Navigating Complex Systems

Look, this is going to shock some of you. But someone’s got to say it. Your ‘cloud’ isn’t floating somewhere out there. It’s anchored in giant rooms you may never see. Ever wondered where your photos, messages, and video calls live? Not in the sky, that’s for sure! They live in data centres. Huge, secure buildings that power everything online. Every click, every stream, every late-night email? It all runs through these digital ‘backbones’. → Massive servers work day and night, always on → Cooling systems stop everything from overheating → Backup power keeps things on, even if the lights go out → Security guards and lots of cameras protect your data 24/7 Hyperscalers like Google, AWS, and Microsoft build these rooms on a scale most of us can’t imagine. (Think football stadiums full of blinking lights!) Why does this matter? → Data centres make sure your apps and websites are always on → They keep your information safe and ready, for whenever you need it → They help businesses grow, learn, and connect across the world But there’s more. As our digital world grows, so does the need for energy. That’s why the industry is changing fast: → Smarter cooling to use less power → Greener energy to lower carbon footprints → New tech to make storage faster and safer I’ve spent years inside these whirring rooms. Planning, building, leading teams to deliver for some of the world’s biggest names. (Trust me, it never gets old seeing a new data hall go live!) Next time you share a photo or join a video call, remember … your cloud is anchored in a real place, with real people working behind the scenes. What surprises you most about data centres? Anything you wish you could see behind those doors?

A big question in software is what happens to the systems of record in a world of AI Agents. Do they go away? Do they just become databases? Or do they become more powerful? I’d argue that they’re just as powerful as ever, if not more powerful, in a world of 100X more interactions with software. The purpose of your system of record (whether it’s ERP, CRM, ITSM, or a document management system) is to hold the data and manage the workflows around the most important areas of your business: your customer commitments, leads, revenue figures, inventory, IP, product research, supply chain, and more. Importantly, you want the data and workflows in these systems operate in deterministic ways. When you ask a question like “what is my revenue,” you need the precise answer. When you move a lead from one stage to another, you can’t afford for it to get dropped. When you update your inventory, you can’t have it change inadvertently. Getting the data, permissions, access controls, business logic, and workflows right, every single time, is critical. On the other hand, AI Agents operate in a world of non-deterministic actions. What makes them so powerful is they can adapt to entirely new instructions on the fly, use judgment to perform actions, and operate on troves of unstructured information and decisions. When you ask an AI Agent to research and summarize a set of documents, it will produce a slightly different answer every single time - and in most use-cases for AI Agents, this is a feature, not a bug. Just as you wouldn’t ask the world’s smartest human to memorize every piece of inventory you have, or all of the permissions of every information that employees should have access (with their specific access controls) to, you similarly won’t ask AI Agents to do that in the future. This is where the separation of duties comes into play. AI Agents will be doing non-deterministic actions (like generating a sales plan, responding to a customer, or writing code), and deterministic systems will be for remembering those actions and incorporating them across a variety of workflows. In fact, in a world of AI Agents running around doing autonomous tasks 24/7, in parallel, and at unlimited scale, the role that these systems of record play will likely be even more important. Getting this relationship down is going to be key to the future of the enterprise IT stack.

🔎 How To Redesign Complex Navigation: How We Restructured Intercom’s IA (https://lnkd.in/ezbHUYyU), a practical case study on how the Intercom team fixed the maze of features, settings, workflows and navigation labels. Neatly put together by Pranava Tandra. 🚫 Customers can’t use features they can’t discover. ✅ Simplifying is about bringing order to complexity. ✅ First, map out the flow of customers and their needs. ✅ Study how people navigate and where they get stuck. ✅ Spot recurring friction points that resonate across tasks. 🚫 Don’t group features based on how they are built. ✅ Group features based on how users think and work. ✅ Bring similar things together (e.g. Help, Knowledge). ✅ Establish dedicated hubs for key parts of the product. ✅ Relocate low-priority features to workflows/settings. 🤔 People don’t use products in predictable ways. 🤔 Users often struggle with cryptic icons and labels. ✅ Show labels in a collapsible nav drawer, not on hover. ✅ Use content testing to track if users understand icons. ✅ Allow users to pin/unpin items in their navigation drawer. One of the helpful ways to prioritize sections in navigation is by layering customer journeys on top of each other to identify most frequent areas of use. The busy “hubs” of user interactions typically require faster and easier access across the product. Instead of using AI or designer’s mental model to reorganize navigation, invite users and run a card sorting session with them. People are usually not very good at naming things, but very good at grouping and organizing them. And once you have a new navigation, test and refine it with tree testing. As Pranava writes, real people don’t use products in perfectly predictable ways. They come in with an infinite variety of needs, assumptions, and goals. Our job is to address friction points for their realities — by reducing confusion and maximizing clarity. Good IA work and UX research can do just that. [Useful resources in the comments ↓] #ux #IA

