With cyber attacks and threats continuing to escalate in tandem with geopolitical tensions, consequence-based cyber risk management has emerged as a vital mechanism for protecting critical infrastructure installations. In contrast with the risk management strategies that traditionally deal with probabilities of threats, this model prioritizes the possible consequences of cyber events to industrial control systems (ICS) and operational technology (OT) environments. Sectors like energy, manufacturing, and utilities are especially dependent on this transition since the effects of a cyberattack could be drastically severe, ranging from downtime of the operations to safety risks and environmental damage.
These critical infrastructures are now seeking to integrate consequence-based cyber risk management with their business goals. This means gaining an intimate familiarity with their operating priorities and the possible consequences of cyber attacks. By integrating this strategy into more comprehensive organizational risk management strategies, organizations can have confidence that their investments in cybersecurity are focused on safeguarding their most valuable assets and processes. IT and OT teams should have strong coordination in this achievement, as coordination enables technical security controls to be linked with operational resilience.
Nonetheless, the biggest challenge for applying consequence-based cyber risk management is the availability of holistic information regarding cyber events and their outcomes. Most companies struggle to gauge the probable damage of attacks based on inadequate historical data or broken-down information systems. This has led to increased adoption of analytics and threat intelligence technologies to enable organizations to simulate the ‘most likely’ outcome of cyber-attacks and predict probable situations. Even in the face of uncertainty, these resources empower organizations to make informed, data-driven decisions.
Assessing how effective consequence-based cyber risk management is in OT/ICS settings depends on main criteria including mean time to detect (MTD), mean time to respond (MTTR), and possible financial and operational consequences of events. Organizations can find weaknesses, assess the performance of their risk mitigation plans, and constantly refine their cybersecurity posture by monitoring these indicators.
By allowing real-time danger recognition, predictive analytics, and automatic response systems, artificial intelligence (AI) and machine learning (ML) are set to transform consequence-based cyber risk management. By enabling businesses to foresee potential outcomes and spot trends, these systems can help them address problems before they grow. Better accuracy and performance of consequence-based cyber risk management will increasingly depend on more mature AI and ML technologies.
The convergence of cyber risks and political tensions has provided industrial firms with a flawless chance. Targeting vital infrastructure is becoming more common among nation-state agents and cybercriminals, so companies need to implement a risk management strategy based on consequences. Industries can negotiate this complicated terrain and guarantee long-term resilience by concentrating on the possible effects of cyber threats and using newer technologies.
Finally, consequence-based cyber risk management is more than a cybersecurity approach; it is a commercial necessity for corporate success in an unsteady environment. Organizations can keep ahead of changing threats and guarantee their future by aligning consequence-based cyber risk management with operational objectives, surmounting data restrictions, and accepting AI-powered solutions.
Aligning consequence-based cyber risk management for industrial success
Industrial Cyber contacted experts to examine how a consequence-based cyber risk management strategy aligns with overall business objectives and existing risk management frameworks within industrial organizations. They also explore how these organizations can effectively balance proactive consequence management with reactive incident response. Additionally, the executives investigate how small to medium enterprises can successfully implement this approach.
Sarah Freeman, chief engineer for intelligence, modeling, and simulation at MITRE’s Cyber Infrastructure Protection Innovation Center, told Industrial Cyber that consequence-based cyber risk management strategies should dovetail with existing risk management approaches. “Put another way, a cyber risk mitigation program should exist as a dimension within other risk programs, not supersede it.”
She added that risk management programs should be framed against the critical functions or activities an organization must perform to succeed and, ideally, flourish. “There are multiple methods and approaches to identify potential risks to an organization. Regardless of which is used, organizations should validate that cyber-induced risks, whether by malicious actors or normal failures, are properly accounted for.”
“Regarding the balance between proactive versus reactive responses, in general, proactive activities represent a greater return on investment (ROI), in part because the cost of remediation can be so high,” Freeman said. “This follows the general axiom: ‘A one-dollar investment to manage a bug in the designing process will save $99 compared to managing a bug later in the implementation phase.’ Proving the proving ROI can be challenging, however. One interesting use case was demonstrated in the healthcare sector as organizations sought to implement additional security to protect patient medical records.”
Referencing a 2024 MITRE publication that evaluates various methods for measuring the advantages of Cyber-informed Engineering (CIE), Freeman illustrated with an example. In 2014, Kwon and Johnson observed similar trends within the healthcare sector, noting that the cost between proactive and reactive investment varied significantly (e.g., adoption of data protection methods for electronic medical records with average costs of proactive implementation (~$1.6M) versus following an incident (~$11.3M)). Additionally, Kwon and Johnson determined that the effectiveness of security solutions also faltered when adopting a reactive approach. They theorized that this may be a result of the fact that reactive security approaches may involve the adoption of ‘myopic bug chasing’ or overly focusing on ‘obsolete threats.’
