https://engineering.hinshelwood.com/concepts/model/ Recent content in Model on Engineering as a Leadership System Hugo en Tue, 16 Jun 2026 17:40:35 +0000 https://engineering.hinshelwood.com/articles/live-site-culture-site-reliability-engineering/ Wed, 17 Jun 2020 13:23:00 +0000 https://engineering.hinshelwood.com/articles/live-site-culture-site-reliability-engineering/ To stay competitive in a fast-changing market, teams must adopt DevOps and continuous delivery, shifting from infrequent releases to deploying updates daily. This requires faster feedback, shared responsibility for quality and operations, and new ways of working, as shown by Microsoft’s Azure DevOps team. Development managers should consider evolving their team structures and practices to support rapid, customer-focused delivery. https://engineering.hinshelwood.com/articles/evidence-based-management-gathering-the-metrics/ Wed, 30 Dec 2020 14:02:07 +0000 https://engineering.hinshelwood.com/articles/evidence-based-management-gathering-the-metrics/ Evidence-based Management helps software organizations focus on delivering real value by tracking metrics in three areas: current value, time to market, and ability to innovate. Traditional measures like on-time and on-budget delivery miss customer value, so organizations should gather and regularly review these agile-focused metrics to guide improvement. Start collecting baseline data now and reassess quarterly to track progress and demonstrate the impact of agile investments. https://engineering.hinshelwood.com/videos/mastering-outcomes-how-evidence-based-management-transforms-your-project-success/ Thu, 12 Sep 2024 13:46:15 +0000 https://engineering.hinshelwood.com/videos/mastering-outcomes-how-evidence-based-management-transforms-your-project-success/ Defining clear, measurable outcomes and using both leading and lagging metrics are essential for project success. Evidence-based management helps teams make informed decisions by consistently collecting and analyzing data, then iterating based on insights. Development managers should focus on setting SMART goals, tracking the right metrics, and using data to guide continuous improvement. https://engineering.hinshelwood.com/videos/mastering-evidence-based-management-in-agile-inform-don-t-control/ Wed, 11 Sep 2024 13:36:29 +0000 https://engineering.hinshelwood.com/videos/mastering-evidence-based-management-in-agile-inform-don-t-control/ Evidence-Based Management helps you use data to guide decisions and understand team behaviors, but it should inform rather than control actions. Define clear outcomes, choose metrics that align with those goals, and use data as a conversation starter to uncover challenges and drive improvement. Regularly review metrics with your teams to stay aligned and focus on delivering real value, not just hitting targets. https://engineering.hinshelwood.com/videos/the-importance-of-evidence-based-management-in-agile-environments/ Mon, 22 Jan 2024 11:00:07 +0000 https://engineering.hinshelwood.com/videos/the-importance-of-evidence-based-management-in-agile-environments/ Evidence-based management helps Agile teams make smarter decisions by tracking key metrics like value delivered, time to market, and ability to innovate, ensuring changes actually lead to improvement. Without data, teams risk wasting time and resources on ineffective changes, but with regular measurement and analysis, they can adapt quickly and foster continuous improvement. Start by identifying and tracking a few important metrics, involve your team, and use the insights to guide your next steps. https://engineering.hinshelwood.com/videos/what-are-the-hierarchies-of-competence-vs-control-why-does-this-matter/ Thu, 13 Apr 2023 14:25:06 +0000 https://engineering.hinshelwood.com/videos/what-are-the-hierarchies-of-competence-vs-control-why-does-this-matter/ Traditional hierarchies based on control slow down decision-making and often promote people beyond their competence, while hierarchies based on competence allow the most capable individuals to lead in real time, enabling faster and more effective responses to market changes. Shifting to a competence-based structure can create a more agile, engaged, and market-responsive organisation. Development managers should consider moving away from rigid top-down models and foster dynamic leadership based on expertise to improve speed and adaptability. https://engineering.hinshelwood.com/videos/how-do-you-know-how-long-it-takes-to-deliver-value/ Fri, 26 Jan 2024 11:00:51 +0000 https://engineering.hinshelwood.com/videos/how-do-you-know-how-long-it-takes-to-deliver-value/ Measuring and improving Time to Market is essential for delivering value quickly and staying competitive. Key metrics like lead time, cycle time, time to pivot, time to learn, and time to fix help teams identify bottlenecks and make better decisions. Focus on streamlining processes, automating tasks, gathering fast feedback, and building cross-functional teams to reduce delivery times and ensure you are delivering what customers need most. https://engineering.hinshelwood.com/tags/predictive-operating-model/ Mon, 24 Nov 2025 13:22:30 +0000 https://engineering.hinshelwood.com/tags/predictive-operating-model/ The Predictive Operating Model is a traditional framework for organizing work that originated during the industrial revolution and is grounded in scientific management principles, notably those of Frederick Taylor and Henry Ford. It is characterized by hierarchical structures, centralized planning and control, functional specialization, and a strong emphasis on efficiency, standardization, and minimizing variability. This model assumes that customer demand and market conditions are stable, work can be fully specified in advance, and performance is best improved through detailed planning, specialization, and strict adherence