Project Management

Stuck in an endless loop of client changes? Lost track of what revision this constitutes? Yeah. Been there. Done that. The secret? It's not about saying no. It's about saying yes to the right things upfront. Every project that goes sideways starts the same way: Vague agreements. Fuzzy boundaries. Good intentions. Six weeks later you're bleeding money and everyone's frustrated. Here's my framework after 30 years of running two 8-figure businesses: The SOW is your salvation. Not some boilerplate template. A real document that covers: • Exact deliverables (not "design work" but "3 homepage concepts, 2 rounds of revisions") • Hours of operation ("We respond M-F, 9-5 PST. Weekend requests get Monday responses") • Revision rounds spelled out ("Round 1 includes up to 5 changes. Round 2 includes 3.") • Feedback cycles defined ("48-hour turnaround for client feedback or the project may be delayed or additional fees may be incurred") But here's what most people miss— Don't work on client notes immediately. Client sends 37 pieces of feedback at 11pm Friday? Producer sends conflicting notes from the CEO? Marketing wants one thing, sales wants another? Stop. Collect everything first. Resolve the conflicts. Get on the phone and discuss it with your client to get alignment. Separate the "have to haves" from the "nice to haves". Then present unified changes. "Based on all feedback received, here are the 8 changes we'll implement. This constitutes revision round 2 of 3." Watch how fast the random requests stop. No extra work that goes unappreciated. No more feelings of being taken advantage of. Communicate before the crisis, prevents the crisis from happening. "Just so you know, we're entering round 2. You have one more included. After that, it's $X per additional round." No surprises. No awkward money conversations. No resentment. Scope creep isn't a them problem. It's a you problem. And that's good news, because that means you are in control. They're not trying to take advantage. They just don't know where the boundaries are because you never drew them. Draw the lines early. Communicate them clearly. Everyone wins. What's your most painful scope creep story? What boundary would've prevented it? Small Business Builders #projectmanagement #clientmanagement #businessgrowth

Make your budget process smoother! Use my checklist based on my 15 years of experience. 🔗 Download it here: https://lnkd.in/edvf5exs Here is what is inside: 1️⃣ Preparation & Planning 🔲 Understand management's expectations concerning growth, strategy & profitability 🔲 Set clear financial goals and differentiate between short and long-term objectives 🔲 Establish a structured approach for managing the budget process (deadlines, owners) 🔲 Ensure that budgeting activities align with the organization’s overarching goals and priorities Tip: you can use ChatGPT to draft your budget instructions or budget memo. If you want to learn how to use ChatGPT for Finance, you can learn it here: https://lnkd.in/e8RGdYsK 2️⃣ Sales Planning 🔲 Choose an appropriate method for sales planning 🔲 Detail your budget sufficiently for effective analysis 🔲 Consider external factors like market trends, economic conditions impacting the business 🔲 Ensure accurate phasing of the sales plan 🔲 Conduct 'what-if' analysis to understand impacts on resources and profitability 3️⃣ Operational & Resource Planning 🔲 Plan for production, delivery, and workload 🔲 Account for direct headcounts & determine capacity 🔲 Determine material needs and plan for necessary investments 🔲 Collaborate with cross-functional teams to develop a comprehensive operational plan 4️⃣ Costing & Overhead Planning 🔲 Compute standard costs: direct labor, material costs, and manufacturing overhead allocation 🔲 Budget for individual departments and allocate overhead costs accordingly 5️⃣ Financial Statements & Reporting 🔲 Translate the budget into key financial statements: Income Statement, Balance Sheet, & Cash Flow 🔲 Establish a structured reporting process to communicate budget-related information to stakeholders 🔲 Create a visual budget performance dashboard to quickly assess the financial performance 6️⃣ Monitoring & Analysis 🔲 Regularly monitor and analyze budget variances to identify deviations 🔲 Perform sensitivity analysis to understand potential impacts on the budget 🔲 Leverage financial data analysis tools to identify trends, patterns, and opportunities for improvement 7️⃣ Communication & Collaboration 🔲 Foster open communication and shared financial goals in relationships, both internally and externally 🔲 Engage with stakeholders from different departments to gather valuable insights 🔲 Develop and communicate clear budgeting policies and procedures 8️⃣ Final Review & Implementation 🔲 Review the budget for any inconsistencies or errors 🔲 Communicate the finalized budget to all relevant departments and ensure its implementation 👉 Did I miss anything? Get this checklist to organize your budget process. Link below in comments.

