Challenges in Custom Software Development

I’ve been working as a contractual Program/Project Manager on complex projects for the past 7 years, most of which followed Agile methodologies. While the Software Development Life Cycle (SDLC) is designed to reduce risk, poor implementation can have the opposite effect. If not executed properly, it significantly increases the risk of project failure. Here’s a quick ranking of critical failure points that commonly derail software projects: 🔴 1. Unclear or Changing Requirements Poorly defined needs or constant scope changes break alignment early and often. ✅ Fix: Involve stakeholders early, use user stories and clarify DoD (definition of done), and validate frequently; another advice: make sure to define change request in the initial contract with the client. 🔴 2. Inadequate Planning & Estimation Unrealistic timelines or budgets create pressure that leads to shortcuts and burnout. ✅ Fix: Buffer for unknowns, involve tech leads in estimation. 🟠 3. Ineffective Communication Team silos and misalignment cause costly rework and delays. ✅ Fix: Daily stand-ups, shared documentation, clear ownership. The tech team needs to understand the functional requirement to be able to implement it technically. 🟠 4. Weak Design & Architecture Hasty or shortsighted technical decisions lead to rework and scalability issues. ✅ Fix: Involving a software architect who could support drafting the best scalable architecture choices within the available projects needs, constraints and budget 🟠 5. Insufficient Testing & QA Testing cut short = bugs in production, bad UX, security holes. ✅ Fix: Invest in a QA strategy to identify tests to be run by type of release, and automate critical time-consuming tests 🟡 6. Lack of Stakeholder Involvement Software built in isolation rarely meets business goals. ✅ Fix: Demo regularly (ideally after each milestone), build feedback into the cycle. 🟡 7. Poor Change & Config Management Inconsistent environments and chaotic updates derail progress. ✅ Fix: Version control, CI/CD, and clear change protocols. 🟡 8. Inadequate Risk Management Unexpected issues become blockers when risks aren't flagged early. ✅ Fix: Ongoing risk logs, contingency planning. 🟢 9. Neglecting Post-Launch Support No plan for support = user churn and poor adoption. ✅ Fix: Monitor performance, address issues fast. 🟢 10. Lack of DevOps & Automation Manual processes delay releases and increase error rates. ✅ Fix: Embrace CI/CD and infrastructure-as-code. Strong software isn’t just about great code—it’s about clarity, communication, and continuous feedback. A strong Project Manager implements the right processes and follows each step methodically to spot weak links early and address them proactively. And when issues do arise (as they often do), they stay calm, communicate transparently, and ensure all stakeholders remain aligned throughout the journey. #SoftwareDevelopment #SDLC #TechLeadership #ProjectManagement #Agile #DevOps #ProductDelivery

Chapter 16: The Price of Saying Yes When we started, we had a major problem—our product was terrible. Far from what we envisioned. The initial system, built by an outsourced team in India, was a disaster—buggy, unreliable, and unsustainable. Clients were losing trust, and we scrambled to keep things together. To fix this, we hired another outsourced team in Minsk, Belarus, to refactor the code. It helped, but not enough. By 2017, I realized patching a broken system wasn’t the answer. The only real solution was to rebuild from scratch with our new Kyiv team. This was massive. For a year, we kept the old system running while developing the new one—like fixing a plane mid-flight while building a better model on the ground. To complicate things, we made a critical sales mistake. In our desperation to land clients, we agreed to custom features for several of them. It seemed like a great way to win business. Clients loved it, and we were happy to accommodate—until we realized the high cost. If you’re ever in this situation, ask: • Will these features benefit future clients? • Will they set us apart? • Can they be leveraged in marketing? • Do they fit our long-term vision? We didn’t ask. We just said yes—leading to two major problems. Problem #1: Scalability Nightmare Each client had unique features, creating a tangled codebase. Every update risked breaking something. The more custom work we did, the harder it became to manage. Problem #2: Hidden Maintenance Costs While clients paid upfront, we didn’t account for ongoing maintenance—support, bug fixes, and QA. As we scaled, this drained resources. The hardest part? Learning when to say no. Turning down revenue is tough when you’re trying to grow. But short-term gains at the cost of long-term scalability lead to failure. We had to shift our mindset—focusing on core features that benefited all clients. We built a structured system to track requests, prioritizing only those aligned with our vision. Saying no was uncomfortable but necessary. We had to be disciplined. We had to protect our platform. And most importantly, we had to think beyond the next sale. Because in startups, success often depends on how well you balance growth and control. On this picture you will see some of our first team members: Ayisha Ashfaq William Edmunds Mark Wing 🙏

