Engineering Management Practices

Most brands are playing the wrong game. They’re moving the Queen. They should be moving all of the pieces on the board. Let me explain. Marketing-led growth gets all the attention. It’s sexy. It’s visible. Founders obsess over it. But marketing is just one piece. A powerful piece — but still one. Business engineering? It moves all the pieces in symphonic coherence, And wins the game. When I advise better-for-you CPG brands, this is the shift I push for. Most teams pour everything into: – ad creatives – influencer UGC – CRO – new channels Good tactics. But they’ll only take you so far. Here’s what separates the breakout brands: They engineer growth at the business level. They move: – pricing – packaging – cash flow – operations – channel strategy – product architecture They see the full P&L → and use it. Let’s get specific. Example 1️⃣ → Gateway SKU Engineering: A Clean supplements brand. $60/month subscription = Hero SKU. Too much friction. First purchase wasn’t converting. The team launched a $15 trial SKU. Low-risk. Easy buy-in. Result? Trial → subscription conversion jumped 4x. CAC down 35%. LTV up. No ad change required. Business lever. Example 2️⃣ → Cash Conversion Engineering Frozen functional food brand. Growing fast, but cash-strapped. They restructured terms with co-packers. Negotiated faster pay from wholesalers. Cash cycle dropped: 120 → 45 days. Millions unlocked. That cash funded more growth. No new ad creatives needed. Business lever. Example 3️⃣ → Operational Engineering Gut health beverage brand. Local retail only. Wanted national. Cold chain shipping was blocking DTC. Their team reformulated + repackaged → shelf-stable. Suddenly: – DTC viable – National retail opened – Margins improved Game changed. Business lever. ____________ This is why I believe: Business-engineered growth > marketing-led growth. ♛ Marketing moves the Queen. ♗♖♕♔♘♙ Business engineering moves all of the pieces on the board. If you want to build a moat → If you want to scale with durability → You need to think beyond ads and creatives. ☑️ You need to think like a business engineer. Curious → are you moving just the Queen? Or are you moving all of the pieces on the board? ___________________________________________ 🔰 Better-for-you brands = better health, longer lives. 👉 Follow me, Kunle Campbell, and let’s scale impact together.

Ever seen a product flop because no one wanted it? Or a team torn apart by competing priorities? It doesn't have to be that way. The truth: The best products come from a perfect mix of business vision and engineering brilliance. Here's how to find that balance: ✅ Dos 𝗜𝗻𝘃𝗼𝗹𝘃𝗲 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 𝗲𝗮𝗿𝗹𝘆: They bring innovative solutions and technical reality checks. 𝗦𝗲𝘁 𝗮𝘀𝗶𝗱𝗲 𝟮𝟬-𝟮𝟱% 𝗼𝗳 𝗱𝗲𝘃 𝗰𝗮𝗽𝗮𝗰𝗶𝘁𝘆 𝗳𝗼𝗿 𝘀𝗮𝗹𝗲𝘀-𝗱𝗿𝗶𝘃𝗲𝗻 𝗾𝘂𝗶𝗰𝗸 𝘄𝗶𝗻𝘀: Flexibility can win deals. 𝗞𝗲𝗲𝗽 𝘁𝗵𝗲 𝗿𝗲𝘀𝘁 𝗳𝗼𝗰𝘂𝘀𝗲𝗱 𝗼𝗻 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗴𝗼𝗮𝗹𝘀: Balance the immediate with the important. 𝗘𝘅𝗽𝗹𝗮𝗶𝗻 𝘁𝗵𝗲 "𝘄𝗵𝘆": When everyone understands the purpose behind decisions, alignment follows. 𝗠𝗮𝗸𝗲 𝗿𝗼𝗼𝗺 𝗳𝗼𝗿 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗹𝗼𝗼𝗽𝘀: Leadership, sales, and engineering all have a role in the product roadmap. ❌ Don'ts 𝗟𝗲𝘁 𝘀𝗮𝗹𝗲𝘀 𝗱𝗶𝗰𝘁𝗮𝘁𝗲 𝘁𝗵𝗲 𝗿𝗼𝗮𝗱𝗺𝗮𝗽 𝘀𝗼𝗹𝗼: Chasing every opportunity creates chaos. Ignore technical debt: Today’s shortcuts can derail tomorrow's growth. 𝗢𝘃𝗲𝗿𝗹𝗼𝗼𝗸 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀: They see risks and opportunities others might miss. 𝗦𝗸𝗶𝗽 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀: Without a clear framework, priorities get lost in the noise. 𝗙𝗶𝗻𝗮𝗹 𝘁𝗵𝗼𝘂𝗴𝗵𝘁: The best teams don’t just build products—they build alignment. A shared vision transforms a list of features into something customers truly need. What strategies have helped your team create balance between business and engineering? Let’s discuss! 👇 ------------------------------------- 👨💻 I help ambitious companies build software, grow engineering teams and implement AI to Drive Change 📩 Drop me a line to discuss your project #productdevelopment #productteams #product

