with Les Binet The 60:40 brand-to-activation framework he co-developed with Peter Field is the most cited effectiveness benchmark in UK marketing strategy. Organisations use it to build a defensible, evidence-based case for long-term brand investment to boards focused on quarterly ROI. His analysis of the IPA Effectiveness Databank covers more than 1,000 case studies across 700 brands, 83 sectors and over three decades of commercial data. No comparable longitudinal evidence base for marketing investment decisions exists in published form. The Share of Search metric he developed gives organisations a free, predictive tool for tracking brand health and anticipating market share movements, validated across automotive, energy and handset categories using publicly available Google Trends data. Research he presented at the 2025 IPA Effectiveness Conference showed that marketing budget is eight times more important than ROI in driving effectiveness. Most CMOs surveyed believed the opposite – a gap his work directly addresses. His grounding in Physics, Artificial Intelligence research and LSE econometrics makes him one of the few voices in effectiveness who can construct, interrogate and critique the statistical models organisations use to evaluate their own campaigns. Biography highlights Co-author of The Long and the Short of It (IPA, 2013) and four further IPA effectiveness reports; has contributed to more IPA Effectiveness Awards papers than any other individual (per the Advertising Association) Former Group Head of Effectiveness at adam&eveDDB; joined BMP account planning in 1987 and remained across all iterations of the agency for more than three decades Recipient of the IPA President’s Medal (2014), the highest honour the UK advertising industry can award Elected IPA Honorary Fellow (2004); Convener of Judges, IPA Effectiveness Awards (2005) Board Advisor, Journal of Advertising Research; named in Campaign Magazine’s “40 over 40” (2023) MA Physics, Oxford; MPhil Artificial Intelligence, Edinburgh; postgraduate Economics (Birkbeck) and Econometrics (LSE) Biography The Long and the Short of It, published by the IPA in 2013, is one of the most-cited effectiveness documents in marketing. Its co-author, Les Binet, spent three decades at adam&eveDDB building the evidence that most organisations structure their marketing investment around the wrong metrics. The research drew on 996 advertising effectiveness case studies across 700 brands, 83 sectors and more than 30 years of IPA Databank data. Its central finding of the “60:40 heuristic” recommended that most consumer brands allocate roughly 60% of marketing budget to brand building and 40% to short-term activation. The report has since been cited in over 70 academic publications and referenced across multiple languages. Binet’s subsequent work has continued to extend the evidence base. The Share of Search metric he developed gives organisations a free, predictive tool for tracking brand health using Google Trends data, validated across automotive, energy and handset categories. At the 2025 IPA Effectiveness Conference, he presented research with Medialab showing that budget is eight times more important than ROI in driving marketing effectiveness. Most CMOs surveyed believed the opposite. He read Physics at Oxford and completed an MPhil in Artificial Intelligence at Edinburgh, later adding postgraduate study in Economics at Birkbeck and Econometrics at the LSE. Elected an IPA Honorary Fellow in 2004, he received the IPA President’s Medal in 2014. He serves as a Board Advisor to the Journal of Advertising Research and consults independently through Binet Consulting. Key speaking topics Marketing effectiveness measurement Brand building versus short-term activation The 60:40 investment framework Share of Search and brand demand indicators Econometrics and advertising evaluation Media effectiveness in digital environments Evidence-based marketing investment strategy Ideal for CMOs and senior marketing leaders making significant media and brand investment decisions CFOs and finance functions reviewing marketing accountability and budget allocation Boards and executive teams evaluating the commercial return on advertising investment Strategy, planning and insight functions in organisations with major advertising spend Audience outcomes A clear, evidence-grounded framework for distinguishing short-term ROI from long-term profit growth, and why the difference matters to boards Practical understanding of the 60:40 brand-to-activation heuristic and how to adapt it by sector, brand maturity and business context A working introduction to Share of Search as a predictive brand health indicator, applicable without specialist tools or budget A stronger internal case for protecting brand investment in organisations under pressure to demonstrate immediate measurable returns Familiarity with the specific effectiveness patterns – reach, share of voice, emotional advertising – that the IPA data consistently identifies as drivers of commercial results

