One of the most important things to remember when undertaking an IT Data and Analytics Project is to avoid making it your last.

IT projects are a crucial part of any business, as they help to streamline processes, improve efficiency, and increase productivity. However, these projects can also be complex and challenging, and it’s common for them to fail.

Data and Analytics Projects are unique in several ways. They are technically complex, require an iterative and agile approach, and may involve innovative cloud technologies, data governance, security considerations, and software vendor interaction.

Data and analytics project management requires unique skills, knowledge, experience, and the ability to roll your sleeves up and pitch in to ensure the project is delivered successfully and meets the business requirements.

Strategy

Technical Complexity: Data and analytics projects involve complex technological processes, such as data integration, data cleansing, data transformation, statistical modeling, and machine learning. Therefore, Project Managers must have a solid technical background and understanding of the latest technologies and tools.

ROI Measurement: Data and Analytics projects require organizational commitment and investment. Therefore, Project Managers must measure and monitor the ROI of the project to ensure that the project delivers tangible business value. An example is the achievement of a goal of 95% prediction accuracy for customer retention.

People Management: Successful Project management is more about people management. But people are inherently flawed, often have conflicting priorities, and may not always have the required skills. Every project plan must be adaptable to a changing business environment. “Stuff happens”, and a sound project planning system can accommodate quick adjustments with the team. Under-resourced projects are the ones more likely to be delayed and even fail.

When projects are completed on time and within budget, stakeholders are impressed and more likely to add new projects. Project management software can help organize activities, but adaptability to add necessary resources where needed is critical. It will be needed, but layers of management approvals can’t bog it down. That’s expensive overhead and slows everything down.

Project managers need that flexibility to avoid getting bogged down, pointing fingers at where delays are occurring, and hamstrung at supplying added resources to overcome issues as they arise. Good teamwork is efficient. Team members need to know that project managers have their backs.

Obviously, it’s no wonder that project management organizations tout project management systems! But too often, the system is taken to be more important than making the team members feel successful. Project Managers should make each project team member successful, which makes the project successful.  

Happy team members turn into long-term employees, which is efficient, productive, and inherently less expensive overall.

Companies that are successful at project management don’t micro-manage project managers. They lay them and adapt resources to needs to keep a project running smoothly. Time is money, and delays are expensive and often have hidden costs.

Complete the project on time and learn how to plan the next project better.

Tactics

Iterative and Agile Approach: Unlike traditional project management approaches, Data and Analytics Projects need an iterative and agile approach. Data and Analytics Projects often involve dealing with unknown variables, and the analysis process may require several iterations before reaching the final result.

Data Governance and Security: Data and Analytics Projects involve sensitive and confidential data. It is crucial to ensure proper data governance and security measures to protect the data. Data and Analytics Project Managers must ensure the project adheres to the relevant data protection laws and regulations.

Stakeholder Management: Data and Analytics Projects involve multiple stakeholders, including business users, data scientists, IT teams, and external vendors. Data and Analytics Project Managers must be skilled in stakeholder management, including managing expectations, resolving conflicts, pivoting when necessary, and communicating effectively.

One of the biggest reasons IT projects fail is the need for proper planning and preparation. Before embarking on an IT project, conducting thorough research and developing a solid plan is essential. This includes identifying the project’s objectives, determining the resources needed, and outlining the steps required to succeed. Without proper planning, it’s easy for an IT project to become overwhelming and challenging to manage.

Another reason IT projects fail is the need for more communication and collaboration. IT projects often involve multiple departments and stakeholders, and ensuring everyone is on the same page is essential. This includes communicating the project’s goals and objectives and informing everyone of the progress and any issues.

It’s easier to tout project completion on time and within budget instead of asking for more time and budget. It’s also important to be realistic about the resources and timelines for the project. IT Data and Analytics Projects can be complex and time-consuming, and having the right resources, including staff, equipment, and budget, is essential. Additionally, it’s important to be prepared for potential delays. Set realistic project timelines.

Finally, it’s essential to have a contingency plan in place in case things go wrong. Build in contingency time and extra budget for unexpected design or technology complications. This includes having a backup plan in case the project doesn’t go as planned and being prepared to pivot and handle any issues.

Listen: Ask your team members about their goals, what consumes their time, and how it fits the company’s strategy. Set measurable objectives and communicate them to the team in a way that is easy to understand.

Be open: Help your team members learn about who you are and what you hope to achieve. Building trust and open communication channels are essential for a new team.

Engage: Go beyond their resumes and learn more about your team members.

Evaluate: Take an unbiased look at your team members and determine who’s best suited for each role based on their skill set. Make sure they understand their role and what is needed from them.

Post Mortem or Lessons Learned: Survey the project team. Ask them what went well to keep doing that; recognize and improve upon What didn’t go so well. Tally the results and hold a meeting to evaluate. There should be no blame or finger-pointing. Keep the discussion positive.

Proof

Several studies have compared projects with project management versus those without project management, and the overwhelming consensus is that project management is essential for project success. Here are a few examples:

1. A Project Management Institute (PMI) study found that organizations with mature project management practices completed more projects on time, within budget, and meeting the original goals and business intent. [1]
2. Another study conducted by McKinsey & Company found that projects that used formal project management processes were more likely to meet their objectives, achieve a higher return on investment, and deliver products or services of higher quality. [2]
3. A review of project management literature by the International Journal of Project Management concluded that project management is critical to project success and that projects are more likely to fail without it. [3]
4. A study published in the Journal of Construction Engineering and Management found that projects with a formal project management process had better cost, schedule, and quality performance than projects without project management. [4]
5. A review of 30 years of research on project management by the University of Sydney found that project management practices, such as planning, scheduling, monitoring, and controlling, significantly improve project success rates. [5]

In summary, research consistently shows that projects with project management are more likely to succeed than those without project management. Effective project management practices help ensure that projects are completed on time, within budget, and with the desired level of quality.

Conclusion

In conclusion, Data and Analytics Project Management is full of twists, turns, thrills, and spills. They require unique skills, knowledge, and experience to ensure the project is delivered successfully and meets the business requirements. They are unique in several ways. They are technically complex, require an iterative and Agile approach, and may involve innovative cloud technologies, data governance, security considerations, and software vendor interaction.

IT projects are a crucial part of any business but can be complex and challenging. By adequately planning, communicating, collaborating, being realistic about resources and timelines, and having a contingency plan, you can increase the chances of success and avoid making this project your last.

Our consultants have successfully help hundreds of satisfied clients manage their Data and Analytics. Request a planning session with us today.

Frank Tirone is a Lead Consultant at CTI in our Data and Analytics Practice.

References:

[1] Project Management Institute. (2017). Pulse of the Profession® 2017. Newtown Square, PA: Project Management Institute.

[2] McKinsey & Company. (2016). Delivering large-scale IT projects on time, on budget, and on value. McKinsey & Company.

[3] Shenhar, A. J., & Dvir, D. (2007). Reinventing project management: A research outlook. International Journal of Project Management, 25(3), 289-298.

[4] Odeh, A. M., & Battaineh, H. T. (2002). Construction project management in developing countries: Jordan as a case study. Journal of Construction Engineering and Management, 128(2), 127-133.

[5] Bakker, R. M., & Hartmann, N. B. (2016). Thirt