Engineering Leadership: The Key to a Resilient Product Culture The difference between a product-led organization and one driven by short-term sales often comes down to engineering leadership. If technical leaders lack influence, sales teams can overshadow strategic product decisions, fueling quick wins that rarely scale. How can this imbalance be prevented and corrected? 1. Product vs. Services Mindsets Product Mindset: Prioritizes innovation, user-centric design, and scalable development. Engineering leadership influences product strategy, ensuring features align with a cohesive vision. Services/Sales Mindset: This mindset focuses on immediate revenue. Roadmaps cater to custom client requests and quick-turn deals, often causing technical debt and fragmented offerings. 2. Why Short-Term Sales Wins Hurt Long-Term Fragmented Strategy: Sales-driven features address narrow client demands, diminishing a unified product roadmap. Technical Debt: Speedy, ad hoc solutions can overwhelm future improvements. Limited Differentiation: A reactive culture inhibits true innovation, allowing competitors to outpace your offerings. 3. Empowering Engineering Leadership Clear Product Vision: Establish long-term goals that guide prioritization. Each new feature should advance the overall product strategy. Cross-functional collaboration: Align Engineering, Sales, and Marketing with shared KPIs (e.g., product adoption, user satisfaction) to unify efforts. Technical Voices at the Table: Give engineering leaders executive-level authority. Their expertise on feasibility and risk is invaluable for balanced decision-making. 4. Correcting a Sales-First Culture Leadership Reassessment: Ensure engineering has an influential seat in strategy discussions. Roadmap Audit: Identify which projects truly serve long-term objectives and curb those that don’t. Strategic Communication: Explain to all stakeholders why shifting to a product-led focus will yield lasting competitive gains. Realign Incentives: Reward collaboration and product milestones, not just top-line revenue. 5. Long-Term Benefits of a Product Culture Ongoing Innovation: Motivated engineering teams explore emerging tech and user needs more deeply. Scalability: Thoughtful architecture and minimized technical debt ease future growth. Differentiation: A well-crafted product vision garners loyal customers, driving sustainable market success. Achieving sustainable growth hinges on influential engineering leadership to shape the product’s trajectory. While a sales-first approach can boost short-term revenues, it often weakens the company’s foundation. By prioritizing strategic engineering leadership, aligning teams around shared objectives, and pruning reactive development, organizations can pivot from a purely sales-driven mode to a truly resilient, product-centric future. Zinnov Karthik Amita Mohammed Faraz Namita Dipanwita Hani Mukhey@ ieswariya Sagar Komal Amaresh

@HSE Process Safety Leadership - Findings of Energy Division Inspection Programme Failures in effective process safety leadership / process safety management can be linked to historical Major Accident Hazard (MAH) events. Main Weaknesses: • Industry has reached ‘normalisation of deviance’ with organisations more willing toaccept degradation of MAH barriers without acting. Knowledge and appreciation of the overall risk profile is improving. Work in areas such as maintenance backlog reviews has helped, but further work is required in order to fully understand where an organisation may be exposed. • Cumulative risk continues to be a challenge. All organisations have developed cumulative risk tools but continue to struggle with demonstrating robust assessment and recording of decisions including where the decision made was to not intervene and cease production. • Audit and assurance is ineffective and is failing to identify areas of weakness.Organisations have not fully implemented industry guidance in this area. Weaknesses in the audit and assurance systems is preventing senior leaders from being assured of the ongoing effectiveness and suitability of the Safety and Environmental Management System (SEMS) and the Corporate Major Accident Prevention Policy (CMAPP). • Industry headcount has reduced significantly with many organisations potentiallyunder-resourced in critical areas, which is having a direct impact on MAH management. There is increasing evidence that competency within the workforce has reduced. • Increase in the number of new recruits in industry (commonly referred to as ‘greenhats’) is placing a burden on the offshore workforce. Insufficient time is being spent as part of the contractor on-boarding arrangements to ensure competency of individuals and correct behaviours. • Contractor engagement remains focused on personal safety with limited considerationof the impact that contracting organisations can have on MAH management. • Effective process safety leadership is being driven by individuals instead of an ingrained part of the organisational structure or culture. • There is an absence of a structured MAH competency framework and training forsenior leaders. • There are early indications of a drop-off in workforce understanding and appreciation of MAH risk. Industry needs to ensure that the workforce remains fully engaged and that efforts are made to provide the relevant awareness training. • Learning and improving. The PSLP inspection programme has not identified any newthemes which have not been identified by HSE previously either through routine inspections or other key programmes such as KP3 and KP4. Gaps in understanding can be linked to the loss of corporate knowledge / memory as a result of headcount reduction or change in personnel responsibilities.

