The demand for online shopping has grown tremendously in the last couple of years. Picnic, a major player in the online grocery industry, is struggling to achieve long-term growth within its current operations. Scheduling and planning are key drivers for maintaining operational efficiency. The Fulfilment Centre (FC) and Distribution Centre (DC) costs heavily depend on efficient operations. This research focuses on improving the scheduling process in an e-grocery FC and DC. The main objective of the model is to maximise the quality of the schedule, which is achieved through two lexicographical objectives. First, the make span is minimised to improve efficiency and to calculate the number of employees required to fulfil the workload. The make span of a schedule is defined as the time between the first scheduled activity i and the last activity j in a schedule s. Next, the number of switches between activities is reduced. The second objective is to increase overall productivity since switching moments cause slack in the operations. Two solution methods are proposed to solve the Flexible Resource Constrained Project Scheduling Problem (FRCPSP). The first solution method is a Mixed Integer Linear Programming (MILP) formulation that is solved with a Branch & Cut (B&C) algorithm. Next, a meta-heuristic is proposed named Variable Neighbourhood Search (VNS). The initial solution is computed by solving the MILP for one objective, minimising the make span. Next, the VNS uses nested neighbourhoods to modify the answer resulting in fewer switches per schedule. For small instances, the exact formulation outperforms the meta-heuristic in most cases. Conversely, the meta- heuristic features a higher efficacy and efficiency when tackling more significant instances, being the only solution method capable of yielding feasible solutions for real-world scheduling problems. Despite the effectiveness of the proposed meta-heuristic, some operational adjustments are still required before implementing the proposed decision-making tool.