Increasingly complex value chains and rising competition require firms to employ advanced planning mechanisms for efficient resource allocations aiming for an increase of their productivity level. Planning is frequently done by corporate entities based on performance analysis techniques such as the Data Envelopment Analysis (DEA). Within planning processes, total resource levels that should be allocated among processes are regularly defined ex-ante, giving rise to decision problems that go beyond basic efficiency analysis. We have developed a method allowing the allocation of an ex-ante defined resource level across various processes of an organization to ensure the achievement of overall productivity targets. We propose a mixed-integer/linear program (MILP) that incorporates a social welfare function, allowing decision makers to consider fairness aspects. The practicability of the method is demonstrated in a real-life case study of setting productivity targets to processes at a first-tier automotive supplier. The model-based allocation strategy is compared to alternative approaches, as well as the strategy applied by the organization in the past. The proposed approach is beneficial in two dimensions: Either fewer activities are required to reach the total productivity target, or a lower overall strain level among the activities in respect of their improvement efforts can be achieved.
- Data Envelopment Analysis
- Mixed-Integer/Linear Programming
- Resource Allocation
- Productivity Enhancement