BA community

Hey, Community! 🙌 Just one day to go until our meet-up - don’t forget to register, we're waiting for you! If you'd like to dive deeper into the topic, join our upcoming meetup: 🎤 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝘀 & 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝘀: 𝗛𝗼𝘄 𝘁𝗼 𝗢𝗽𝗲𝗿𝗮𝘁𝗲 𝗮𝘀 𝗢𝗻𝗲 𝗧𝗲𝗮𝗺 📅 June 18, 2026 🕓 18:00 CEST / 16:00 UTC / 17.00 Minsk / 18.00 Poland We'll discuss how Product Managers and Marketing Managers can work together across the entire customer lifecycle—from market research and positioning to onboarding, retention, and growth. I'll share practical frameworks, real examples, common collaboration traps, and the tools that help teams make better decisions together. 👉 Register here: Enter your registration data for the meetup Looking forward to seeing you there! 🙂

GPT-5.5: WHY THIS MODEL UPDATE MATTERS FOR BA/SAs 🔶 OpenAI released GPT-5.5 as a model for complex professional work - and for Business and System Analysts, the key point is not only stronger reasoning. The real signal is workflow maturity. GPT-5.5 is positioned for coding, online research, information analysis, document and spreadsheet work, and tool-based execution. It also supports long-context work in the API, which makes it more relevant for real analytical environments: specifications, transcripts, legacy documentation, tickets, policies, and system descriptions. What matters most for BA/SAs: 🔹 Better support for complex tasks Analytical work is rarely one prompt → one answer. It usually means reading context, comparing versions, finding gaps, checking assumptions, and preparing structured outputs. 🔹 Stronger tool use GPT-5.5 is designed to work better across tools. For analysts, this matters because BA/SA workflows increasingly connect documents, spreadsheets, tickets, diagrams, and knowledge bases. 🔹 Long-context analysis Large inputs are normal in analysis: BRDs, API specs, discovery notes, call transcripts, business rules, and old documentation. Better long-context handling means better synthesis and fewer isolated answers. 🔹 More reliable professional outputs OpenAI also highlights stronger performance in professional tasks and reduced hallucinations in GPT-5.5 Instant. This is important because a polished but wrong AI output can easily become a bad requirement or misleading decision note. For BA/SAs, the practical use cases are clear: • requirements review • acceptance criteria drafting • gap and contradiction analysis • stakeholder meeting summaries • documentation comparison • impact analysis • test scenario preparation • backlog refinement support My takeaway: GPT-5.5 is another step from AI as a chatbot toward AI as a workflow assistant. But the analyst’s responsibility does not disappear. The value shifts to context control, validation, traceability, and knowing where AI output is useful — and where it is only a hypothesis. The best analysts will not be those who simply use GPT-5.5. They will be those who can integrate it into analytical workflows without losing ownership of quality. BusinessAnalysis RequirementsEngineering GPT55 OpenAI

Is a software release just a technical procedure? 🤔 For a digital native - I believe yes. But for someone who spent 20 years in Event Management before pivoting to system analysis at 40+, a release is a high-stakes performance. At first glance, these two universes seem to exist on opposite poles. One is about spotlights, catering, and microphones, the other is about SQL queries, API contracts, and Jira tickets. However, as I navigate my career path, I’ve realized that a software release and a large-scale forum share the same DNA. Imagine a major international summit. You have months of planning, a diverse group of stakeholders with conflicting interests and ambiguous requirements, and a hard deadline that cannot be moved. That is exactly how a software release feels. In both worlds, your "backlog" is the event program. Your integrations are the external vendors and speakers who must perform in perfect sync. If the sound system fails during a speech, it’s a critical bug in production. If the registration desk is slow, it’s a bottleneck in the system architecture. As a system analyst, I’ve found that my event brain gives me a massive advantage. In event management, you learn to spot a crisis before it happens. You become a master of requirements gathering because if you misunderstand the client’s vision for a gala dinner, there is no undo button once the guests arrive. In IT, this translates to meticulous analysis. I don't just look at the data fields, I look at the guest journey, user experience. My transition was never about discarding my past, it was about reformatting it. When I’m analyzing a complex database structure, I use the same logical patterns I used to coordinate a 1000 person event. Both require a high-level view of the system and attention to details. Whether it’s a post-mortem report or a sprint retro, the goal is the same - to learn how to do it better next time. If you are considering a career shift at any age, stop viewing your previous experience as white elephant. It is your secret weapon. You’ve spent years solving real-world puzzles under pressure. IT is just a different set of tools to solve the same human problems. Experience is the most stable architecture you can build. BusinessAnalysis SystemAnalysis