Why organisations work with Neil Martin He built the probabilistic strategy modelling systems now used by more than half the current Formula One grid – not a commentator on F1 decision-making, but the person who changed how the sport models decisions under uncertainty. Two specific, named race outcomes are directly attributed to his calls: Red Bull Racing’s first Formula One win at the 2009 Chinese Grand Prix, and Räikkönen’s win at the 2005 Monaco Grand Prix – both the product of real-time probabilistic reasoning under extreme competitive pressure. He translates a specific, working methodology – Monte Carlo simulation and game theory applied to real-time competitive decisions – into frameworks organisations can use when multiple futures must be weighed against each other with no time to wait for certainty. His experience spans the full decision chain: building the analytical models, leading the strategy team live in the race, and managing the operational culture of teams working against non-negotiable deadlines with global coordination demands. As Co-Founder of PACETEQ GmbH, he continues to build and deploy competitive analytics tools across motorsport, which means his perspective is operational and current rather than retrospective. Biography highlights BSc in Mathematics with Computer Science and MSc in Operational Research, University of Southampton; MSc project on optimal pit-stop and refuelling strategies secured a full-time role at McLaren Racing Pioneered the application of Game Theory and Monte Carlo simulation to F1 race strategy at McLaren from 1998, replacing deterministic planning with stochastic models that could account for uncertain events in real time Team Leader of Operational Research at McLaren Racing; Chief Strategist at Red Bull Racing; Head of Operations Research and Strategy at Scuderia Ferrari (2011-2015) Strategic calls directly credited with Red Bull Racing’s first-ever Formula One win at the 2009 Chinese Grand Prix and Räikkönen’s victory at the 2005 Monaco Grand Prix Co-Founder of PACETEQ GmbH, an AI-powered motorsport analytics business; software originating from his work in active use across more than half the Formula One grid Covered in the Financial Times; featured speaker at the Gartner Data and Analytics Summit Biography Neil Martin joined McLaren Racing in 1996 to solve a specific problem: race strategy was being built on deterministic models that assumed a single most-likely future. He replaced those models with stochastic ones, applying Game Theory and Monte Carlo simulation to uncertain events. Traffic patterns, overtake probabilities, safety car timing – these could now be modelled, and strategy built around a range of probable outcomes rather than one. That shift produced verifiable results at the highest level. At the 2005 Monaco Grand Prix, Martin sent an email from McLaren’s Woking base instructing Räikkönen to stay out under a safety car; the call won the race. At the 2009 Chinese Grand Prix, as Red Bull Racing’s Chief Strategist, he kept both cars out in wet conditions when almost every competitor pitted. It was the team’s first-ever Formula One win – a 1-2 finish built on asymmetric risk reasoning under pressure. Martin joined Scuderia Ferrari in 2011 as Head of the newly created Operations Research department, brought in alongside Pat Fry to rebuild the team’s race operations. He left in 2015. Since then, he has founded Random Logic and co-founded PACETEQ GmbH, an AI-powered analytics business whose tools now run on more than half the current Formula One grid. For senior leaders, the argument is direct. Performance under pressure is not determined by the quantity of data available. It is determined by the quality of the frameworks used to act on it. Martin’s career is a proof of concept for what that discipline looks like when competitive stakes are at their highest. Key speaking topics Decision-making under uncertainty Probabilistic risk modelling Data-driven competitive strategy High-performance operations Risk management in live environments Marginal gains and continuous improvement Analytics-led performance optimisation Ideal for C-suite and senior strategy leaders making high-stakes decisions with incomplete data and competitive time pressure Risk, analytics, and data science functions seeking to operationalise probabilistic thinking across the organisation Boards and executive teams benchmarking their decision culture against elite performance environments Corporate conferences in financial services, technology, and professional services where data-driven decision-making is a strategic priority Audience outcomes A named conceptual shift: from deterministic “most likely scenario” planning to probabilistic mapping of multiple futures and their associated likelihoods Clarity on the conditions under which data produces better decisions, and the organisational habits that close the gap between having information and acting on it with confidence Specific, race-derived examples of asymmetric risk reasoning applicable to resource allocation, market entry, and competitive response decisions Practical understanding of how high-performance teams coordinate under non-negotiable deadlines without sacrificing analytical discipline A benchmark for what genuinely data-driven operational culture looks like when competitive stakes leave no margin for deterministic thinking