Procurement’s biggest negotiation power is NOT during Contract Negotiation phase. (It is BEFORE vendors are invited for tender) You miss this window, your leverage bleeds out daily. Negotiation | 16 SEP 2025 - Procurement's ability to negotiate, shape vendor terms, price and deliver fit-for-purpose contracts "Decays Like an Hourglass" once sourcing process begins. Here’s why timing is everything: #1. Peak Leverage (Supplier Registration & PQQ) →Vendors compete blindly for a spot. → Push for acceptance of non-negotiable terms early. → Include standard T&Cs with key terms. #2. Leverage Leak (RFP/Bid Clarification & Submission) →Vendors now see competition. →Use competitive tension; let vendors know no. of bids. →Clarify specs but do not negotiate scope. #3. Critical Decline (Best and Final Offer) →Shortlisted vendors smell victory; alternative shrink. →Keep ≥ 3 vendors until BAFO; Never reveal rankings. →Use scoring gaps to extract concessions. #4. Near-Zero Leverage (Contract Award) →Winner knows you’re committed. →Switching costs soar; too late for heavy lifts. → Focus on SLA fine-tuning not pricing or terms. Use prequalification to: ✅Force adherence to standard Ts&Cs ✅Eliminate non-compliant bidders early ✅Create FOMO in Vendors (Will we make the cut?) Negotiation is a race against your OWN process. The Early Bird Catches the Worm Front-load pressure or backpedal through concessions." Always include your non-negotiables into vendor registration gateways. What procurement stage have you seen early leverage make or break a deal? #Procurement #NegotiationTips #RFPTips #StrategicSourcing

With disruption accelerating across industries, many believe that greater specialization will be key to professional success—“learn X to get Y.” But is that enough? While deep expertise is valuable, breadth and adaptability are just as critical. In uncertain environments, companies need talent who can connect the dots, synthesize new information, and pivot quickly—not just at the leadership level, but across the entire organization. These reflections brought me back to David Epstein’s Range, which I recently revisited and thoroughly enjoyed. His book makes a compelling case for how diverse experiences and cross-disciplinary thinking help individuals navigate uncertainty and drive innovation in a variety of domains - from sports and music to science and beyond. This is something we see firsthand at IESE Business School. The most effective professionals aren’t just specialists—they are strategic thinkers with a broad perspective. A general management approach equips them to break silos, adapt across industries, and make high-impact decisions. That’s why we emphasize a holistic, general management perspective that encourages business leaders to think beyond functional expertise and consider the broader impact of their decisions. As industries transform, the companies that thrive are those with teams who see the bigger picture, embrace diverse experiences, and navigate complexity with confidence.

