Project Management is a powerful tool for driving competitive advantage in organizations by enabling teams to deliver value rather than simply following rigid plans. Emphasizing transparency, flexibility, and data-driven decision-making, modern project management practices focus on meeting customer needs and fostering team autonomy for greater efficiency and innovation.

One of the outcomes of the Strategic Planning process conducted in organizations is a list of actions, initiatives, and projects aimed at achieving the goals defined for strategic objectives.

These projects are then filtered through specific criteria, resulting in a portfolio that will be executed by the teams.

However, there is significant risk in keeping this process inflexible. Nowadays, we must learn to respond to changes rather than strictly adhere to a plan. This principle applies to extensive planning processes and to projects at the directorate and management levels.

Delivering value is different from simply delivering projects. This shift in mindset is not yet complete. Rigid project plans that leave no room for change may seem more convenient. Many managers hold the false expectation that the world around them will remain the same from the beginning to the end of a project and prefer to fail while clinging to a plan rather than adapting to benefit stakeholders and deliver value. Value means meeting the customer’s needs. The value delivered is measured by those who will use the product. Project managers exist to deliver what the customer needs, not necessarily what was outlined in a perfect plan—often crafted by one or two individuals.

A key differentiator also lies in identifying requirements and specifications. In most cases, customers don’t know what they want. Clearly defining what needs to be done in a project or product is a strong indicator that, when teams start working, the discrepancies between what needs to be done and what is actually being done will be minimized.

This ability helps reduce rework, identify dependencies, and increase the value delivered by teams. To make this happen, the product owner must listen carefully to key stakeholders and document the essentials so that the team understands what needs to be done.

Another important aspect is the level of detail in the requirements that make up the backlog. This level of detail is directly related to prioritization. Items prioritized for upcoming sprints will require more detail. Items further down the backlog don’t need to be refined, as they are far from being developed. Detailing items that may never be produced wastes time.

To evolve as product teams, we must focus on certain principles. The first, a pillar of Scrum, is transparency. Everyone should know what others are working on. This practice helps foster T-shaped professionals—more versatile individuals capable of performing tasks across different process stages. Over time, this reduces dependency on specialists or minimizes it. While it may not achieve the same level of performance, it will be incredibly helpful in identifying problems and replacing team members if needed.

Organizations must also encourage teams to be more autonomous. Dictating how teams should work is counterproductive. Measuring individuals and creating metrics that do not improve processes is also not recommended. A key differentiator here is giving teams the space and trust to operate. There is no effective way to measure creative work—it is non-linear.

When it comes to solutions, keeping project scopes flexible is essential. Start projects with the information already defined about the product and use iterative and incremental approaches to reduce risks and eliminate uncertainties. Iterative development shortens feedback cycles—a critical practice for delivering value at the end of each iteration. Shortening feedback cycles brings us closer to the solution and avoids wasting effort on unnecessary items.

Regarding work items, it’s ideal to maintain system stability by aligning workload with team capacity. This prevents overload and backlog accumulation. Overloading the process increases lead time and reduces quality. The longer a task stays on the board, the more value it loses. Stop starting and start finishing.

Finally, we are living in the era of metrics. Our ability to collect data has significantly increased. Virtually every department in a company is open to data collection. This broad data availability has driven the demand for methods to extract useful insights. Data exploration has become a competitive advantage.

Data Science encompasses fundamental principles that guide the extraction of knowledge from data. It involves principles, processes, and techniques for understanding phenomena through automated data analysis. The primary goal of Data Science is to enhance decision-making—a critical interest for businesses. Data-driven decision-making (DDD) refers to basing decisions on data analysis rather than intuition. The more data-driven an organization is, the more productive it becomes. Remember, data is a business asset. Acquiring data requires investment.