<｜begin▁of▁sentence｜>### Instruction:
As a Supply Chain Manager, imagine you're evaluating the efficiency of communication across various departments in your company. These departments are represented as nodes in a network, with lines of communication between them visualized as edges. Now, consider we have a simplified model of this network where department 0 can communicate directly with departments 1, 2, and 3, and similarly, departments 1 and 2 have direct lines of communication with department 3. In terms of our relationship map, this would correspond to the edges [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3)].

Your task is to assess the average global efficiency of this communication network, a measure critical for understanding how swiftly and effectively information disperses throughout your company. Could you please calculate this average global efficiency, where it is defined as the mean inverse of the shortest communication paths between every pair of departments? Remember, this measure gives us an idea of network performance, helping us pinpoint where improvements in communication flow might be needed.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(0, 1), (0, 2), (0, 3), (1, 2), (1, 3)])

# Compute the average global efficiency
efficiency = nx.global_efficiency(G)

print('Average global efficiency:', round(efficiency, 12))
<|EOT|>
