The Industrial Internet of Things (IIoT) has attracted considerable attention recently due to its potential application in factory automation e.g., of manufacturing or production systems. As most manufacturing operations can be modeled by discrete event systems (DESs), how to monitor a DES remotely and in a timely manner through sensors and communication links needs investigation in IIoT. In this paper, we present a lossless data compression method for real-time monitoring of DESs. In particular, we find that timing side information (TSI) is available in delay-constrained communications. Based on the TSI, the data rate required to describe a DES can be substantially reduced. To this end, we derive the minimum data rate of a DES as a conditional entropy from an information-theoretic perspective. Low complexity compression algorithms are also developed. Both analytical and numerical results demonstrate the TSI-enabled compression gain in three typical scenarios.