Adaptive Project Management and Project Control

Adaptive Risk Management and Project Control

Let’s assume that you are involved in management of software development project. In addition to creating other project planning documents you identified risks and created risk management plan. It includes:

  • a risk register with risks and their properties
  • a risk management strategies for each risk
  • a risk mitigation and response plants
  • a risk adjusted project schedule

In other words, you performed all of the recommended steps to ensure that you properly manage risks in your project. Once the project started, something happens – a risk occurs. For example, a software developer left the team and you must manage this situation. There are different ways to manage this problem and it is unclear which solution will would work better. You can only try. For example, you can ask your other team members to cover the departed software developer’s duties, hire somebody new, or completely re-write the software code left by the software developer. Here is a main problem: you cannot select a best course of actions unless you try all scenarios and when you try everything it can be too late. This is a common dilemma and we believe the solution is the adaptive management process.

Here is how adaptive management works in general. You come up with a strategy, which supposes to solve a problem. This problem has a lot of uncertainties. For example, one of the areas where adaptive management is actively used is environmental management. What would be a fish stock in the particular area as a result of overfishing and climate change? Or what would happen with melting of the particular glacier. Then you generate a hypothesis. Based on this hypothesis you would create different models. It is important to know that you may need to apply multiple models, however some of them may not be suitable for the particular problem, and don’t need to be executed. After you execute selected models you monitor what actually happened and compare results with the model. For example, you monitor fish population or melting glacier during certain period of time. This information will prove or disprove your original hypothesis. You may need to create new models. Then next step is evaluation of your strategy. For example, your strategy to maintain healthy fish stock would be to limit a season of fishing. But it may not work because fish stock may go down faster than expected. In this case based on adaptive learning, you would need to change strategy, update hypothesis, create new model and repeat the process. For example, you may recommend shutting down fishing in the area altogether for certain period of time and continue to monitor the situation.
In many areas adaptive management is a formalized process: each step of the process is reviewed and documented, models are well defined, results of monitoring are recorded, but most importantly, decisions related to strategy and hypothesis are clearly defined and approved. This formalization is very important, because the impacts of decisions can be very costly.

Adaptive Project Management

The point of all of this is that we want to be able to apply this adaptive process to the management of project risks. There is how you can apply adaptive management to project risk management:

  1. Define a strategy: strategy is a combination all risk management strategies for multiple risks in the projects. Risks can be avoided, mitigated, transferred, or accepted. You would need to create appropriate risk mitigation and response plans.
  2. Generate hypothesis. Here is one of the main differences between the traditional approach and adaptive management. You must generate multiple hypotheses at the same time and document them. In case of project management, this requires multiple risk mitigation and response plans for the same risks. Even it seems to be a time consuming exercise, it may save a lot of time and money in the long run.
  3. Create models and evaluate them. You would need to perform project risk analysis with multiple sets of risk mitigation and response plans. After this step, you will decide what plan worth execution. This selection can be based on an assessment of cost and duration of each model, which are essentially different project scenarios.
  4. Execute one or more models. Here is another difference between adaptive management and the traditional process. You may want to execute multiple mitigation or response plans at the same time and see which performs better.  For example, you may hire somebody to work with code developed by departed developer and at the same time develop new code.
  5. Perform project control and validate your hypothesis. Another important component of adaptive management is the control and evaluation during the execution of risk mitigation and response plans at each phase of the project. As part of project control, schedule risk analysis needs to be performed for all mitigation and response plans.
  6. Final evaluation of risk management strategy. This is done at major project milestones. At these junctures, you must determine if the overall risk management strategy is working. After this you may update your risk register including risk properties and perform schedule risk analysis.

Adaptive risk management is much broader concept than just updating probabilities and impacts, and other properties of the risks when project progresses. It includes generation of multiple hypotheses, modelling and execution some of them, and performing project control to determine if hypotheses and overall strategies are correct.