If You Can’t Explain Budgeting Like This, You’re Not Ready for FP&A Interviews. Let’s assume I ask you the budget for fuel (petrol/diesel) expenses that you are going to incur next year in 2026. How would you budget using the below techniques: 1. Incremental / Traditional Budgeting You take into account the expenses on fuel you made this year. Assuming that amount is INR 50,000. Considering inflation, fuel price changes, and usage patterns, you estimate a 20% increase. Accordingly, your fuel budget for next year will be INR 60,000 (50,000 + 20%) 2. Zero-Based Budgeting Instead of taking current year’s expenses, you start from scratch. You estimate how much your car will travel next year. Then factor in expected fuel price and mileage of your vehicle. Based on this, you calculate a reasonable estimate of fuel expenses for next year 3. Activity-Based Budgeting Let’s say you use the car only to commute to and from office. For each round trip, your car consumes fuel worth INR 500. Your budgeting would be based on this activity (number of trips taken in a year). If you go to office twice a week, total trips = 52 × 2 = 104. Hence, your fuel budget = 500 × 104 = INR 52,000. 4. Flexible Budgeting Your fuel cost depends on how frequently you travel. Instead of one fixed budget, you prepare multiple scenarios. Example: 2 days/week → INR 52,000 4 days/week → INR 104,000 Your actual budget will depend on actual usage during the year. 5. Rolling (Continuous) Budgeting You don’t fix the budget once for the entire year. You keep revising it periodically (monthly/quarterly). Example: if fuel prices increase mid-year or your travel increases, you update the remaining budget accordingly. 6. Top-Down vs Bottom-Up Budgeting Top-Down: You decide a cap (say INR 55,000) and adjust your usage to stay within it Bottom-Up: You calculate expected usage (like ABB/ZBB) and arrive at the number logically 7. Value Proposition Budgeting (using the same example) Instead of focusing only on cost, you evaluate whether the expense creates value. You analyse each type of travel: Office commute - necessary Leisure / unnecessary trips - optional You may reduce or eliminate low-value trips, carpool, or use alternative transport. Hence, your budget is driven by value derived rather than just estimated usage. This way, the same fuel expense can give you very different budgets depending on the approach you use.

Explaining the Evaluation method LLM-as-a-Judge (LLMaaJ). Token-based metrics like BLEU or ROUGE are still useful for structured tasks like translation or summarization. But for open-ended answers, RAG copilots, or complex enterprise prompts, they often miss the bigger picture. That’s where LLMaaJ changes the game. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗶𝘁? You use a powerful LLM as an evaluator, not a generator. It’s given: - The original question - The generated answer - And the retrieved context or gold answer 𝗧𝗵𝗲𝗻 𝗶𝘁 𝗮𝘀𝘀𝗲𝘀𝘀𝗲𝘀: ✅ Faithfulness to the source ✅ Factual accuracy ✅ Semantic alignment—even if phrased differently 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: LLMaaJ captures what traditional metrics can’t. It understands paraphrasing. It flags hallucinations. It mirrors human judgment, which is critical when deploying GenAI systems in the enterprise. 𝗖𝗼𝗺𝗺𝗼𝗻 𝗟𝗟𝗠𝗮𝗮𝗝-𝗯𝗮𝘀𝗲𝗱 𝗺𝗲𝘁𝗿𝗶𝗰𝘀: - Answer correctness - Answer faithfulness - Coherence, tone, and even reasoning quality 📌 If you’re building enterprise-grade copilots or RAG workflows, LLMaaJ is how you scale QA beyond manual reviews. To put LLMaaJ into practice, check out EvalAssist; a new tool from IBM Research. It offers a web-based UI to streamline LLM evaluations: - Refine your criteria iteratively using Unitxt - Generate structured evaluations - Export as Jupyter notebooks to scale effortlessly A powerful way to bring LLM-as-a-Judge into your QA stack. - Get Started guide: https://lnkd.in/g4QP3-Ue - Demo Site: https://lnkd.in/gUSrV65s - Github Repo: https://lnkd.in/gPVEQRtv - Whitepapers: https://lnkd.in/gnHi6SeW