Requirements Engineering is changing fast — and AI is one of the main reasons why. At IREB exploRE2026 in Wrocław, many discussions focused on the future of requirements work, business analysis, system analysis, and the practical impact of AI on our profession. As a Business and System Analyst at Andersen, I had the opportunity to speak on the topic: “AI-Aware Business Analysis: New Skills and Practices for IT Analysts in the LLM Era.” The key problem to address is simple: AI can generate, summarize, compare, and review analytical artifacts much faster than before. But faster wording does not automatically mean better understanding. A polished requirement may still hide weak assumptions, missing context, or unclear business intent. 📝 In my presentation, I focused on several practical ideas: - AI should support analysts, not replace their responsibility. - Analysts should move from simple artifact production to analytical orchestration. - Context engineering becomes as important as prompt engineering. - AI can help with discovery, elicitation, drafting, review, and system analysis — but every output must be validated. - Traceability, source awareness, and human approval become even more important in the AI era. 🟢 For me, the future analyst is not an “AI scribe.” The future analyst is a professional who can manage context, challenge outputs, validate decisions, and build reliable, traceable, and responsible AI-supported analysis. IREB exploRE2026 RequirementsEngineering

🗣 Product + Marketing = Results Why do some products skyrocket while others go unnoticed? Quite often, it’s not just about the idea or execution – it’s about how well the product and marketing are aligned throughout the entire user journey 👀 📅 On June 18, we’re holding a meetup where we’ll explore how product and marketing teams can operate as a single system – from market understanding to retention and growth. Agenda: – Where collaboration creates the biggest impact; – What each team truly brings to the process; – Why a lack of alignment leads to missed opportunities; – What a practical framework for joint decision-making looks like; – How to strengthen positioning and drive real impact. 🧠 No theory overload – just real-world scenarios and approaches you can apply right after the meetup. Speakers: 🎤Natallia Tarasevich – Product Manager/Product Owner/Business Analyst 🎤Aryna Barysionak – Lead Marketing Manager | Digital Marketing Manager 🔗 Register here: https://lnkd.in/dB9AJPD6 Two experts. One user journey. One result! Meetup details: ⏰ Time: 18:00 (СEST) 🕒 Duration: 60-80 minutes 🗣 Language: English 💻 Online: the link to the stream will be sent to your email specified in the registration form See you!

Major conference of IREB is now behind us 👏 Our community member Alexander Malyarenko recently represented us at IREBexploRE2026 - one of Europe's leading conferences on Requirements Engineering! As proud partners with IREB, we're thrilled to support this collaboration and gather valuable insights from cutting-edge events like this. Alexander shared powerful takeaways on Business Analysis in the LLM Era: AI isn't just adding tools - it's reshaping how analysts work. From AI-assisted interviews to orchestrating analytical workflows, the BA role is evolving toward contextual understanding, validation, risk governance, and managing ambiguity. 💡 📌 Stay tuned and Alexander will share more deep insights and practical tips in his upcoming posts! IREB exploRE2026 BusinessAnalysis RequirementsEngineeringAI

Communication is about empathy 🤍 We live in an era of total communication, yet it remains a weak spot for many in IT. There’s a reason why soft skills are a top priority for recruiters. Let’s dive into how we can boost our projects and careers using a few simple, often overlooked tips. ✔️Hearing vs. Listening 👂 What’s really behind your peer’s or manager’s frustration? Have you ever tried to walk in their shoes? Understanding the roots of the other person's thoughts is the key to success. Try looking at the situation from a different angle. Perhaps, you’ll find out that in the same circumstances you would behave the same way. Make the ability to truly listen to your core trait and it’ll change the way you handle daily communication. ✔️Why your “Awesome” is actually useless? We can easily write a negative review for a restaurant. But what about our colleagues? Aren’t we afraid to hurt their feelings? Actionable feedback isn't about offending people — it's about growth. We can’t fix our blind spots if we don’t know they exist. • Be fair and polite. • Encourage others to give you feedback, too. • Be extremely specific! Saying “You did it wrong” or “You’re awesome” is too ambiguous. It gives the other person nothing to work with. ✔️Don’t be a Meeting Ghost Even if you have a brilliant Scrum Master or PM, don’t hesitate to be their wingman. Imagine yourself standing in front of a crowd that doesn’t react to your jokes or questions. It’s just as awkward in a Zoom call as it is on a real stage. Even if it’s not your job to lead, a simple supportive phrase or a proactive answer breaks the ice. It makes the conversation more comfortable for everyone and speeds up the decision-making process. Communication isn't just about "talking." It's about empathy, clarity, and team support. By mastering these three simple habits, you’re not just being a "nice" person — you're becoming a high-value professional who can navigate any corporate environment. #SoftSkills #TechCommunication #FeedbackCulture

