Engineering Management Practices

SACPCMP vs ECSA Engineers with significant project management experience 🧐 SACPCMP regulates project managers, construction managers, and construction project managers. Their focus is on planning, coordinating, and managing projects—particularly in the built environment. Registration categories include Professional Construction Project Manager (PrCPM), Professional Project Manager (PrPM), and others. The assessment criteria are aligned to project delivery, stakeholder management, cost/time/scope control, and risk management, rather than technical engineering design. ECSA regulates engineering professionals (Professional Engineers, Professional Engineering Technologists, and Professional Engineering Technicians). Their focus is on engineering problem solving, design, analysis, and application of scientific/engineering principles. The 11 outcomes ECSA assesses are aligned to engineering knowledge, problem solving, design, impact, ethics, and professional responsibility, not primarily project management. Where Engineers with Strong Project Management Experience Need to Be Careful - Many engineers spend years in roles that lean heavily toward project management—running teams, managing budgets, schedules, and contractors. While this experience is valuable, here’s the caution: ECSA requires evidence of solving engineering problems. If your application is dominated by project management duties, you risk falling short of demonstrating the necessary engineering competencies (design, analysis, problem definition, technical judgement). SACPCMP, on the other hand, values project management experience. If most of your recent work has been managing projects rather than doing direct engineering design or problem solving, you may align more closely with SACPCMP registration criteria. Overlap creates confusion. Some candidates mistakenly think project management experience automatically strengthens an ECSA application—it does not. In fact, if over-emphasised, it can weaken your case because assessors may conclude you are functioning more as a project manager than an engineer. Why This Matters If your career path is technical engineering (design, problem solving, innovation), then ECSA is the correct registration route, and you must ensure your submission highlights engineering outcomes rather than only project management achievements. If your career path is delivery-focused (coordinating teams, managing risks, overseeing schedules and budgets in construction or engineering projects), then SACPCMP may be the more appropriate professional home. Some professionals choose to register with both councils if their roles span both areas—but you must be clear about which body you are targeting, because the competencies assessed are fundamentally different. Bottom line: For ECSA, they need to show evidence of engineering problem solving and technical responsibility, not just project delivery. Otherwise, they risk rejection or misalignment.

Engineers work to produce technology (in the broad sense), processes, materials, systems and/or services that now pervade almost every aspect of our daily lives.   Doing that safely and in an economically and environmentally responsible way demands deep knowledge of mathematical and scientific principles, but it also requires deep understanding of engineering methods including risk management, requirements analysis, design, quality management, life cycle analysis (to name a few), and the appropriate execution and management of the engineering task. This is far from a prescriptive process, requiring sound professional engineering judgments at many points along the way in contexts characterised by complexity and uncertainty. But there are some common elements of good engineering practice and performance and one very helpful expression of these is captured in the PPIR Protocols which are a very important contribution to the practice of engineering. The Professional Performance, Innovation and Risk (PPIR) Protocols were developed over a 20-year period by many of Australia’s most eminent engineers, as an initiative of The Warren Centre for Advanced Engineering, within The University of Sydney at the time. They cover elements such as The Engineering Team and its stakeholders, The Engineering Task scope and objectives, Competence to Act, Statutory Requirements and the Public Interest, Risk Management, Engineering Innovation, Engineering Task Management, and the Contractual Framework. In September 2020 Engineers Australia became the custodian and licensee of the PPIR Protocols. They were last updated in 2016 and they will be revisited for possible updates (e.g. for sustainability considerations) by Engineers Australia in the future. But they are as relevant today as they were then, and, at just a few pages, are a highly recommended and accessible resource for all engineers and clients of engineering work. You can find the protocols on our website: https://lnkd.in/eW6sSaqd #engineering #ProfessionalStandards #EngineeringPractice #ProfessionalPractice #PPIR @engineersaustralia

Amazon does not use OKRs or KPIs. Instead, Amazon uses a simple, flat list of goals with no hierarchy. Each goal has a single owner and objective pass/fail criteria. Here is how this approach works so well for Amazon: Amazon’s goal-setting process is simple. Every year, through the OP-1 planning cycle, teams generate a list of SMART goals (specific, measurable, achievable, relevant, and time-bound). These goals fall into two categories: initiatives (things you want to build or complete) and metrics (things you want to achieve). These goals are not aspirational statements or vague ambitions. They are written with such precision that there is no debate at the end of the timeframe: a goal is either met or not met. For example, a goal might read, “Achieve TP 95 1-hour delivery to any business in the Los Angeles metro area (see zip codes here) by September 15th for 200k items, including the top 75% business items.” You either did that, or you didn’t. There is no room for debate. Roughly 10 to 20 percent of the goals created in the OP-1 are elevated to S-team (senior executive/c-suite) goals when a senior executive says, “This should be an S-team goal.” That designation doesn’t change how the goal is written; it just adds more rigor to how progress is tracked. For S-team goals, owners must report status monthly or quarterly using a simple red/yellow/green system. Green means on track. Yellow signals risk. Red indicates you will not meet the goal unless you make a significant change. At the end of the goal’s timeframe, the goal is marked as “met” or “not met”. There is no partial credit and no scoring system, just pass or fail. One of the most interesting aspects of Amazon’s approach to goal setting is its strong emphasis on team-controlled levers that, if improved, will lead to better business outcomes. This means goals rarely say “Generate X revenue”; instead, they say something like “Increase on-time delivery by X percent” or “reduce receive cost per item by X dollars and cents.” This goal-setting method is often misunderstood. A senior executive at another large company once asked me, “At what level do Amazon leaders start managing the real stuff, like revenue and profit?” The answer is: there is no such level because the expectation is that you operate at all levels. Input metrics, the nitty-gritty things that the company controls that can impact the customer experience, are the “real stuff”. Ultimately, this goal system works because it’s brutally simple. There’s no cascading structure, no weighted scorecards, and no project management software required to track it. If you own a goal at Amazon, you’re responsible for hitting it.