𝗧𝗼𝗱𝗮𝘆, 𝗣𝗠𝗜 𝗿𝗲𝗹𝗲𝗮𝘀𝗲𝘀 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝗿𝗲𝘀𝘂𝗹𝘁𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗹𝗮𝗿𝗴𝗲𝘀𝘁 𝘀𝘁𝘂𝗱𝘆 𝘄𝗲’𝘃𝗲 𝗲𝘃𝗲𝗿 𝗰𝗼𝗻𝗱𝘂𝗰𝘁𝗲𝗱 - 𝗼𝗻 𝗮 𝘁𝗼𝗽𝗶𝗰 𝘁𝗵𝗮𝘁 𝗶𝘀 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝘁𝗼 𝗼𝘂𝗿 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻: 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗦𝘂𝗰𝗰𝗲𝘀𝘀. 📚 Read the report: https://lnkd.in/ekRmSj_h With this report, we are introducing a simple and scalable way to measure project success. A successful project is one that 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘀 𝘃𝗮𝗹𝘂𝗲 𝘄𝗼𝗿𝘁𝗵 𝘁𝗵𝗲 𝗲𝗳𝗳𝗼𝗿𝘁 𝗮𝗻𝗱 𝗲𝘅𝗽𝗲𝗻𝘀𝗲, as perceived by key stakeholders. This clearly represents a shift for our profession, where beyond execution excellence we also feel accountable for doing anything in our power to improve the impact of our work and the value it generates at large. The implications for project professionals can be summarized in a framework for delivering 𝗠𝗢𝗥𝗘 success: 📚𝗠anage Perceptions For a project to be considered successful, the key stakeholders - customers, executives, or others - must perceive that the project’s outcomes provide sufficient value relative to the perceived investment of resources. 📚𝗢wn Project Success beyond Project Management Success Project professionals need to take any opportunity to move beyond literal mandates and feel accountable for improving outcomes while minimizing waste. 📚𝗥elentlessly Reassess Project Parameters Project professionals need to recognize the reality of inevitable and ongoing change, and continuously, in collaboration with stakeholders, reassess the perception of value and adjust plans. 📚𝗘xpand Perspective All projects have impacts beyond just the scope of the project itself. Even if we do not control all parameters, we must consider the broader picture and how the project fits within the larger business, goals, or objectives of the enterprise, and ultimately, our world. I believe executives will be excited about this work. It highlights the value project professionals can bring to their organizations and clarifies the vital role they play in driving transformation, delivering business results, and positively impacting the world. The shift in mindset will encourage project professionals to consider the perceptions of all stakeholders- not just the c-suite, but also customers and communities. To deliver more successful projects, business leaders must create environments that empower project professionals. They need to involve them in defining - and continuously reassessing and challenging - project value. Leverage their expertise. Invest in their work. And hold them accountable for contributing to maximize the perception of project value at all phases of the project - beyond excellence in execution. 📚 Please read the report, reflect on its findings, and share it broadly. And comment! Project Management Institute #ProjectSuccess #PMI #Leadership #ProjectManagementToday

Running LLM-powered applications shouldn't drain your budget. While you're excited about building your next GenAI project, knowing how to optimize LLM costs is essential for long-term success. LLM cost optimization involves multiple complementary strategies to reduce inference expenses while maintaining performance. Input optimization focuses on efficient prompt engineering and context pruning to minimize token usage, ensuring only essential information is processed. Model selection involves choosing right-sized models for specific tasks, preventing resource waste from oversized models while maintaining accuracy. Model optimization techniques like quantization and pruning reduce model size and computational requirements without significantly impacting performance. Distributed processing leverages distributed inference and load balancing to optimize resource utilization across multiple machines, improving throughput and cost efficiency. Caching strategies implement response and embedding caches to avoid redundant computations, storing frequently requested responses and pre-computed embeddings for quick retrieval. Output management implements token limits and stream processing to control response lengths and optimize data flow. System architecture considerations include batch processing to maximize throughput and request optimization to reduce unnecessary API calls. Together, these strategies form a comprehensive approach to LLM cost optimization, balancing performance requirements with resource efficiency. The key is implementing these strategies in combination, as each addresses different aspects of LLM deployment costs. Success requires continuous monitoring and adjustment of these strategies based on usage patterns, performance requirements, and cost metrics. Know more about such LLM cost optimization strategies and techniques in this blog: https://lnkd.in/gMvbg6Se Subscribe to my YouTube channel to know & understand more in-depth concepts on Generative AI: https://lnkd.in/gmAKSxKJ

I caught up with a friend who works at a mid-size Swedish tech company. Over the last 4 months, their shipping velocity has almost doubled – not because they hired more engineers, adopted some new agile framework, or worked late nights. It came down to a single change in how they build products: they started using Lovable to prototype features instead of writing traditional spec docs. Before Lovable, it usually went like this: PMs drafted long PRDs, trying to anticipate every detail. Multiple stakeholders reviewed these documents, leaving comments and raising concerns. The document grew with each iteration. Alignment meetings were frequent but often resulting in ambiguity. Engineers often began implementation while details were still debated. Inevitably, confusion emerged about trade-offs, timelines got pushed, and features shipped incomplete or scaled back. Now, PMs build interactive prototypes directly in Lovable. These aren’t wireframes or rough mockups – they’re fully clickable, end-to-end experiences that feel like the real product. Engineers don’t have to guess what the flow should be. Designers don’t have to explain interactions. Everyone sees the same thing, from day one. The end result is fewer meetings, fewer misunderstandings, fewer rewrites. What used to take weeks of coordination now happens in a single day. This is what has provided the most value for enterprises using Lovable so far. Over time, the increase of clarity and velocity saves the companies millions of $ in wasted effort.

