How can project data inform capacity building for sustainable project management?

This doesn't happen overnight. Capacity building needs assessment. For it to be sustainable, it should be clear from the start that the capacities built cns be maintained over the long term without continued external support. There should be a measure of independence

why project data is so informative in capacity building for sustainable project management, is the fact that, every projects were monitored, evaluated and controlled, from the initiation, planning, execution and close out phases. And through these important components of projects, we can able to understand why project is successful, on-hold or event not complete. And from project management perspective through the process involve and using software tracking, costing, scheduling, monitoring and evaluating projects, Architects and Engineers can able to visualize project setbacks, that are related to the four stages of projects. And such challenges are inclusive both, from stakeholders, clients, Architects/engineers, governments/donor agency.

Data is important yes but we need to turn this data into knowledge for sustainability in PM. Knowledge guides the decision making process which is needed.

Project data is the information that you collect, analyze, and use throughout the project life cycle, from planning and execution to monitoring and evaluation.

The ability to change methods, methods and approaches in the future with maximum involvement in the project area. Implementation of current research and technology.

Data is the lifeblood of any project. With project data, relevant stakeholders can be engaged, and when they are engaged, their interests and intervention in capacity building ate inclusive and collaborative.

Data will help you look at the past, present and future. It will help you identify gaps, strengths and predict future scenarios.

Data is concrete information that gives you a clear picture. It can be unforgiving, but it enables you to see clear as day where everything stands. Additionally, it reveals needs that your organization has. By focusing on addressing these needs, you can find effective ways to move forward.

Project data capacity building refers to the process of enhancing an organization's or team's ability to effectively collect, manage, analyze, and utilize data in the context of project management. Regularly monitor and evaluate the effectiveness of your data capacity building efforts. Assess whether the implemented changes have resulted in improved data management practices, enhanced decision-making, or other desired outcomes. Adjust your strategies as needed based on the evaluation results. By investing in project data capacity building, organizations can optimize their project management processes, make more informed decisions, and improve overall project outcomes.

In a project, timely collection and analysis of data allows you to always keep your finger on the pulse of the project. Make urgent changes or change the concept.

What happens when a person accepts a blood transfusion, and the transfused blood is incompatible with his own blood? Catastrophic! Patients have died and do die for taking in the wrong oxygenated blood. In the same way, projects have died and will die when unreliable data is used in decision-making activity.

Having a good discipline in data gathering and entry are the most important things. If an organisation does not have a good data handling practice, the capability to utilise it will be limited. The very first thing that needs to be done is set data gathering and handling guidelines specific to the company’s values and needs.

Data collection should be codified and streamlined. Having a good CRM, along with databases and reports aimed at collecting data are a must. However, the most important aspect of this is proper executing. If you are not consistently collecting the information as you need to do so, you will have some major issues down the road since your data will be incomplete.

Consider music. Music is a universal language. The arrangement of musical notation to create music can be understood and played by any musician, irrespective of the language that he speaks. In the same way, the right kind of data visualization can be understood by just about anybody who understands business or the use of data, irrespective of the language that he speaks.

One thing I have found helpful is the use of PowerBI and tableau for visualization. I do find that all these tools are ineffective if we have no strategy for asking the correct questions. Reports are based on data collected.

Visualizing project data goes beyond mere representation; it's about weaving a compelling narrative. The art of data storytelling not only captivates the audience but also ensures clarity. It's vital to adapt these visualizations to cater to different stakeholders—what resonates with a data scientist might differ for a project manager. Leveraging interactive tools, like those in Tableau, empowers individuals to dive deeper and derive insights. I can't stress enough the importance of clean data; automated processes are crucial. Moreover, the advent of augmented analytics, powered by AI, transforms our data understanding. With predictive analytics, we can anticipate trends and outcomes, and real-time data keeps everyone in the loop.

If you have statistics, then finding ways to develop metrics that make use of percentages will be extremely helpful in identifying efficiencies and effectiveness. If your data consists primarily of customers and their contact information, then finding ways to break up your customer base into smaller groups that can then be quantified is the way that you need to go.

An example that I have used for this was when data was showing that the number of work orders accomplished were below the threshold of what we planned to do. After doing much analysis we realized that staff needed to be trained in some courses to improve. This was the result of having low work orders.

Data can be historical. Data collected from a just-concluded project can be invaluable on the next project. In capacity building, data can be used for effective team management, revealing workloads, and ensuring fair distribution, thereby improving team productivity and morale.

Project data can show you the direction that you business is going. If you are able to visualize where you will be in five years, you will then see tools/equipment that need to be purchased in order for you to successfully achieve this objective.

Some Popular frameworks: -> Data Literacy Programs: These programs enhance the understanding of data and its implications across organization. -> Data Visualization Tools: Tools like Tableau and Power BI help in presenting data in a visual manner. -> Data Governance Frameworks: Establishing data governance policies and procedures to ensure data accuracy, security, and compliance. -> Analytics and Machine Learning Platforms: Platforms like Python, R, and TensorFlow enable data analysis and predictive modeling. -> Data Training Workshops: Interactive workshops to improve data handling skills and knowledge within the workforce. -> Business Intelligence (BI) Tools: Tools like QlikView and Looker provide insights from data.

Project data is a valuable source of information for capacity building in sustainable project engagement. Project data can help identify the strengths and weaknesses of project teams,the opportunities and challenges of project contexts, and the impacts and outcomes of project interventions.By analyzing project data, project managers can learn from past experiences, improve current practices, and plan for future scenarios. Project data can also inform the design and delivery of capacitybuilding activities, such as training, mentoring, coaching, and peer learning. Project data can help tailor capacity-building to the specific needs and goals of project stakeholders, and measure the effectiveness and sustainability of capacity-building efforts

While project data provides insights, relying solely on data for capacity building overshadows the significance of critical thinking and adaptive learning in sustainable project management. Effective project management isn't about numbers alone; it's about nurturing a dynamic and resilient team that navigates uncertainties and adapt swiftly to changing project landscapes. Emphasizing human-centric skills development alongside data-driven insights fosters a holistic and sustainable approach to project management, one that values the intuitive understanding of team dynamics and the ability to pivot swiftly in the face of challenges, rather than purely relying on data for decision-making.

Project data can inform capacity building for sustainable project management by providing insights to improve performance and adapt to changing circumstances. Some best practices: (1) Data Collection and Analysis: Collect and analyze project data consistently to identify trends, issues, and opportunities for improvement. (2) Performance Metrics: Define and track key performance metrics aligned with project goals. (3) Lessons Learned: Document and share lessons learned to apply knowledge gained from past projects to future ones. (4) Continuous Training: Provide ongoing training opportunities for project team members to enhance their skills. (5) Feedback Mechanisms: Create mechanisms for stakeholders to provide feedback and suggestions.