Formula
score = (x) -> if x == "Yes" 10 else 0 redistributed_weights = (weights, values) -> num_of_weighted_values = weights.length for value, index in values if value == "Not Applicable" num_of_weighted_values -= 1 redistributed_weight_value = weights[index] for weight, i in weights if weight == 0 continue weights[i] = weight + redistributed_weight_value/num_of_weighted_values weights[index] = 0 weights weights = [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1] ecosystem_conversion = [commitment, evidence, time_bound_targets, high_risk_commodities, sourcing_disclosure, coversion_free_supply_chain, minimization_commitment, minimization_evidence, minimization_system_disclosure, minimization_targets_disclosure] redistributed_weights(weights, ecosystem_conversion) weights.reduce((weighted_sum, weight, index) -> weighted_sum + weight*score(ecosystem_conversion[index]) , 0)
World Benchmarking Alliance
commitment
2023
World Benchmarking Alliance
evidence
2023
World Benchmarking Alliance
time_bound_targets
2023
World Benchmarking Alliance
high_risk_commodities
2023
World Benchmarking Alliance
sourcing_disclosure
2023
World Benchmarking Alliance
coversion_free_supply_chain
2023
World Benchmarking Alliance
minimization_commitment
2023
World Benchmarking Alliance
minimization_evidence
2023
World Benchmarking Alliance
minimization_system_disclosure
2023
World Benchmarking Alliance
minimization_targets_disclosure
2023