4 reasons custom features are derailing your growth. Use this pitch to fix it: Here is how to advocate for a rational approach to implementing customer requests, that will protect your company against: 1. Negative ROI that you can see coming from miles away 2. Hijacking of Engineering's development capacity To my colleagues on the leadership team: In the last quarter we ended up spending 53% of our development capacity on implementing customer feature requests. We developed features for Acme, Dunder Mifflin and Globex. We also developed features in the hope of signing potential customers Wernham Hogg, Exxya, and Yoyodyne. - Acme is still not using the feature we developed for them. - Globex is kind of using it, but now they have additional requirements. - Yoyodyne decided not to purchase after all. When we implement a feature for a specific customer we incur the following types of indirect costs — over and above our direct development costs. 1. Opportunity costs Every feature we develop for a customer displaces improvements we would have chosen to make to benefit all customers and/or our company. 2. Maintenance costs The feature will need to be maintained in working order through every future release for the life of the product. 3. Complexity costs Every feature we implement makes our codebase more complex to develop further, so each subsequent feature will cost progressively more. 4. Support costs Every feature will generate support calls and tickets of various kinds. We’re not charging enough: Based on the above, if we were to charge the true cost of implementing features for customers, they would be very expensive indeed – probably more expensive than customers would be willing to pay. These features are not economical: It likely costs us more to build and maintain such features than the lifetime value of the relevant customers. I propose we allocate a maximum of 20% of our development capacity for “Customer Specials” and set expectations accordingly with the sales department and our existing customers. — Your CTO Have you grappled with this situation and possibly come to a similar realisation? If you're a SaaS CTO or VP Engineering,  I'm hosting a private masterclass for you: A CTO Pathway to Tangible Business Outcomes Details and registration → https://lnkd.in/ddN6e2b7

Every time you hear "we need to customise that", your implementation costs just doubled. Here's what your implementation partner won't tell you: they love customisation requests. Why? Because they get to bill you twice - once to build it, and again every time it breaks during an upgrade. Yet 80% of customisation requests are just people wanting the new system to work exactly like their old one. That's not transformation - that's expensive nostalgia. Want to know the real cost? It's not just the development time. It's the testing overhead, the upgrade complications, and the technical debt that compounds with every change. Stop letting "but that's how we've always done it" drive your implementation into the ground. (… and no, I am not denying the value of customisations that are required for legal or compliance reasons, or those that result in truly competitive value – I’ve only been doing this for 30 years now…) And as my colleague Shaun will explain later today, it gets even worse when you try to build custom solutions on poor quality data...   What's the most unnecessary customisation you've seen in a D365 F&O implementation? Share your horror stories below. #D365FO #Implementation #Customisation #TechnicalDebt

👉 Unclear or shifting requirements are the silent killers of IT projects. Did you know 35% of IT projects fail due to lack of clarity? Imagine you're building a custom CRM, but months into development, the client requests major changes to the sales pipeline. Suddenly, you're facing a 2-3 month delay and a 40% cost increase. Sounds familiar? It happened with a US-based logistics client of mine. What started as a simple tracking feature turned into a full-blown fleet management system, costing an additional $50,000 and delaying launch by 4 months—all because of unclear initial requirements. But there’s a way to avoid this. Using Agile methodology, I broke down evolving requests into manageable user stories, keeping the project on track while accommodating changes. With early discovery workshops, we reduced confusion and misalignment by 50%. If you’re tired of projects going off the rails due to changing requirements, it’s time to rethink your approach. Start by implementing Agile and discovery workshops. How do you handle shifting requirements in your projects? Let’s discuss! #projectmanagement #consultant #digimonk #gwalior #gauravjain #ecommerce #crm #ai #agile #scrum

AI-generated code is revolutionizing early-stage development. We’ve seen tools like GitHub Copilot, ChatGPT, and Cursor enable rapid prototyping and automate repetitive tasks. This accelerates time-to-market and fosters innovation. However, relying solely on AI-generated code to build full applications poses challenges in maintainability and scalability. Inconsistent coding standards, insufficient documentation, and potential security vulnerabilities can complicate future development. To maximize the benefits of AI while mitigating risks, human oversight is STILL essential. Would you hand off system design to AI? Experienced developers should review AI-generated code, implement comprehensive testing, and strategically use AI for specific tasks. AI should complement human expertise, not replace it, especially when building robust systems.

Custom software rarely fails because it doesn’t work. It fails because no one knows when to stop. One 3PL I worked with built their own system. Smart team. Clear purpose. Solid start. But there was no gatekeeper. No one steering the bus. So when the system started working… everyone jumped on with pet projects: - Ops wanted this tweak - Sales needed that quote tool - Finance wanted reporting And because it was all “internal,” no one said no. The roadmap? Didn’t really exist — not when no one had the authority to steer the ship. The system bloated. And suddenly — they weren’t building leverage. They were maintaining Franken-software. 👆 I talked about this moment with Dave Crysler on the Everyday Business Problems podcast. 🎥 Clip here — full episode in the comments. If you're building your own WMS, watch this first. It’s not the code that gets you. It’s the lack of boundaries.