𝑷𝒂𝒓𝒕 4 – 𝑺𝒊𝒙 𝑬𝒍𝒆𝒎𝒆𝒏𝒕𝒔 𝒐𝒇 𝑷𝒓𝒐𝒋𝒆𝒄𝒕 𝑪𝒐𝒏𝒕𝒓𝒐𝒍𝒔 – 𝑪𝒐𝒎𝒑𝒆𝒕𝒆𝒏𝒄𝒚 𝒂𝒏𝒅 𝑳𝒆𝒗𝒆𝒍 𝒐𝒇 𝑬𝒇𝒇𝒐𝒓𝒕 𝑩𝒚 𝑳𝒂𝒏𝒄𝒆 𝑺𝒕𝒆𝒑𝒉𝒆𝒏𝒔𝒐𝒏, 𝑪𝑪𝑷 𝑭𝑨𝑨𝑪𝑬 𝙊𝒓𝙜𝒂𝙣𝒊𝙯𝒂𝙩𝒊𝙤𝒏𝙖𝒍 𝑪𝙤𝒎𝙥𝒆𝙩𝒆𝙣𝒄𝙮: With the enterprise capabilities defined, the organization can begin establishing the taxonomy of the organizational competency. When defining organizational competency, it must identify the corporate and functional project mandates that support the overall business strategy. The organization should also define its vision and mission statements, executive directives, and key performance indicators (KPI). Subsequently, the organization must establish its required project management and project controls standard practices, processes, templates, and tools to provide the appropriate monitoring levels, controls, and project reporting. These standard practices must be functionally adequate and assessed against approved standards, preferably best practices known to produce favorable outcomes. Figure 2 provides an example of the hierarchy of deliverables that define and support organizational competency. The introduction and adherence to this hierarchy will provide the appropriate level of awareness of the health of the project and organization. When establishing the business norms for operating a project delivery model, the organization will be required to provide the appropriate context and governance for applying any policies, procedures, and processes. An organization cannot be successful if it does not ensure compliance with these requirements. The policies, procedures, and processes are written to improve the efficiency and effectiveness of the organization, as well as improve the timeliness of decision-making and problem-solving. Finally, by ensuring compliance, the organization can identify and mitigate enterprise, portfolio, and project risks. Policies, procedures, and processes are written to protect the organization’s interests, not to obstruct the membership of the organization nor the delivery of the project. Organizations may want to reference AACE’s Total Cost Management Framework and associated recommended practices to develop organizational competencies.

At Amazon, SDMs (Software Development Manager) are expected to take a holistic, end-to-end ownership of the services they manage. This means being deeply involved not just in the development process, but also in the ongoing operations and continuous improvement of those services. A critical skill for an effective SDM is proactively finding problems. Rather than just reacting to issues as they arise, SDMs need to be able to identify potential problems before they manifest, analyze trends and patterns in customer and on-call data, and then devise long-term, strategic solutions to elevate the operational excellence of their services. Additionally, SDMs must be able to think big and innovate. They should be able to envision ambitious, transformative improvements to their services, and then work backwards to make those visions a reality. The first step is to deeply understand your service - what are the critical components of your architecture? How is a request processed by your service, hop by hop, component by component? Where are the bottlenecks in your system? You need to have this basic understanding of your service's inner workings before you can really see the problems and start creating ideas to address them. Next, you need to know your customers - what value does your service provide to them? What are the key performance indicators (KPIs) to measure the customer experience? What are the top three pain points that customers face when consuming your service? Understanding the customer perspective is crucial. Equally important is understanding the pain points of your on-call engineers. What keeps them awake in the middle of the night? What are the top three issues they deal with? What is the size of their ticket queue, and how many pages do they receive per on-call shift? Addressing the on-call team's challenges is essential for improving operational efficiency. Once you have a good understanding of the service, the customers, and the on-call team, it's time to think outside the box. Many operational problems are actually signals of underlying architectural defects. For example, if you keep getting tickets from customers requesting quota limit increases, your immediate response might be to automate the approval process. However, this is just addressing the problem at the surface level. Instead, you could ask yourself: Why do we have a quota limit for customers in the first place? Can we make the limit adaptive to customer demand, using concurrency to tune the dynamics of demand and capacity for 99.99% of the use cases? This kind of innovative thinking, where you challenge the fundamental assumptions and explore more radical solutions, is what can lead to true operational excellence. By taking this holistic, customer-centric approach, you can become the product manager of operational excellence and drive meaningful improvements to your service.

