Hello, Qlik Community,
I'm part of an organization that leverages Qlik Sense on-premise as the reporting layer for our analytics projects, within an OEM partnership framework. We're facing several challenges as we try to apply agile methodologies to our analytics projects, which are intricately linked with the core product development that follows a more traditional waterfall approach. Our key issues include:
1. Analytics Projects Treated Like Core Product Development: Our analytics projects are often lumped together with the core product software development cycles, making it difficult to maintain agility and respond to changing requirements.
2. Waterfall Approach for Core Products: The core product developments follow a waterfall methodology, leading to late delivery of essential data for the analytics layer. This misalignment causes delays and inefficiencies in our analytics project timelines.
3. Late Data Availability: We receive the necessary data for our analytics solutions very late in the development cycle, yet our deliverables are expected to be ready concurrently with the core product go-live.
4. Evolving Scope and Priorities: The scope and priorities of our projects tend to change over time, which is not adequately reflected in the initial design and planning phases, leading to frequent adjustments and realignments.
Given these challenges, I'm reaching out to the community for insights, experiences, or advice on how to better integrate agile methodologies into our analytics projects within this OEM partnership context. Specifically:
- How have you managed the integration of agile practices for analytics in environments dominated by traditional development methodologies?
- What strategies have you employed to ensure timely data availability and flexibility in scope and priorities for your analytics solutions?
- Are there specific communication or project management tools and techniques that have helped you align more closely with the core product development timelines while maintaining agility in your analytics projects?
Any shared experiences, tools, frameworks, or strategies that have worked for you would be greatly appreciated. We're looking to learn from your successes and challenges to improve our approach and outcomes.
Thank you in advance for your insights and support.
Best regards,
Felix