Hey, Community 👋 On June 9, we’ll talk about how to turn chaotic business requests into clear and actually useful dashboards. At the meetup, we’ll discuss: — Why many dashboards end up unused; — How to formalize requirements for metrics and data sources — How to improve communication between business teams, analysts, and data engineers. If you’ve ever dealt with endless revisions, last-minute “can we add one more chart?” requests, or discussions like “what exactly should this metric calculate?” – this meetup will definitely be useful for you 👀 🎙 Speaker – Darya Drobova, Principal BI Developer at EffectiveSoft with over 12 years of experience in BI and expertise in Power BI, Tableau, and IBM Cognos Analytics. 🎟 Register here You’ll get real-world cases, practical approaches, and templates you can start using in your work right after the meetup. Event details: ⏰ Time: 19:00 (Minsk time, GMT+3)/18:00 (CEST) 🕒 Duration: 1 hour 🗣 Language: Russian 📍 Offline: Andersen’s office in Minsk 💻 Online: The link to the stream will be sent to your email specified in the registration form This meetup will definitely come in handy 👀 Become a speaker See you!

WHAT BA/SAs SHOULD READ ON AI: APRIL PAPERS AND BOOKS 📕 April was a useful month for BA/SAs who try to understand AI not as hype, but as a working instrument. My short reading focus would be this: 1️⃣ First, papers on LLMs in requirements engineering. The most interesting part is not that AI can generate user stories. We already know that. The real question is whether it can help with gaps, contradictions, traceability, validation, and domain understanding. Example: Formal Requirements Engineering and Large Language Models by Alessio Ferrari et al., 2025. Why it fits: it is not just about generating requirements. It looks at how LLMs can support correctness, reliability and validation in requirements engineering. A good example for the idea: AI can draft, but the analyst must validate. 2️⃣ Second, materials on AI in business process modelling. This is especially relevant for analysts, because the discussion is moving from “AI writes text” to “AI helps structure work”. Example: BPMN Assistant: An LLM-Based Approach to Business Process Modelling by J. T. Licardo et al., 2026. Why it fits: this is about moving from text to process logic. The paper shows how LLMs can help create and edit BPMN models, which is directly relevant for BA/SA work. 3️⃣ Third, books about AI and knowledge work. For BA/SAs, the best AI books are not only technical. They should explain how decisions, roles, responsibility and collaboration change when AI becomes part of the workflow. Example: Ethan Mollick, Co-Intelligence: Living and Working with AI. Why it fits: this is not a technical book about models. It is about how people work with AI, how responsibility changes, and why human judgement remains central in knowledge work. My conclusion is simple: reading about AI is useful only if we read with an analyst’s mindset. Not “what can this tool do?” But: “what responsibility still stays with me?” #BusinessAnalysis #SystemAnalysis #RequirementsEngineering #AI #BA #SA

Bad requirements or bad users? 🤔 In 1935, Boeing built a plane so advanced it crashed on its first test flight. Engineers immediately blamed "pilot error". But the reality? The machine was simply "too much airplane for one man to fly". They did not ask for smarter pilots, they just added a simple checklist. I’ve been thinking about this from BA perspective. It is easy for us to design a complex flow and just expect users to "get it". When they get confused, click the wrong button, or abandon the process, our first instinct is often to write it off as user error. We assume they just didn't read the screen carefully. But honestly, I'm realizing we might be wrong to think like that. Often, what we call "user error" is actually a sign that we designed a system that is just too hard to fly. When a user makes a mistake, it usually means we built "too much airplane". Look, real users aren't sitting in a quiet room studying our systems. They are: - distracted - rushing - just trying to get a task done We can't expect perfect users. Instead, we have to accept our own blind spots as the people creating the system, and build safer paths. We need to guide users so naturally that they don't have to struggle. Great software shouldn't force people to think harder. It should just help them fly safely. #BusinessAnalysis #SystemDesign #ProductThinking #UXDesign #SoftwareDevelopment