Just created this comprehensive Pandas cheatsheet that I wish I had when I started my  journey! After seeing fellow practitioners struggle with the same pandas operations, I decided to create a simple yet powerful reference guide: "9 Must-Know Pandas Operations for Working with Data" This is - • Focused on real-world use cases, not just syntax • Includes time-saving tips I learned the hard way • Covers both basic and advanced features • Clean, visual layout for quick reference Key sections include: - Data Import/Export tricks - Efficient data selection methods - Statistical operations - Time series handling - String manipulation - Advanced features you might not know about Perfect for: • Data Professionals (Data Engineers, Data Scientists, ML Engineer, AI Engineers, and Data Analysts) • Tech Professionals working with Data Here are a few other commands that can help you with advanced operations - 1. 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗶𝗽𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗦𝗲𝗰𝘁𝗶𝗼𝗻    - 𝚙𝚍.𝚌𝚘𝚗𝚌𝚊𝚝() for combining DataFrames    - 𝚙𝚒𝚟𝚘𝚝 vs 𝚞𝚗𝚜𝚝𝚊𝚌𝚔 operations    - 𝚍𝚏.𝚛𝚎𝚗𝚊𝚖𝚎() for column renaming    - 𝚍𝚏.𝚜𝚎𝚝_𝚒𝚗𝚍𝚎𝚡() and 𝚍𝚏.𝚛𝚎𝚜𝚎𝚝_𝚒𝚗𝚍𝚎𝚡() 2. 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝗮𝗹 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀    - 𝚍𝚏.𝚙𝚌𝚝_𝚌𝚑𝚊𝚗𝚐𝚎() for percentage changes    - 𝚍𝚏.𝚌𝚞𝚖𝚜𝚞𝚖(), 𝚍𝚏.𝚌𝚞𝚖𝚙𝚛𝚘𝚍() for cumulative operations    - 𝚍𝚏.𝚛𝚊𝚗𝚔() for ranking values 3. 𝗧𝗶𝗺𝗲 𝗦𝗲𝗿𝗶𝗲𝘀    - 𝚙𝚍.𝚝𝚘_𝚍𝚊𝚝𝚎𝚝𝚒𝚖𝚎() for converting to datetime    - More datetime accessors like .𝚍𝚝.𝚖𝚘𝚗𝚝𝚑, .𝚍𝚝.𝚢𝚎𝚊𝚛    - Business day operations with 𝚙𝚍.𝚘𝚏𝚏𝚜𝚎𝚝𝚜 4. 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀    - 𝚙𝚍.𝚌𝚞𝚝() and 𝚙𝚍.𝚚𝚌𝚞𝚝() for binning    - 𝚙𝚍.𝚐𝚎𝚝_𝚍𝚞𝚖𝚖𝚒𝚎𝚜() for one-hot encoding    - Window functions beyond .𝚛𝚘𝚕𝚕𝚒𝚗𝚐()    - Cross-tabulation with 𝚙𝚍.𝚌𝚛𝚘𝚜𝚜𝚝𝚊𝚋() 5. 𝗗𝗮𝘁𝗮 𝗖𝗹𝗲𝗮𝗻𝗶𝗻𝗴    - 𝚍𝚞𝚙𝚕𝚒𝚌𝚊𝚝𝚎𝚍() method    - 𝚍𝚏.𝚠𝚑𝚎𝚛𝚎() and 𝚍𝚏.𝚖𝚊𝚜𝚔()    - 𝚍𝚏.𝚌𝚕𝚒𝚙() for limiting values 6. 𝗠𝗮𝘆𝗯𝗲 𝗮 𝗡𝗲𝘄 𝗦𝗲𝗰𝘁𝗶𝗼𝗻 𝗼𝗻 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴    - MultiIndex operations    - Index alignment    - Cross-section selection with .𝚡𝚜() Have I overlooked anything? Please share your thoughts—your insights are priceless to me.