to procedures. It operates through mechanisms such as predictive plans, fixed scopes and resources, stage gates, and individual accountability, with success measured by output consistency, cost control, and on-time delivery. The Predictive Operating Model excels in stable, predictable environments where repeatable processes and operational excellence provide competitive advantage, enabling organizations to scale efficiently and maintain clear accountability. However, it faces significant limitations in dynamic or uncertain contexts, such as slow adaptation to change, siloed functions, long feedback loops, and limited capacity for learning or innovation. As markets and customer needs become more volatile and complex, many organizations are transitioning toward more adaptive models that emphasize flexibility, cross-functional collaboration, and iterative learning. Understanding the Predictive Operating Model is crucial for organizations aiming to evolve their operating practices, as it highlights both the strengths that can be leveraged in stable settings and the constraints that must be addressed to succeed in agile, DevOps, or product-centric environments. https://engineering.hinshelwood.com/tags/cell-structure-design/ Thu, 10 Apr 2025 14:48:25 +0000 https://engineering.hinshelwood.com/tags/cell-structure-design/ Cell Structure Design is an organisational model that redefines traditional hierarchies by establishing a decentralised network of autonomous units, referred to as cells. Each cell is granted end-to-end responsibility, enabling rapid responses to customer needs and market fluctuations. This model aligns with the principles of the Beta Codex, promoting accountability and continuous adaptation through dynamic coordination rather than a command-and-control approach. Grounded in complexity theory, Cell Structure Design acknowledges the unpredictable nature of modern business environments, where adaptability is essential. By fostering transparency and collaboration both within and between cells, this structure enhances communication and accelerates decision-making, allowing teams to deliver value in a predictable and sustainable manner. The independent yet cohesive operation of cells facilitates ongoing innovation and process improvement, contributing to long-term organisational success. This systemic design not only boosts operational efficiency but also nurtures a culture of empowerment and engagement, which is vital for thriving in today’s fast-paced business landscape. Ultimately, the focus on value creation and responsiveness equips organisations to effectively navigate complexity, ensuring their competitiveness and relevance in the market. https://engineering.hinshelwood.com/tags/current-value/ Thu, 10 Apr 2025 14:21:05 +0000 https://engineering.hinshelwood.com/tags/current-value/ Current Value is a vital metric within Evidence-Based Management that quantifies the real-time value a product or service provides to its users. It includes various indicators such as customer satisfaction, revenue impact, and performance feedback, which together offer insights into the value being realised at any moment. This concept is crucial for teams striving to deliver value in a predictable and sustainable manner, as it facilitates continuous assessment and adjustment based on actual performance rather than assumptions. By tracking Current Value, organisations can make data-driven decisions that improve their offerings and better align them with customer needs. This ongoing evaluation promotes a culture of responsiveness and adaptability, allowing teams to swiftly adjust to feedback and shifting market conditions. Unlike static measures, Current Value is dynamic and systemic, reflecting the changing landscape of customer expectations and business environments. It empowers teams to concentrate on delivering meaningful outcomes, ensuring that their efforts lead to long-term success and customer loyalty. This emphasis on real-time value delivery distinguishes Current Value from other concepts such as Value Stream Management or Customer Satisfaction, which may not fully capture the immediacy and comprehensive nature of the value being generated. https://engineering.hinshelwood.com/concepts/model/ Wed, 09 Apr 2025 14:00:00 +0100 https://engineering.hinshelwood.com/concepts/model/ A model is a conceptual representation that aids teams in understanding and analysing complex systems or problems by simplifying intricate dynamics into more manageable forms. This simplification enhances clarity, enabling teams to visualise relationships, processes, and outcomes, which in turn fosters effective communication and collaboration through a shared framework for discussing challenges and opportunities. Models are particularly valuable in Agile, Lean, and DevOps environments, where rapid change and adaptability are essential. They serve as foundational tools for decision-making and systems thinking, distinguishing themselves from frameworks or methodologies by focusing on the underlying dynamics rather than structured approaches. For example, the Cynefin Framework assists teams in identifying problem complexity, while the Three Ways of DevOps model optimises software delivery through visualising flow and enabling feedback loops. By providing insight into the structural relationships that govern a system, models empower organisations to navigate complexity confidently, make informed decisions, align with organisational goals, and enhance agility and resilience. Ultimately, effective use of models allows teams to optimise their responses to challenges, ensure consistent value delivery, and drive sustainable organisational growth. https://engineering.hinshelwood.com/tags/lean-startup/ Tue, 11 Feb 2025 10:17:24 +0000 https://engineering.hinshelwood.com/tags/lean-startup/ Lean Startup is a methodology