PLANNING ABILITY
Please note that only candidates that came to Harambee after 24 October 2016 candidates completed the Planning Ability Assessment
About
​
The Planning Ability Assessment measures how candidates behave when faced with complex, multi-step problems. It assesses whether candidates think ahead and consider the consequences of their current choices for further actions, or whether they only consider one step at a time.
Planning ability is a crucial skill in a modern work environment, particularly in situations when workers need to act under limited supervision. Furthermore, high planning ability has been shown to predict retention rates at firms in the USA, even when other factors, such as IQ, are taken into account (Burks et al. 2009).
​
The Planning Ability Test is based on a test developed by Gneezy et al. (2010) and was adapted to the context of South African job seekers.
More Information
-
Burks, S. V, Carpenter, J. P., Goette, L., & Rustichini, A. (2009). Cognitive skills affect economic preferences, strategic behavior, and job attachment. Proceedings of the National Academy of Sciences, 106(19), 7745–7750.
​​
-
Gneezy, U., Rustichini, A., & Vostroknutov, A. (2010). Experience and insight in the Race game. Journal of Economic Behavior and Organization, 75(2), 144–155.
Example
​
Candidates had to play three rounds of the so-called “Hit15” game against a computer.
A candidate and a computer take turns putting stones into a basket on the screen. For each turn they choose to add either 1, 2, or 3 stones to the basket.
​
The player that adds the 15th stone wins the round. The starting number of stones in the basket changes with each round, so candidates have to prove their planning ability in different situations.
​
For example, consider the case where there are 10 stones in the basket at the start of the game. The candidate moves first, and puts two additional stones in the basket. That leads to a total of 12 stones. The computer then moves and adds three stones, which leads to a total of 15 stones. The computer wins the round.
This happened because the candidate did not anticipate the computer’s next move in their own decision.
​
Candidates are evaluated based on the number of rounds they win and based on the time they take to beat the computer in each round they won.