Why organisations work with Karun Chandhok He has lived inside two of the most exposed environments in elite sport: the cockpit of a backmarker F1 team trying to build a car around him, and a Sky Sports broadcast booth analysing the same paddock in real time. He sits on the Motorsport UK Board and the FIA Drivers’ Commission, so the governance, safety and DEI conversations he brings into the room are ones he is actively shaping, not commenting on from the outside. He translates how F1 teams turn millions of data points per race into decisive calls that engineers, strategists and a driver all act on within seconds, with examples a non-motorsport audience can follow. He is one of only two Indians ever to race in Formula One, which gives weight to his work on talent pipelines, representation and what it takes to break into a closed competitive system. He is a working broadcaster for a global audience, so the keynote is paced and structured for the room rather than delivered as a career retrospective. Biography highlights 11 Formula One Grand Prix starts for Hispania Racing in 2010 and Team Lotus in 2011. Sky Sports F1 analyst, co-commentator and pit-lane reporter, full-time since 2019. Board Director, Motorsport UK, and member of its Equality, Diversity and Inclusion Committee. Founding member of the FIA Drivers’ Commission since 2013, with further roles on the FIA Single Seater Commission and Driver Grading Committee. Williams Heritage driver since 2016, demonstrating the team’s championship-winning cars. Author of “Drive to Victory: Incredible True Stories from the Fastest Sport in the World”, Hachette Children’s, 2025. Biography A modern Formula One team is roughly a thousand engineers, strategists and operations staff who have to redesign their product every two weeks, inside a moving regulatory frame, while a driver they have never met executes the result on television. Karun Chandhok has been the driver in that picture, the analyst describing it for Sky Sports F1, and a director on the boards that write the rules around it. He raced 11 Grands Prix for Hispania Racing and Team Lotus, becoming the second Indian to compete in the championship. From there he moved into the FIA World Endurance Championship and five starts at the 24 Hours of Le Mans, then drove for Mahindra Racing in the inaugural Formula E season. The breadth matters: very few people have raced across the three categories actively reshaping motorsport’s relationship with technology, sustainability and global audiences. Since 2019 he has been part of the core Sky Sports F1 line-up as analyst, co-commentator and pit-lane reporter. The role is unusual because it sits between the engineers and the public; he has to read live telemetry, strategy calls and team radio quickly enough to explain them on air, and accurately enough that the paddock will keep talking to him next weekend. His governance work gives the keynote its third dimension. He has served on the FIA Drivers’ Commission since 2013 and joined the Motorsport UK board in 2021, where he sits on the Equality, Diversity and Inclusion Committee. Those seats are why his material on talent pipelines, safety reform and competitive integrity carries authority that most sports speakers cannot match. Key speaking topics Decision-making in high-pressure performance environments Leadership and team coordination in elite motorsport Data, technology and human judgement in Formula One Safety, governance and regulatory change Diversity, inclusion and talent pipelines in closed competitive systems Continuous transformation under external pressure Global sport as a commercial and operational system Ideal for Executive teams and boards working through sustained operational or regulatory change. CHROs, DEI leads and talent functions building pipelines into historically closed industries. Engineering, technology and data leadership audiences interested in how F1 turns data into action. Sales conferences and client events where a credible, broadcast-quality headline speaker is needed. Audience outcomes A clearer view of how elite teams sustain judgement and coordination when conditions keep shifting. A working sense of how F1 organisations turn data and technology into faster human decisions. Specific examples of how regulation, safety and competitive performance trade against each other inside a sport. A more honest picture of what genuine inclusion looks like in a sector that historically locked talent out.