WHAT IS WISE LEADERSHIP IN COMPLEXITY #Complexity arises from a world marked by interdependence, rapid change, and ambiguity. Often, complexity is discussed through agility—adapting means to meet external change. However, complexity is not just about responding to external shifts but also about integrating diverse internal perspectives. It requires navigating both ends (goals) and means (external conditions). The left axis of the matrix reflects external complexity—representing a structural sociology, focused on control and predictability. Methodologies like Complex Adaptive Systems (CAS), Lean, and Cybernetics address these aspects, enabling resilience and agility. The right axis, reflects an interpretative sociology, which emphasises pluralism and subjective experience, focussing on the internal complexity of diverse preferences and worldviews. This draws on Arrow’s impossibility theorem, which highlights the challenge of achieving consensus among differing perspectives. The intersection of these axes forms a dialectical space, where leaders develop their understanding of both ontological (reality) and epistemological (truth) complexities, overcoming absences and contradictions through good action (ethics). Tactical Control (Machine) Focuses on control, predictability, and rigid structures. Organizations operate like machines, aiming for efficiency with little room for diverse perspectives. Leadership emphasizes top-down direction. Adaptive Resilience (Organism) These organizations adapt to external complexity but retain unitary internal goals. They emphasize resilience, often in competitive environments, where change is managed but diversity of thought remains limited. Dialogical Integration (Political Community) These organizations foster collaboration and shared governance. They integrate diverse perspectives, striving for fairness and social justice while engaging all voices in decision-making. Dialectical Excellence (Professional Practice) Organizations here balance external resilience and internal pluralism, aiming for flourishing. Leadership cultivates an environment of freedom, care, and character development, leading to flourishing as a byproduct of reflective and transformative practice. Dialectics implies the sublation of the tension between outer and inner complexities. How individuals see the world influences their response to external challenges. This interplay requires a continual examination of values, ethics, and corporate responsibility. By integrating contradictions, leaders drive organizational growth and social justice, fostering #transformation. Complexity #leadership is about shaping organizational #wisdom for societal #flourishing. Leaders must work on cultures, structures, and individual agency, guiding their organizations to continually experiment with “good organizing.” In the end, wise leadership is about becoming—developing organisational character, wisdom, and practices that lead to collective flourishing.

🌍 What if the very systems driving our progress are also accelerating our greatest challenges? I recently read an article titled “The System Dynamics Approach for a Global Evolutionary Analysis of Sustainable Development” by Feder, Callegari, and Collste, which uses the Earth4All model to explore this question. The study offers a sobering but vital perspective on how environmental, social, and economic systems are deeply interconnected—and how this interplay shapes our future. Here are the main findings: 📉 Unsustainable Development Erodes Resilience The study shows that our current development trajectory creates “macro-selection pressures” that harm global resilience. Environmental challenges like climate change and resource depletion degrade economies, while social issues like inequality and declining well-being weaken societies’ ability to adapt and innovate. 🌍 Interconnected Forces Amplify Risks These challenges are not isolated—they interact in feedback loops that compound their effects. For instance, environmental degradation increases inequality by raising the cost of resources, while inequality slows the social reforms needed to combat climate change. Together, they create cycles that destabilize long-term systems. 🔄 Delaying Action Increases the Costs The Earth4All model vividly illustrates how delays in tackling these issues lead to cascading crises. By the time the full effects are visible, reversing the damage becomes far more difficult and expensive. Here are some of my own reflections on this study: 💡 Systemic Interplay This research reinforces something I’ve long believed: we can’t address environmental, social, or economic challenges in isolation. They are interconnected. For example, policies focused solely on short-term economic gains often overlook their environmental costs, which eventually undermine the economy itself. Solutions must integrate these systems to work sustainably. 📊 The Role of Models Like Earth4All I’m a strong advocate for the Earth4All model because it provides a clear and integrated view of these complexities. It connects natural, social, and economic systems into one framework, helping us see the long-term impact of today’s decisions. For policymakers and leaders, it’s an invaluable tool to guide strategy. 🎓 Learning and Awareness Finally, this study reminded me of the importance of understanding complexity. Tools like Earth4All empower us to move beyond short-term fixes and focus on systemic solutions. Awareness is the first step toward meaningful action. To learn more about this model, I would highly recommend visiting their website: (https://earth4all.life/) If you’re interested, you can read the full article here: https://lnkd.in/e5tRft63 🌐 How do you see the interplay of these systems shaping the challenges in your field? #Sustainability #SystemsThinking #ClimateAction #SocialEquity #FutureOfEconomics 🌟