that integrates Lean principles into the development of new business ideas, prioritising rapid experimentation and validated learning. Originating from the need to minimise risk and investment in product development, it advocates for the creation of a minimum viable product (MVP) to test assumptions about customer needs and market viability. This approach allows teams to collect real-time feedback, facilitating informed decisions to pivot or persevere based on empirical evidence rather than mere speculation. By cultivating a culture of experimentation, Lean Startup enables organisations to innovate continuously and adapt quickly to shifting market dynamics. It promotes cross-functional collaboration, ensuring that insights from diverse stakeholders shape product development. While it shares similarities with Agile methodologies, Lean Startup uniquely emphasises the validation of business models and market fit, thereby supporting long-term sustainability. This systemic approach embeds learning within the organisation, fostering resilience and adaptability in a constantly changing environment. Ultimately, Lean Startup enhances the likelihood of delivering products that meet genuine customer demands, optimising resource allocation and aligning organisational goals with customer needs. https://engineering.hinshelwood.com/tags/minimum-viable-product/ Tue, 11 Feb 2025 10:17:24 +0000 https://engineering.hinshelwood.com/tags/minimum-viable-product/ Minimum Viable Product (MVP) is a fundamental concept in product development that emphasises the creation of a product version with just enough features to meet the needs of early adopters and facilitate feedback for subsequent iterations. Originating from lean startup methodologies, the MVP approach enables teams to quickly test hypotheses and validate market assumptions, thereby minimising the risk associated with investing substantial resources in untested ideas. This strategy not only accelerates product launches but also fosters a culture of experimentation and learning, which is essential for organisations seeking sustainable innovation. By promoting cross-functional collaboration, teams can collectively determine the essential features of the product, enhancing its relevance and aligning team members around common objectives. The MVP framework is not solely focused on speed; it establishes a basis for continuous improvement and value delivery, allowing organisations to remain responsive to evolving market conditions and customer preferences. Ultimately, this approach supports long-term success and resilience in a competitive environment by ensuring that products are developed in a manner that maximises value over time. https://engineering.hinshelwood.com/tags/organisational-physics/ Tue, 11 Feb 2025 10:17:24 +0000 https://engineering.hinshelwood.com/tags/organisational-physics/ Organisational Physics is a conceptual model that applies systems thinking to understand and influence the dynamics within an organisation. It originates from the need to comprehend how various elements, including people, processes, and technology, interact and affect overall organisational behaviour and performance. This model is crucial in agile, DevOps, and product development contexts as it enables teams to recognise patterns and feedback loops, thereby identifying systemic issues and areas for improvement. By providing a framework for understanding the forces at play, Organisational Physics facilitates more effective decision-making, change management, and innovation. It empowers organisations to become more adaptable and resilient, allowing them to respond to challenges while maintaining a focus on value delivery. Rather than merely managing specific methodologies, this approach offers a holistic perspective on the underlying dynamics that drive performance, fostering a culture of continuous improvement. In an era of rapid change, Organisational Physics serves as a foundation for leaders to align their strategies with the realities of their operational environments, ultimately enhancing decision-making processes and contributing to long-term organisational success. https://engineering.hinshelwood.com/tags/complexity-thinking/ Tue, 11 Feb 2025 10:16:54 +0000 https://engineering.hinshelwood.com/tags/complexity-thinking/ Complexity Thinking is an approach that utilises principles from complexity science to address the intricate dynamics present within organisations and systems. It acknowledges that many challenges faced by organisations are complex rather than merely complicated, characterised by unpredictable interactions and emergent behaviours. This perspective is vital for teams striving to deliver value in a predictable and sustainable manner, as it promotes a deeper understanding of the interdependencies within systems. By employing Complexity Thinking, teams can better foresee how changes in one area may have cascading effects throughout the organisation, leading to unintended consequences. This understanding nurtures a culture of adaptability, enabling teams to respond effectively to changing circumstances rather than relying on linear planning. It empowers organisations to embrace uncertainty, fostering experimentation and learning, which are critical for innovation. Furthermore, Complexity Thinking aligns with Agile and Lean principles by advocating for iterative processes and continuous feedback loops, shifting the focus from isolated tasks to the overall health and performance of the system. This systemic approach not only improves decision-making but also builds resilience, ensuring organisations can thrive in the face of change and complexity. By integrating Complexity Thinking into their practices, teams can discover new avenues for growth and improvement, ultimately enhancing their ability to deliver value consistently and effectively.