Risk management: 4 key strategies
Blog: The Enterprise Project - Enterprise Technology
Risk management: 4 key strategies
January 26, 2022 – 3:00am
Thanks to the pandemic, supply chain disruption, and labor shortages, today’s CEOs are focused on risk like never before. It could very well be surpassing growth and operating efficiency as the main issue that keeps them up at night.
But what exactly do we mean by risk? Risk can come in many different forms – from non-compliance to safety risk and operational risk. Failure to comply with FDA guidelines can put a company at risk of fines, penalties, and plant closures; product defects can irreparably damage a company’s reputation; inefficient workflows can pose hazards to workers, and employee error can result in faulty products.
Strategies for addressing specific types of risk
Effectively managing risk requires identifying and assessing it, building controls to reduce and mitigate its effects, and analyzing and auditing critical quality data to continuously improve it.
Consider the following four types of risk and how to thwart them.
1. Design risk
Identifying problems and product quality issues as early as possible can save costs on scrap, rework, or recalls. However, it can be difficult to identify risks early in the design process due to a lack of evidence and prior data.
[ For more on risk management, read Disaster preparedness: 3 key tactics for IT leaders. ]
One way to estimate risk is based on observing similar products, industries, and outcomes. Another way is to conduct a Failure Modes and Effects Analysis (FMEA), safety analysis mode, and Hazard Analysis and Critical Control Points mode (HACCP). These can provide the detailed and granular insights needed to mitigate design risks using strategic data connected to the design process.
2. Supply chain risk
It can be difficult for enterprises to manage supply chains outside their organizational ecosystems. Yet the fragility of today’s supply chain and the occurrence of supplier quality issues can pose severe risk. Faulty parts can endanger consumers and compromise production processes, and supply chain disruption can cause product delays that impact sales. For these reasons, suppliers must be treated as an extension of the company and its risk management initiatives.
Centralized quality management systems should support collaboration and enable data-sharing without compromising data privacy. Additionally, it’s important to have an adequate supplier qualification system to onboard suppliers and create ratings and other assessments to identify both short- and long-term risk factors using actual measurable and observable data.
3. Production risk
Though it’s better to identify quality issues in the design phase when less investment and damage has occurred, or in the supply chain to circumvent problems before ramp-up occurs, problems can happen during production and unknowingly be rolled out to customers. It’s important to use predictive analytics to identify non-conformances and potential outcomes and track these issues to develop a better idea of what could happen in the future.
This requires that you align quality control data from the shop floor with quality management processes to proactively take action to mitigate different levels of risk. This information also can be used for performing root cause analysis, corrective and preventative actions, and risk-based incoming inspections, which allow you to adjust processes according to defined and measurable risk.
4. Post-market risk
Ensuring continuous improvement is a critical way to ensure new risk doesn’t creep back into processes and products. Creating a dynamic feedback loop that connects complaints and customer feedback can better inform design, engineering, supply chain management, and production processes.
Customer-facing data should be fed into your quality management system (QMS) to create a more holistic picture of risk challenges and opportunities for mitigation. Focusing attention on post-market risk requires using market performance data to adjust risk controls and future processes and identify new and emerging hazards, as well as to help you determine new acceptable risk levels according to severity and occurrence rates.
Risk management is inherently a data-intensive endeavor, so it’s important to remove data silos and create a single source of truth connecting risk management activities and other business division activities across your organization’s footprint.
Risk matrices: A blueprint to effective risk management
When making important decisions impacting your company, you need a way to quantify risk to make the best choice and be able to explain that choice. A risk matrix lets you calculate and communicate risk for various situations.
A risk matrix identifies the likelihood of an event multiplied by its impact. The first step is breaking up probability and severity into numerical scales, and then plotting these scales to calculate risk in three zones: low, moderate, or high. A risk matrix, however, is a tool, not a solution. To be truly effective, it requires vetting the risk matrix against historical data and experienced managers on the other end interpreting the results.
Today’s business landscape is more complex than ever before. The pandemic, supply chain disruption, increasing regulations, labor shortages, and growing complexity of products increase the likelihood of corporate risk. Yet risk management as a dynamic, cross-functional, multi-disciplinary process can take the fear out of the unknown and help companies sidestep potential problems – or at least minimize their consequences.
[ How do containers and Kubernetes help manage risk? Read also: A layered approach to container and Kubernetes security. ]