Thanks to the pandemic, supply chain disruptions and labor shortages, today’s CEOs are focusing on risk like never before. This could very well overtake growth and operational efficiency as the main issue keeping them up at night.
But what exactly do we mean by risk? Risk can take many different forms – from non-compliance to security risk and operational risk. Failure to follow FDA guidelines can expose a company to fines, penalties, and plant closures; product defects can irreparably damage a company’s reputation; inefficient workflows can pose risks to workers and employee error can lead to defective products.
Strategies for dealing with specific types of risk
Effectively managing risk requires identifying and assessing it, implementing controls to reduce and mitigate its effects, and analyzing and auditing critical quality data for continuous improvement.
Consider the following four types of risk and how to counter them.
1. Design risk
Identifying product quality problems and issues as early as possible can reduce disposal, rework or recall costs. 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 looking at similar products, industries, and outcomes. Another method is to perform a Failure Modes and Effects Analysis (FMEA), a Safety Analysis mode, and a Hazard and Critical Control Points Analysis (HACCP) mode. These can provide the detailed and granular information needed to mitigate design risk using strategic data related to the design process.
2. Supply chain risk
It can be difficult for companies to manage supply chains outside of their organizational ecosystems. Yet today’s fragile supply chain and emerging supplier quality issues can pose serious risks. Defective parts can endanger consumers and compromise production processes, and supply chain disruption can lead to product delays that impact sales. For these reasons, suppliers should be treated as an extension of the business and its risk management initiatives.
Centralized quality management systems should support collaboration and enable data sharing without compromising data confidentiality. Additionally, it is important to have a proper supplier qualification system in place to onboard suppliers and create ratings and other assessments to identify short and long term risk factors using measurable real data. and observable.
Suppliers should be treated as an extension of the business and its risk management initiatives.
3. Production risk
Although it is best to identify quality issues in the design phase when less investment and damage has occurred, or in the supply chain to work around issues before ramp-up, problems can occur during production and be unknowingly deployed to customers. It’s important to use predictive analytics to identify potential nonconformities and outcomes and track those issues to develop a better idea of what might happen in the future.
This requires you to align shop floor quality control data with quality management processes to take proactive steps to mitigate different levels of risk. This information can also be used to perform root cause analysis, corrective and preventive actions, and risk-based incoming inspections, allowing you to adjust processes based on defined and measurable risks.
4. Post-marketing risk
Ensuring continuous improvement is an essential way to ensure that new risks do not recur in processes and products. Creating a dynamic feedback loop that connects customer complaints and feedback can better inform design, engineering, supply chain management, and production processes.
Customer-facing data should feed into your quality management system (QMS) to create a more holistic picture of risk challenges and mitigation opportunities. Focusing on post-market risk requires using market performance data to adjust future risk controls and processes and identify new and emerging hazards, as well as to help you determine new levels of acceptable risk in based on severity and occurrence rates.
Risk management is inherently a data-intensive business, so it is important to break down data silos and create a single source of truth connecting risk management activities and other business division activities across the footprint of your organization.
Risk matrices: a model for effective risk management
When making important decisions that impact your business, you need a way to quantify the risks to make the best choice and be able to explain that choice. A risk matrix allows you to calculate and communicate risks for various situations.
A risk matrix identifies the probability of an event multiplied by its impact. The first step is to break down probability and severity into numerical scales, then plot those scales to calculate risk in three areas: low, moderate, or high. A risk matrix, however, is a tool, not a solution. To be truly effective, this requires checking the risk matrix against historical data and experienced managers on the other hand to interpret the results.
Today’s business landscape is more complex than ever. The pandemic, supply chain disruption, increased regulations, labor shortages and increasing product complexity increase the likelihood of business risk. Yet managing risk as a dynamic, cross-functional, multidisciplinary process can eliminate fear of the unknown and help companies avoid 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. ]