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

After 5 years at Amazon, I found 1 practice that builds the best software teams: I call it knowledge distribution. ► If your team relies on "tribal knowledge": ↳ Onboarding takes months instead of weeks. ↳ You're always one resignation away from disaster. ↳ Your best engineers burn out from being constant bottlenecks. ↳ Critical systems become "no-fly zones" that only a few understand. ► If your team is good at sharing knowledge: ↳ Bus factor becomes a strength, not a risk. ↳ New hires become productive in days, not months. ↳ Any engineer can debug any system (without pinging "the expert"). ↳ Your top talent can focus on hard problems instead of answering the same questions True engineering leadership does not mean you must be the only one knowing it all. It means ensuring everyone knows enough to make you redundant. The choice is yours: Be the engineer who's constantly needed Or build the team that doesn't need you. How does your team handle knowledge sharing? ~~~ 👉🏻 Join 50,001+ software engineers getting curated system design deep dives, trends, and tools (it's free): ➔ https://lnkd.in/dkJiiBnf ~~~ If you found this valuable: 👨🏼💻 Follow Alexandre Zajac 🔖 Bookmark this post for later ♻️ Repost to help someone in your network #softwareengineering #coding #programming

The hardest technical decision I made at Amazon wasn't about technology. During a project, an engineering team wanted to rebuild our entire checkout system. I remember, the enthusiast team; "It's legacy code," one of my best engineering colleague said. "We can do it in 3 months." But here's what my Amazon experience taught me to ask: I asked the below Questions: 1/ Why now? 2/ What's the actual pain? 3/ What's the hidden cost? After diving deep (Amazon leadership principle in action), we discovered: - 80% of issues came from 20% of the code - Complete rebuild = 6 months minimum - Migration risks > Current pain What we did instead: 1/ Isolated the problematic components 2/ Created clear interfaces 3/ Rebuilt critical parts first Result: - 70% improvement in performance - Only 6 weeks of work - Zero customer impact The Framework I Used: 1. Pain Assessment - Current impact - Future risks - Resource cost 2. Solution Mapping - Quick wins - Medium changes - Complete rebuilds 3. Hidden Cost Analysis - Migration complexity - Team bandwidth - Customer impact Key Learning: Technical decisions aren't about the newest technology. They're about making the right trade-offs. Early PMs: What technical decisions are you struggling with? Let's solve them together 👇

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.

When I joined Amazon in 1999, our software and fulfillment network was swamped by the growth in demand. We were barely surviving. We couldn't be operationally excellent until we dug ourselves out of that hole and built systems and processes to meet the demand. Fast forward two decades, and Amazon is an example of Operational Excellence. It didn't happen in one day, week, month, or year… it was a series of steps, processes, actions, and decisions over many years. One of the steps we took to get there was to apply proven techniques from other excellent companies, namely Toyota. One of the methods they invented at Toyota is the “Five Whys” method for root cause analysis of failures. Here is how we used it and a template for you to use: Whenever there was a significant failure in the customer experience, we would run a formal investigation. This meant not just asking why the surface-level effect occurred, but also why the condition that allowed it existed in the first place, why the condition that allowed THAT condition existed, and so on. Asking “why” five times was a forcing function that pushed teams to reach the root cause. Then, once we knew exactly what happened, why it happened, and why our processes, rules, or systems allowed it, we made a plan to fix the root cause so it could never happen again. By the way, committing to following through on those two steps — much easier said than done. The output was a CoE (Correction of Error) document (6 pages or less) that described the issue, the actual root cause (which was often very different than the surface-level failure), and the long-term fix. These documents were not optional and they would be reviewed at the VP level or in some cases, the CEO level. Here is how to structure a CoE doc (copy and paste this into a doc): — [Insert Topic Here] Correction of Errors 1. Description of problem and its impact a. Description b. Data Collected to demonstrate the problem c. Customer Impact d. Financial Impact 2. Root causes (use the 5 whys method) a. Why did the error occur? b. Why did that condition exist? c. Why did the above condition exist? d. Why did the above condition exist? e. Why did the above condition exist? Answering these questions five levels deep should lead you to the root cause of the issue, though the tool does not tell you what questions to ask or how to find the answers, so it is not a guarantee of success. 3. Corrective actions taken a. b. c. etc, 4. Lessons learned (bad and good) Here are the errors we made and/or hard lessons we learned: a. b. c. d. e. Here are some things we did well: a. b. c. To better understand the CoE process, read a sample CoE report on our website: https://lnkd.in/gF-CPb8s

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