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By e-Core
•
July 22, 2025
Introduction In today’s digital economy, IT Service Management (ITSM) platforms are more than just support tools, they are strategic enablers that impact operational efficiency, user satisfaction, and business agility. With an increasing focus on automation, AI, and user-centric service delivery, selecting the right service desk solution has become a critical decision for CIOs, IT leaders, and digital transformation teams. Why choosing the right service desk tool matters The service desk is the heart of IT operations. Beyond resolving tickets, it supports governance, ensures compliance, and drives consistent service experiences. A well-chosen ITSM platform enables faster resolution, proactive problem management, better user engagement, and alignment with digital transformation goals. On the other hand, a misaligned tool can lead to inefficiencies, user dissatisfaction, and mounting operational costs. When to use each tool Choosing the ideal tool depends on your organization’s size, IT maturity, integration needs, and strategic objectives: Jira Service Management (JSM): Best suited for organizations already using the Atlassian ecosystem or looking for agility and fast ROI. Strong in DevOps integration and automation via Rovo. ServiceNow : Preferred for large enterprises needing robust enterprise-grade features, deep AI capabilities, and high levels of customization. Ideal for those with higher budgets and complex service architectures. Freshservice: A favorite among mid-sized companies that need a full-featured ITSM without the complexity. Known for ease of use and rapid implementation. Zendesk: Strong contender for businesses that need multichannel support, especially customer-facing teams. Good choice for aligning IT support with customer experience. ManageEngine ServiceDesk Plus: Ideal for organizations needing strong ITIL compliance, asset management, and on-premise or hybrid deployment options.

By e-Core
•
July 22, 2025
Throughout my career as a Project Manager, I’ve seen many companies, even those whose core business is technology, struggle to adopt Agile project management models like Scrum and Kanban. While many claim to use these methodologies, most actually operate under a hybrid approach, applying selected Agile practices while maintaining a traditional mindset. Even more than 20 years after the Agile Manifesto, many organizations still have difficulty executing core Agile practices. Issues like inconsistent ceremonies , poor task prioritization , and lack of delivery planning often delay product launches and lead to team dissatisfaction. Recently, I served as a Scrum Master for a client project where, over six months, we improved the team’s Agile processes and project management maturity. Working in an extended team model with the client’s development team and Product Owner, I helped optimize ceremonies and workflows while the client team remained focused on strategic business efforts. By the end of this period, the squad was operating more efficiently, with better backlog management, faster task execution, and shorter release times. This article shares the Agile improvements we implemented and the benefits they brought to the te am. Optimizing the daily me eting Agile frameworks recommend that the Daily Meeting (or stand-up) lasts no more than 15 minutes. When I joined the project, these meetings often exceeded 30 minutes because they had become status report sessions, reviewing each task and its delivery timeline. To fix this, we refocused the Daily on its core purpose: having each developer share (a) what they worked on, (b) what they planned to work on next, and (c) whether they had any blockers. To support the change, we created a shared page where team members could write their answers before the meeting. This helped them prepare concise updates. Eventually, this support wasn’t needed anymore, the team internalized the practice. We also noticed that completed tasks weren’t advancing through the Kanban board because developers weren’t updating the workflow status. This created bottlenecks despite tasks being technically done. To address this, we encouraged the team to update the task status daily, document the adopted solution, identify the next step, and assign the task to the next person in the execution flow . Eventually, the team became autonomous in keeping the board up to date. Another challenge was that unrelated discussions often took place during the Daily, such as deep dives into technical solutions. To resolve this, we created a separate 15-minute daily meeting for technical discussions and a weekly refinement session for reviewing complex tasks. This kept the Daily focused and efficient. By the end of the project, the Daily Meeting had gone from 40 to 15 minutes thanks to these adjustments . Product backlog prioritization One of the most common challenges in Agile teams is backlog prioritization. When everything is a priority, nothing truly is. Trying to deliver too many features at once reduces focus and often results in rework. In our project, the Product Managers had a long list of features they wanted released as soon as possible. We worked with the PO to rank tasks based on business value, impact, and urgency , using prioritization techniques such as customer value, cost of delay, and effort-to-impact ratios. We ensured this prioritization was clearly reflected in the Kanban board so developers would know what to tackle next without needing to ask. This increased autonomy and avoided idle time between tasks. The prioritized backlog also became a prerequisite for Sprint Planning. Developers would estimate each task, and based on team velocity , we could forecast what was achievable in the next Sprint. By avoiding work on lower-priority items before higher-priority ones were completed, we reduced WIP (Work in Progress) and increased delivery focus. Over six months, we reduced WIP by 20% and doubled the number of completed tasks per Sprint. Improving task detail Developers need well-defined tasks to execute efficiently. Yet in this project, many tasks only had a title or vague descriptions, requiring developers to chase down details, which delayed development.

By e-Core
•
July 22, 2025
A strategic approach to modernizing code At e-Core, we often partner with organizations whose software technically “works” in production, but just barely. Over time, shifting teams, competing priorities, and tight deadlines lead to codebases that are fragile, expensive to maintain, and risky to enhance. In this context, software refactoring becomes more than a technical task. It’s a business strategy that preserves continuity while unlocking future growth. Defining refactoring: Evolution without disruption Software refactoring is the disciplined restructuring of existing code, improving readability, modularity, and performance, without altering its external behavior. Unlike a full rewrite, refactoring delivers incremental value by: Accelerating feature delivery through cleaner, more modular code. Reducing operational risk by eliminating brittleness and regressions. Lowering total cost of ownership by making enhancements less labor-intensive. Why refactoring matters for business Healthy codebases have a direct business impact: Faster Time-to-Market: Modular components support parallel development and faster releases. Greater resilience: Decoupled services isolate failures and simplify maintenance. Easier onboarding: Clear architecture and design patterns help new developers ramp up quickly. Sustainable cost savings: Less firefighting, fewer regressions, and lower maintenance overhead. What may look like a simple “cleanup” is often the first step toward digital reinvention. Refactoring techniques In enterprise environments built on Java, C#, or Python, we apply proven object-oriented refactoring techniques to increase cohesion and extensibility: Class decoupling: Split monolithic classes into focused, single-responsibility components. SOLID principles: Apply interface segregation and dependency inversion to stabilize architecture. Composition over inheritance: Build flexible, interchangeable structures. Testability enhancements : Isolate side effects and inject dependencies for better test coverage. These techniques form the foundation of our incremental software refactoring roadmaps. Beyond OO: Choosing the right tools for each paradigm Modern languages blend programming paradigms. We help clients apply the right tools to the right problems: Functional patterns in Python to create concise, side-effect-free data pipelines. Kotlin/Scala hybrids that combine OO structure with expressive functional constructs. C# LINQ and Async for declarative data queries and scalable concurrency. This multi-paradigm approach ensures that systems remain robust, flexible, and expressive. A refactoring story: From debt to differentiation Case Study: Regional logistics provider
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