66% of technology projects end in partial or total failure.
1. Set Clear Project Goals and Direction
One common pitfall in data projects is the lack of a clear project goal and direction. To overcome this, start by identifying the right stakeholders and collecting project requirements. Map out your stakeholders and develop a stakeholder management plan. Determine who holds the most influence and who will be most affected by the project. Understand their interests and keep them satisfied throughout the process. By setting up a project roadmap with well-defined objectives, milestones, and deadlines, you’ll have a clear direction for your project.
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2. Improve Data Literacy
Another hurdle in data projects is the lack of skills to effectively use and understand data. Educating your employees on data literacy is key to overcoming this challenge. Establish a knowledge repository where employees can access relevant information. Utilise tools like Google Sheets and Looker for data documentation and visualisation. Encourage problem-solving with data and provide training to enhance data literacy across your organisation.
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3. Secure Executive Support
Active involvement from management is crucial for the success of a data project. Develop a project governance process that involves executives from top to middle management. Establish regular stand-ups, steering committee meetings, and high-level strategic meetings to keep executives informed of progress and make strategic decisions. By gaining executive support, you’ll have the backing and resources needed to drive your data project forward.
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4. Set Realistic Expectations
Understanding what data can deliver and the time and effort required for implementation is vital. Adopt an Agile governance mindset by starting small and iterating. Collect feedback, data, and ideas to validate and scale up your project. This approach allows you to manage expectations effectively, delivering incremental results while continuously improving and adapting.
5. Provide Ongoing Support and Maintenance
Neglecting post-implementation support and maintenance can hinder the success of a data project. Create a backlog of maintenance tickets, prioritise them, and schedule regular maintenance activities. Allocate 15-20% of the total development time to maintenance tasks. Regularly review and update your backlog, estimating effort and including maintenance tasks in your project sprints. By prioritising and addressing maintenance needs, you ensure the long-term success and sustainability of your data project.
6. Effectively Prioritise Competing Priorities
Running multiple projects simultaneously can lead to conflicts in priorities. To overcome this challenge, create an effective task schedule that evaluates importance, urgency, and impact on your business. Negotiate deadlines with sponsors and update stakeholders about any adjustments. Use visual reminders such as Kanban boards, calendars, Gantt charts, and whiteboards to keep track of priorities and stay organised.
Key Takeaways:
- Set clear project goals, identify stakeholders, and develop a roadmap with defined objectives, milestones, and deadlines.
- Educate employees to improve data literacy, utilising knowledge repositories and data visualisation tools.
- Secure executive support through regular meetings and strategic involvement.
- Adopt an Agile mindset, starting small and iterating to manage expectations effectively.
- Provide ongoing support and maintenance to ensure the long-term success of your data project.
- Prioritise effectively by evaluating importance, negotiating deadlines, and utilising visual reminders.
By implementing these project management hacks, you’ll be well-equipped to overcome hurdles specific to data projects and transform chaos into clarity. Start applying these strategies today and unlock the true potential of your data projects!
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Unlocking the power of data
Devoteam’s experts provide tips and tricks for getting started with using data to generate insights and achieve business success. You’ll learn how to:
- Establish a data-driven culture in your organisation
- Tackle the technological and organisational aspects of collecting, analysing, and visualising data effectively
- Identify and mitigate common challenges in becoming a data-driven organisation like pitfalls, resistance to change and more
- Continuously improve and optimise your data-driven strategies