Predictive management and empirical management offer distinct approaches to handling complex work.

Predictive management operates on the premise that the future course of work can be anticipated at the outset. This approach assumes that with enough planning and analysis, one can lay out a detailed roadmap for the work and follow it rigorously. The focus here is on careful upfront planning, with an expectation that the work will unfold as anticipated once these plans are set. However, this can be challenging in complex environments because of the inherent uncertainties and ever-changing conditions. As a result, a predictive approach may struggle to adapt when unforeseen challenges or new requirements emerge, leading to potential inefficiencies or deviations from the intended outcome.

On the other hand, empirical management acknowledges that not everything about complex work can be known from the start. Instead of predicting the entire path, this approach emphasises learning from ongoing work, making decisions based on observable results, and regularly adapting. It operates on an inspect and adapt approach. As the work progresses, the team uses real-world data and feedback to inform their next steps, ensuring they remain responsive to changing conditions and new information. This iterative and incremental approach allows for greater flexibility, particularly suited for complex work where unpredictability is the norm.

Before Scrum & Agile became widespread, traditional approaches to software development utilised a predictive method. Predictive techniques do not offer the best chance of success when doing complex work. Work where outputs, outcomes and challenges cannot be well predicted and fully understood beforehand. In these environments, we cannot standardise and rely on best practices. Each challenge we face is unique and requires its own new and unique solution.

Empiricism refers to the idea that knowledge comes from experience and observation rather than theory or speculation. Agile teams use an empirical process control approach to manage work. This involves raising transparency on the actual state of the environment and progress and then regularly inspecting and adapting based on feedback and observations. It uses data and metrics to guide decision-making and measure progress wherever possible.

As more about our product domain becomes known, our ability to make accurate predictions may increase. Knowledge comes from experience; the only way to get experience is to build the product, deliver it to customers, and inspect the results.

Command & Control Management

Command and control management is a traditional approach rooted in the industrial age, emphasising hierarchical structures and top-down decision-making. In this system, authority is centralised, and managers or leaders make vital decisions and then convey them to subordinates. These subordinates are expected to follow instructions without much deviation. Communication primarily flows from the top down, and lower-level feedback might face challenges travelling up the hierarchy. The primary premise of this model is that leaders or managers have the necessary knowledge and perspective to guide operations and make the best decisions, with efficiency often being a significant objective. This approach can sometimes lead to rigidity, as changes in processes or decisions usually require multiple approvals, slowing adaptability.

Self-Management

On the other hand, self-management by a team is a more contemporary approach, emphasising empowerment, autonomy, and decentralised decision-making. In self-managed teams, the members collaboratively make decisions, relying on the collective intelligence and expertise of the group. This method encourages innovation, as team members feel ownership of their work and are more invested in the outcomes. Communication in this system is more fluid, often horizontal, allowing for easier sharing of ideas and feedback. The underpinning belief here is that those closest to the work have the most relevant insights to guide it effectively. This approach promotes adaptability and responsiveness but requires trust, clear communication, and a culture that supports empowerment.

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