How to fail in an interview Topic: Product Backlog Role: Product Owner 👔 Interviewer: “As a Product Owner, how do you ensure stakeholder needs are reflected in the Product Backlog?” 🧑 Candidate: “I ask stakeholders what they need and add it to the backlog in priority order.” 👔 Interviewer: “Alright, but let’s make it real. Imagine this: You have multiple stakeholders with conflicting priorities—one wants a feature for a major client, while another insists on addressing technical debt. The team is overwhelmed, and deadlines are slipping. How would you handle this situation?” 🧑 Candidate: “I’d try to balance their requests and ask the team to work harder to meet both needs.” What the Product Owner Should Have Answered: ------------------------------------------------------ ✍️ Facilitate Prioritization: “I would engage stakeholders in a prioritization workshop, using a framework like WSJF (Weighted Shortest Job First) or MOSCOW, Or Kano Model to evaluate features based on value, time sensitivity, and effort.” ✍️ Align on Vision: “I’d refer back to the product vision and roadmap to explain how each request aligns with strategic goals, helping stakeholders understand trade-offs.” ✍️ Collaborate with the Team: “I’d consult with the team to assess capacity and feasibility, ensuring realistic commitments without jeopardizing delivery quality.” ✍️ Communication is Key: “Transparency is critical. I’d keep all stakeholders informed about the decisions, timelines, and reasons behind prioritization.” Impact of the Right Answer: ✅ Avoid chaos: Proper prioritization prevents overloading the team. ✅ Strengthen relationships: Transparent communication builds stakeholder trust. ✅ Deliver value: Aligning requests with the product vision ensures the team works on what truly matters. 💡 Takeaway for POs: Strong prioritization and stakeholder management are essential to success. How would you handle conflicting priorities? Share your thoughts below! 🚀 Need more! Join "Agile Interview Hub": Link in the comment section below #InterviewTips #ProductOwner #agile

If I had to setup a PMO today, Here's what I'd do: Step 1: See how things really are ↳ Interview execs, sponsors, PMs, and business leads ↳ Map all current projects - active, planned, and stalled ↳ Benchmark maturity across processes, tools, and culture ↳ Identify pain points (missed deadlines, ROI leakage, siloed teams) Step 2: Figure out how they should actually be ↳ Align with executives on “why the PMO exists” ↳ Lock in sponsorship to protect the PMO’s mandate ↳ Clarify which business units and geographies the PMO supports ↳ Define KPIs: cycle time, benefits realization, stakeholder trust, etc ↳ Decide scope: standards, governance, delivery, or strategy partner Step 3: Lay the groundwork ↳ Draft a RACI for PMO vs. execs vs. PMs ↳ Stand up intake and prioritization workflows ↳ Pinpoint quick wins the PMO can solve immediately ↳ Pick a starter toolset - Excel, Smartsheet, or light PPM ↳ Define governance checkpoints that enable - not delay - delivery ↳ Set lightweight standards (scope, schedule, risk, status reporting) Step 4: Pilot with purpose ↳ Select 1–2 projects with high visibility and executive sponsorship ↳ Apply the PMO framework in real time - don’t over-engineer ↳ Track value delivered vs. “old way” of running projects ↳ Package results into a case study to showcase impact ↳ Capture lessons learned in a living playbook Step 5: Roll out & roadshow ↳ Position PMO as an enabler - solving pain points, not adding burden ↳ Conduct PMO “roadshows” to share wins and benefits org-wide ↳ Create cheat sheets, quick guides, and templates for adoption ↳ Scale pilot practices across 3–5 additional projects ↳ Train PMs and sponsors on new processes Step 6: Measure & share ↳ Compare portfolio spend vs. strategic value delivered ↳ Share updates regularly with executives to build trust ↳ Use metrics to secure more resources and influence ↳ Report on benefits realized, not just activities done ↳ Create dashboards with one version of the truth Step 7: Take the next stride ↳ Update frameworks based on adoption, not theory ↳ Run quarterly PMO retrospectives with stakeholders ↳ Gather qualitative feedback (ease of use, clarity, impact) ↳ Push toward the next level of maturity without losing agility ↳ Expand into advanced areas (portfolio mgmt, benefits tracking, AI tools) ⚠️ What I’d avoid at all costs: ↳ Measuring success by reports produced instead of value delivered ↳ Trying to impose control instead of building credibility first ↳ Rolling out a PPM tool before fixing processes ↳ Starting with 50 templates nobody asked for 💡 If you had to build a PMO from scratch tomorrow, which step would you double down on first? -- ♻️ Repost to help PMOs succeed! 🔔 Follow me (Hussain Bandukwala) for more content like this.