Why organisations work with Ting Li A sitting professor at a top European business school whose work appears in Management Science, MIS Quarterly, and Information Systems Research, which means the frameworks she brings to a leadership room have already been tested against the strongest academic standards. Director of Digital Business Practice at the Erasmus Centre for Data Analytics, where research is run alongside large corporates and the Dutch government, so the recommendations are grounded in operating reality rather than slideware. One of the few academic voices working across digital pricing, online advertising, social and mobile analytics, and immersive technology, which lets her connect AI investment decisions to concrete commercial levers. Named to the Poets and Quants Top 40 Under 40 ranking of business school professors, an external signal that the teaching translates for senior executive audiences, not only doctoral students. Bilingual in English and Mandarin, with research and teaching ties across Europe, North America, and China, useful for boards working through digital strategy with operations on both sides of the rules-based order. Biography highlights Professor of Digital Business and head of the Information Systems group at Rotterdam School of Management, Erasmus University. Founding member and Academic Director of Digital Business Practice at the Erasmus Centre for Data Analytics, and head of the Immersive Tech and AI Lab. Visiting Professor positions at Wharton, MIT, Tsinghua, Temple, Arizona State, and City University of Hong Kong. Published in Management Science, MIS Quarterly, Information Systems Research, Nature Communications, Production and Operations Management, and Harvard Business Review. Named by Poets and Quants as one of the Top 40 Best Business School Professors Under 40 Worldwide. Research funded by the Dutch National Science Foundation and by industry partners including VIVAT, AllSafe, and the Dutch Police. Biography Most digital strategy advice on AI and platforms is opinion dressed as evidence. Ting Li works the other way around. Her research at Rotterdam School of Management uses econometrics, field experiments, and machine learning to test what digital technologies actually do to consumer behaviour, pricing, and competitive position, then translates the result for the people making the investment call. At RSM she holds the chair in Digital Business and runs the Information Systems group. She is also Academic Director of Digital Business Practice at the Erasmus Centre for Data Analytics, where she works with corporates and Dutch public bodies on live problems in digital advertising, platform design, and AI deployment. The Immersive Tech and AI Lab she leads gives her a working view of where AR, VR, and generative tools are starting to change customer experience rather than only marketing decks. Her academic record sits at the top of the field. Papers in Management Science, MIS Quarterly, Information Systems Research, and Nature Communications, alongside articles in Harvard Business Review, mean a board hearing her on digital pricing or online advertising is hearing the underlying evidence, not a secondhand reading of it. Visiting positions at Wharton, MIT, and Tsinghua give her a working network across the leading research centres on the digital economy. The Poets and Quants Top 40 Under 40 ranking captured what executive education clients already report: she is a researcher who can hold a senior room. That is what makes her useful when the question on the table is whether a specific AI or platform bet will move the business. Key speaking topics Digital strategy and the digital economy AI and decision-making in the enterprise Digital platforms and online advertising Pricing and revenue management Social and mobile analytics Digital privacy and algorithmic accountability Generative AI, AR, VR, and immersive technology Ideal for Boards and executive committees setting digital and AI investment priorities. Chief Digital, Data, and AI Officers moving from pilots to operating deployment. Chief Marketing Officers and revenue leaders working on pricing, platform, and advertising decisions. Strategy and innovation leads in retail, financial services, and consumer-facing platforms. Audience outcomes A clearer read on which AI and digital investments have evidence behind them and which do not. A sharper view of how digital pricing, advertising, and platform mechanics affect customer behaviour at scale. Practical reference points for governing AI use in commercial decisions. A working sense of how immersive and generative technologies are starting to reshape customer experience.

