What is risk management and why it is important?
Risk management is the process of identifying, assessing, and controlling risks for a business. These risks could stem from a wide variety of sources, including rising energy prices, trade disruptions, a pandemic, and inflation.
If an unforeseen event blindsides your business, it could sustain financial loss or, in the worst-case scenario, it could even close. To reduce risk, you need a consistent, systemic, and integrated approach to risk management that can help determine how best to identify, manage, and mitigate significant risks.
If a business focuses its attention on controlling and mitigating risk, it will protect itself from uncertainty, reduce costs and increase the likelihood of successful operation.
Predictive analytics for risk management
In risk management, it’s a common practice to use the predictive analytics technology based on historical data to analyze patterns and predict future outcomes. It forecasts what might happen and includes what-if scenarios and risk assessment.
To predict future outcomes, you can use simulation. With simulation, you can model the behavior of a system, upload historical data, and experiment with various scenarios of how the system will develop with time.
There are many business use cases of predictive modeling which include:
- Business Processes – for optimization, project management, investment analysis, impact analysis, and more.
- Manufacturing – to optimize production processes, improve maintenance scheduling, plan inventory, and more.
- Healthcare – in clinical trials, predictive scheduling systems, pharmaceutical market analysis, and more.
- Supply Chain – for design, planning, sourcing optimization, inventory management, transportation planning, and risk management.
Predictive modeling application areas in various industries
Every business is subject to risks – strategic, operational, financial, and more. These cannot be entirely avoided because they are hard to predict. However, there are many strategies that businesses implement to cut back on the negative impact. Simulation is a tool that helps identify potential risks and find ways to make your business resilient. Find out how:
Book: Simulation for complex project management →
White paper: Developing disruptive business strategies with PwC →
Case study: Investment planning to predict and reduce operational risks →
Article: Acquisition planning and risk management under uncertainty →
Plenty of manufacturing risks hinge on widespread trends and the global economic outlook. Equipment failure, cyber threats, third-party vendors, raw material price volatility — all these threats can be accounted for before they hit a business. Using simulation, a company can build a model of a manufacturing business, play out different scenarios, and find out how to avert potential dangers.
Case study: Avoiding equipment downtime →
Case study: Accounting for risks when opening a new facility →
Article: Controlling risk levels on processing equipment →
Article: Choosing a supplier in digital manufacturing under uncertainty →
White paper: Resolving complex material handling challenges with simulation →
Based on the size and complexity of an organization, healthcare businesses use a variety of tools to identify and evaluate risks and associated opportunities. Healthcare uses simulation, for example, to prevent and control the spread of infections, efficiently manage staff, detect medical equipment malfunction, and more.
At the start of the COVID-19 pandemic, many countries made different decisions regarding policies toward this new coronavirus. Some of these decisions were risky, but all of them impacted their countries in many different sectors, including the political and economic. A company evaluated vaccination policies for controlling the spread of COVID-19 →
Case study: Identify drug dosage for every patient and their response to the treatment →
Case study: Improving resource utilization and preventing potential risks →
Case study: Evaluating the medical and economic impact of introducing mobile stroke units →
Case study: Assessing new technologies and interventions in healthcare →
Sophisticated management practices (lean manufacturing, just-in-time inventory, and so on) together with globalization make supply chains more complex and interconnected, and consequently more vulnerable to disruption. Production downtimes, unfulfilled demand, lost revenues, and the loss of customers are among the consequences.
Companies struggle to make their supply chains resilient – to be both low risk and able to adapt quickly to disruption. To handle risk and disruption managers need to have complete visibility of the complex interdependencies in their supply chains. Optimization and simulation modeling are the techniques that can help managers successfully achieve this.
Case study: Eliminating bottlenecks and increasing supply chain resilience →
Case study: A digital twin to improve operations of a company affected by COVID-19 →
Case study: Planning a green hydrogen supply chain →
Case study: A supply chain simulation to decide on new distribution centers →
To sum up
Regardless of the industry, every business is subject to risks and disruption, especially these days as they recover from the pandemic and adapt to geopolitical shifts. The right way to deal with the potential danger to the company is for you, as a manager, analyst, or engineer, to predict the risks, analyze them, and prepare for them.
To do that, you can use simulation, predictive analytics, and/or machine learning, and AnyLogic will help you combine it all into one system. Take a look at case studies or register for the upcoming AnyLogic Conference 2022. See how other companies use AnyLogic to predict future outcomes and make their businesses more resilient to change.
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