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In a large-scale empirical study of 65 new venture projects, Sommer et al (2009) showed that the best combination of learning and selectionism, as measured by their effect on  project success, depends on the level of unforeseeable uncertainty in the project and t  complexity of the project (Figure 1). When both uncertainty and complexity are low  (lower left quadrant), planning and standard risk management are up to the task and t  most efficient. When unforeseeable uncertainty looms large, be flexible and apply trial  and error. When complexity is high, use parallel trials and narrow the field down to t best as soon as possible. The hardest situation is in the upper right quadrant, which  ne  ne  he is  where megaprojects usually find themselves and where unforeseeable uncertainty and project complexity combine. It turned out that the highest success level was associated with parallel trials if they could be kept alive until uncertainty had been reduced to the point that all important risks were known. Otherwise, trial and error performed better. Of course, in any large project, trial and error and selectionism can be combined and  applied differently across sub-projects.

Figure 1 In a large-scale empirical study of 65 new venture projects, Sommer et al (2009) showed that the best combination of learning and selectionism, as measured by their effect on project success, depends on the level of unforeseeable uncertainty in the project and t complexity of the project (Figure 1). When both uncertainty and complexity are low (lower left quadrant), planning and standard risk management are up to the task and t most efficient. When unforeseeable uncertainty looms large, be flexible and apply trial and error. When complexity is high, use parallel trials and narrow the field down to t best as soon as possible. The hardest situation is in the upper right quadrant, which ne ne he is where megaprojects usually find themselves and where unforeseeable uncertainty and project complexity combine. It turned out that the highest success level was associated with parallel trials if they could be kept alive until uncertainty had been reduced to the point that all important risks were known. Otherwise, trial and error performed better. Of course, in any large project, trial and error and selectionism can be combined and applied differently across sub-projects.