Why organisations work with Hannah Fry Hello World (2018) advances a specific governance argument: that AI fails not because the technology is wrong, but because accountability was poorly designed. That gives boards a working framework for AI governance, not just a sharper awareness of risk. Her UCL research was applied directly – she worked with governments, police forces, health analysts, and supermarkets, translating mathematical models of human behaviour into operational decisions. That applied track record is what separates her algorithmic analysis from academic commentary. The accuracy-versus-fairness trade-off in predictive systems is a mathematical problem before it is an ethical one. She can explain it precisely enough for legal, compliance, and strategy leaders to translate it into governance decisions – not just for data teams. She holds Cambridge’s inaugural Professorship in the Public Understanding of Mathematics – a chair that formalises the argument that making quantitative thinking accessible to non-specialists is itself a research discipline. As President of the Institute of Mathematics and its Applications and a Fellow of the Royal Academy of Engineering, her institutional credibility extends well beyond media profile. Biography highlights First Professor of the Public Understanding of Mathematics at the University of Cambridge (from January 2025), joining the Department of Applied Mathematics and Theoretical Physics Previously Professor in the Mathematics of Cities at UCL Centre for Advanced Spatial Analysis; research applied to urban crime, transport, health analysis, and terrorism, with direct advisory roles across government and industry Fellow of the Royal Academy of Engineering (elected 2022) and Fellow of Queens’ College, Cambridge President of the Institute of Mathematics and its Applications Author of Hello World: How to Be Human in the Age of the Machine (2018) – winner of the 2020 Asimov Prize; shortlisted for the Baillie Gifford Prize for Non-Fiction and the Royal Society Science Book Prize Christopher Zeeman Medal (2018) and Royal Society David Attenborough Award (2024) for contributions to science communication Delivered the 2019 Royal Institution Christmas Lectures – only the fourth mathematician to do so since Michael Faraday established the series in 1825 BBC presenter across AI Confidential with Hannah Fry (2026), The Secret Genius of Modern Life (BBC Two), and Bloomberg Originals’ The Future with Hannah Fry (2023); regular contributor to The New Yorker; TED Talk «The Mathematics of Love» has exceeded five million views Biography Hannah Fry spent over a decade at UCL studying the mathematics of cities – how people move through urban space, where crime clusters, how disease propagates through populations. Her research was applied: she worked directly with governments, police forces, health analysts, and supermarkets. The question she returned to consistently was what happens when those decisions are automated, and whether the automation can be trusted. Her book Hello World (2018) answered that question with precision. Algorithms are not objective – they encode the biases embedded in the data they were trained on, often before anyone noticed. The response, she argued, is not to distrust AI but to design governance that keeps humans genuinely in the loop. She called this the «cyborg future» – a practical framework for accountability, not a metaphor. The book won the 2020 Asimov Prize and was shortlisted for the Baillie Gifford Prize for Non-Fiction and the Royal Society Science Book Prize. In January 2025, she became Cambridge’s first Professor of the Public Understanding of Mathematics, following in the footsteps of David Spiegelhalter and Stephen Hawking as a public interpreter of the discipline. She also serves as President of the Institute of Mathematics and its Applications and holds a Fellowship of the Royal Academy of Engineering. Her media work extends the argument across audiences that no academic publication reaches. BBC Two’s AI Confidential with Hannah Fry (2026) investigated how AI is reshaping human relationships and institutional decisions. The Secret Genius of Modern Life ran over two BBC Two series. She delivered the 2019 Royal Institution Christmas Lectures – only the fourth mathematician in the lectures’ 200-year history to do so – and writes regularly for The New Yorker. For leadership teams moving from AI adoption to AI accountability, that combination of mathematical rigour and public clarity is not a communications asset. It is the substance of what she brings. Key speaking topics AI and algorithmic decision-making Data bias and algorithmic fairness Human-machine governance Risk and probability in complex systems The mathematics of human behaviour Urban data and city systems Science communication and mathematical literacy Ideal for Executive and board-level audiences setting AI governance and risk policy Chief Data Officers, Chief Technology Officers, and senior technology strategy teams Leadership conferences addressing responsible AI adoption in regulated industries – healthcare, financial services, criminal justice Public sector audiences navigating the use of predictive and automated systems Audience outcomes A clearer understanding of how algorithmic bias is produced and why it is mathematically difficult to eliminate without deliberate trade-offs A practical mental model – drawn from the Hello World framework – for when to trust algorithmic output and when to retain human judgment Confidence to engage substantively with AI governance questions without requiring deep technical knowledge Greater ability to interrogate the assumptions behind data-driven outputs, rather than treating them as authoritative A vocabulary for discussing AI risk that is precise and usable in board-level and policy conversations