Mitigating operational risks in manufacturing through data analytics

Risk management is crucial for any business. It is costly and time consuming to implement risk strategies. For manufacturing companies, risk management can help identify, assess, and mitigate potential threats to the organization’s objectives. Adopting data analytics in risk management can help bring down risks in business management. Risk management is evolving by using data analytics to gain real-time insights that help in risk-preventive policies, procedures and early identification.

Operational risks are increasingly complex to manage in the manufacturing industry. Manufacturing industries face countless risks including financial, operational, regulatory, security, legal and strategic. This can range from equipment failure to defective products, supply chain disruptions to currency and interest rates, commodity price fluctuations to legal regulatory changes and also changes in market dynamics due to industry environment. 

In the operational landscape, manufacturers face customers, employees, and operations. Innovation in manufacturing industry, be it in terms of new technologies or expanding markets, will bring in new opportunities but there is a potential risk factor. Risk management in manufacturing industry involves 3 critical steps.

1. Identification of risk: To use data analytics to mitigate risks, one should be aware of the risk profile. Identifying the risk, its sources, types, and levels that the business is facing and the impacts and consequences of those risk is very crucial. By understanding this, the focus can now be on efforts and resources that are critical risks for your business. In today’s scenario, using data analytics tools and techniques such as risk assessment, mapping and visualization to assess and prioritize your risks based on their severity is a huge time saver. Hence, this identification or assessment of risks should be based on data and analytics rather than mere speculations.