One thing I’ve learned building AI powered automation for clients: Deterministic and agentic automation do not ask for the same kind of patience. On paper, they both look like “a workflow”. In real life, they feel very different. Deterministic automation is the rules-based kind. If X happens, do Y. If a field is blank, stop. If a deal is in Stage 3, notify this person. You reach for this when: • The rules are clear • The data is structured • The same input should always produce the same output You spend most of your time defining the logic and testing a few scenarios. Once it works, it’s usually stable until something upstream changes. Agentic or AI powered automation is different. You’re not just routing data. You’re asking for judgment. Things like: • Summarize this email • Decide which team should handle this request • Draft a response that fits these guidelines • Classify this lead based on what they wrote Small input changes can shift the output. So the work changes too. You’re not just connecting steps. You’re shaping behavior. That means: • More rounds of testing with real examples • More time tightening prompts and instructions • More clarity on what “good” looks like and how to make it repeatable You do get to a stable version. It just takes more iteration to earn that stability. Neither type is “better”. They just shine in different places. • Clear rules, strict outcomes, predictable paths → deterministic • Messy inputs, natural language, prioritization, judgment → agentic The mistake is expecting agentic automation to behave like deterministic automation on day one. It can do more, but it also asks more from you: More patience. More examples. More care with inputs. Once you accept that, you start building with clearer expectations and a lot less frustration.

Nature doesn't operate in silos, so why do our solutions? Earlier this year, the IPBES released their Nexus Report looking at the interconnectedness of environmental, social, and economic crises. For decades, we've tried to simplify complex challenges by separating them into neat categories - biodiversity separate from climate, water management distinct from food systems, economic models divorced from social outcomes. We created separate departments, separate policies, separate accounting methods, and separate KPIs. But this artificial separation hasn't made things simpler - it's made them more complex and less effective. 👉 A close look at this wheel reveals how restoration of coastal systems simultaneously addresses biodiversity, carbon sequestration, and disaster risk reduction. Notice how circular bioeconomy solutions touch on consumption, resource use, and waste management simultaneously. See how water governance connects to social equity, infrastructure planning, and ecosystem health. These connections aren't exceptions - they're the rule. When our accounting methods, reporting frameworks, and governance accountabilities fail to capture these interconnections, they're not just incomplete - they're inaccurate. Some might even say dishonest… especially when we know we are externalising the cost of doing business. The good news? We're seeing a shift. Integrated reporting frameworks, systems thinking approaches, and holistic governance models are gaining traction. Organisations that understand these connections are finding more innovative and effective solutions. 💭 The challenge ahead isn't just technical - it's conceptual. Can we unlearn our tendency to compartmentalise and embrace the beautiful complexity of interconnected systems? Read the report summary here: https://lnkd.in/e8vY72E2

This morning's breakfast discussion with Business Insider reinforced something I see daily: #resilience isn't just a buzzword, it's become the defining capability that separates thriving organizations from those merely surviving. The conversation centered on how companies are leveraging #sustainability insights to build organizational resilience through comprehensive risk evaluation and translating climate considerations into sustainable competitive advantages. What struck me most was the shared recognition that these aren't separate initiatives, but interconnected strategies for long-term business continuity. Exercises like #doublemateriality and climate risk and opportunity assessments (#CCRO) have evolved far beyond compliance tools. They've become essential frameworks for understanding how environmental and social factors intersect with core business operations, supply chains, and strategic planning. When done rigorously, they reveal the connections between sustainability performance and business resilience that might otherwise remain invisible. Last week, we published our updated Sustainability Materiality Report, which reflects years of learning about how to make these assessments truly decision-useful rather than just comprehensive. The process taught us that the most valuable insights come not from identifying every possible risk, but from understanding which factors could fundamentally alter our business trajectory. As #ClimateWeek unfolds, these conversations feel particularly timely. Building deep understanding of both #mitigation and #adaptation strategies isn't just about environmental stewardship, it's about developing the organizational awareness needed to navigate an increasingly complex operating environment. Those around today's table represented diverse stakeholder groups, yet we all shared similar challenges: how to build systems that can anticipate change rather than simply react to it. The answer consistently pointed back to the quality of our risk assessment processes and our willingness to integrate those insights into strategic decision-making. #ClimateAction requires this level of institutional intelligence—the capacity to see connections, anticipate disruptions, and adapt accordingly. Companies that master this integration will find themselves better positioned not just for environmental challenges, but for the full spectrum of changes reshaping business today.