Lessons from the Trenches: What I've Learned as a Principal Engineer in Amazon Search Amazon's [Principal Engineer tenets](https://lnkd.in/eHtuzWMA) provide valuable guidance that comes alive when applied to specific challenges. Let me share how three experiences taught me what these principles mean for me in practice. Early at Amazon, I noticed our search and catalog systems weren't speaking the same language. Search was built for shoppers while catalog served sellers, creating a disconnect in how we understood products. When customers searched, we struggled to connect their intent with the right items. "Technical Fearlessness" meant proposing an overhaul of data flow between these systems rather than continuing with incremental fixes. This required questioning established patterns across multiple organizations. "Leading with Empathy" became essential as teams brought different perspectives. I discovered even basic terms meant different things to different groups. By actively listening and rephrasing in my words—"So what you're saying is XYZ?"—I built bridges between viewpoints. This wasn't just about being nice; it created the shared understanding necessary for technical progress. Another experience taught me about being "Balanced and Pragmatic." After analyzing tens of millions of search queries to understand the filters that customers encountered, I found quality issues invisible in our averaged metrics and aggregated dashboards. We developed fixes but faced a choice: wait for a sustainable solution or deliver immediate improvements. We chose customer experience, rolling out enhancements while confirming their value through testing, then building sustainability afterward. Sometimes the best technical decision isn't the most elegant—it's the one serving customers now while creating space to build properly for the future. Finally, "Learn, Educate, Advocate" took on new meaning with AI's evolution. Realizing I was behind on AI coding tools, I jumped directly into practice—progressing from basic prompts to Q CLI. This led to building a server in one-tenth the usual time, revealing how we might boost productivity across our engineering work. These experiences showed me that Amazon's PE tenets gain meaning through application—practical guides that help navigate complex technical challenges while focusing on delivering better experiences for customers.

At the recently concluded AWS re:Invent, Werner Vogels shared some critical lessons that are universal to improving architecture and processes within Engineering teams across the board. As systems inevitably grow in complexity over time, he suggests embracing evolution and building with simplicity and manageability in mind from day one. Some of the key lessons about managing complexities that were worth noting include: 1. Make evolvability a requirement: Design systems knowing they will change. Prioritize flexibility and anticipate future needs. For instance, Amazon S3 has a simple API that has remained consistent while the underlying architecture has undergone radical transformations to accommodate growth and new features. 2. Break complexity into pieces: Decompose systems into smaller, manageable components with well-defined interfaces. This allows for independent scaling, evolution, and maintenance. Amazon CloudWatch has evolved from a simple service to a collection of microservices to improve functionality and address engineering challenges. 3. Align your organizations to your architecture: Structure teams to mirror the architecture of your systems. This promotes ownership, clear responsibilities, and efficient development. It is important for teams to own their work and for leaders to foster a sense of agency and urgency. 4. Organize into cells: Divide systems into isolated cells to limit the impact of failures and disturbances. This approach enhances reliability and simplifies operational management. Vogels explains how various AWS services like CloudFront and Route 53 utilize cell-based architectures. 5. Design predictable systems: Minimize uncertainty by designing systems with predictable behavior. Ensure consistent processing and avoid spikes or bottlenecks. 6. Automate complexity: Automate everything that doesn't require human judgment. This frees up resources and reduces the risk of human error. AWS, for instance, leverages automation extensively, particularly in security, with automated threat intelligence and agent-based workflows for support tickets. A link to the complete session is available here: https://lnkd.in/gxWquATs

A few years ago, an engineer on my team suggested rebuilding one of our core systems. His reasoning? “It will be easier to maintain in a new language.” On the surface, it sounded reasonable. But when we dug into the details, the problem wasn’t the language at all. It was that we couldn’t easily identify customer data during debugging. The “rebuild” would have been a huge effort—and it wouldn’t have solved the real issue. This is exactly why the “working backwards” approach at Amazon is so powerful. You start with the customer, clearly define the problem, and only then explore solutions. Skip straight to the solution, and you risk building something impressive but ultimately irrelevant. For engineers, this process can feel unfamiliar. We’re trained to think about capabilities: new frameworks, architectures, and technologies. But the real value comes from understanding the customer and the specific impact of the problem. How long does a process take for them? How does it affect their experience? How can we measure improvement? Once the problem is clearly defined, multiple solutions can be explored and compared. Each comes with its effort, benefits, and trade-offs. This makes prioritization much clearer, and ensures that the work you invest actually delivers measurable value. Working backwards also helps your team claim credit for the impact they create. When you tie your work directly to improvements for customers, everyone sees the value added, and the team can continue focusing on the things that truly matter. I go into this process in more detail in my article, with examples and practical steps for applying it in engineering teams. If you want a structured, practical way to ensure the work you do actually solves real problems, it’s worth checking out.