“Some organizations can successfully leverage their existing risk management programs, asset management programs, and engineering quality review process,” Jeremy Smith, OT Engineer at West Yost Associates, told Industrial Cyber. “These programs can be augmented with consequence-based principles. However, it is more effective if CIE principles are adopted and governed by a parallel program. This is especially useful early in the adoption of CIE.”
Smith identified that critical mission validation and critical function identification is a necessary first step. “These address low-hanging fruit and provide long-term guidance on the path to CIE maturity. It is tempting to prioritize the 12 principles of CIE when adopting consequence-based risk management. While critical function may dictate early risk mitigation improvements, all principles should be regularly evaluated.”
He added that all organizations, especially small ones, must start with identifying their CIE team. This will identify gaps in skillset and staff availability. “Considering the 12 principles holistically will help plan for future staffing needs or outside assistance.”
Neelima Rustagi, vice president and general manager of ServiceNow technology workflow solutions, told Industrial Cyber that consequence-based risk management does more than align with business objectives–it’s an essential strategy for long-term resilience and productivity.
“With a clear picture of an incident’s potential impact on operations, businesses are in an ideal position to make the right investments in technology, services, and people to keep critical operations up and running,” Rustagi assessed. “A proactive, consequence-based risk management approach also provides built-in prioritization that makes incident response playbooks and workflows much more effective.”
Matt Morris, global managing director for 1898 & Co., the consulting arm of Burns & McDonnell, told Industrial Cyber that a consequence-based cyber risk management (CBCRM) strategy is about pinpointing and protecting the functions that drive your business. “By focusing on the potential impacts of cyber incidents on your most critical operations, CBCRM ensures that your cybersecurity measures directly bolster your business objectives and operational resilience. This approach works hand in hand with established frameworks like IEC 62443, NIST CSF, and Enterprise Risk Management (ERM) by shifting the focus from merely preventing breaches to understanding how disruptions affect operations (visibility, measurement, management & control, protection) and public trust.”
Morris noted that key elements include strategic alignment, balancing proactive and reactive measures, and SME implementation. “Assessing the consequences of incidents, such as disruptions in power grids, water treatment, or manufacturing, allows organizations to prioritize investments in controls that keep business running smoothly. Approaches such as Consequence-Driven, Cyber-Informed Engineering (CCE) map out system dependencies to inform risk prioritization,” he added.
“A winning strategy incorporates prevention and recovery. Proactive steps like vulnerability assessments, threat hunting, and continuous monitoring reduce the likelihood and impact of incidents,” according to Morris. “Organizations can quickly restore operations when incidents occur with robust incident response plans, disaster recovery strategies, and regular simulation exercises. This dual approach is essential, especially amid rising state-sponsored cyberattacks.”
He noted that small and medium enterprises can scale CBCRM by focusing on key operational processes, using simplified risk models, and leveraging external expertise or managed security services. “Integrating consequence assessments into existing risk management practices ensures that even with limited resources, the most critical assets receive the attention they deserve. Implementing a consequence-based cyber risk management strategy strengthens defense capabilities and enables swift recovery of vital business functions when incidents occur.”
Overcoming data limitations in consequence-based cyber risk management
The executives weigh in on how industrial organizations tackle data limitations or uncertainties when assessing potential consequences. They also examine whether there are specific industries where consequence-based risk management is more or less effective.
Freeman said that in general, the industrial security community believes the ‘established’ security sectors are more effective at evaluating potential consequences (e.g., the energy sector). “Although it is true that having a robust library of failure modes and effects analysis to draw from generally strengthens the process of identifying potential adverse outcomes, this also can stifle creative thinking as organizations seek to ensure the worst-case outcomes are addressed. This is particularly true in cases where robust engineering approaches result in invalidated trust or inappropriate confidence that the system is secure.”
She noted that organizations can minimize this inherent bias by ensuring that a variety of roles, job functions, and experience levels are accounted for in any activities that seek to brainstorm or identify worst-case outcomes.
“Every sector and organization can benefit from a consequence-centric review of their systems. Mitigation methods or other security approaches, however, may be more or less effective depending on the environment or technology being evaluated,” according to Freeman. “In some cases, an engineering-based, physical control may not be appropriate or effective. For example, it is unreasonable to dictate the control of wind generation plant on site as part of an effort to reduce the likelihood of remote manipulation. Instead, organizations must identify and acknowledge the risks associated with their daily operations, mitigate them as much as they are able to, and accept the associated risks.”
Speaking from the water industry perspective, Smith said that the people closest to the critical function of the organization have the information. “These are operations staff, maintenance, and their first level of management. Without regular hands-on and eyes on their facilities, organizations have an information gap. Regularly assembling the right mix of management, engineering, and O&M staff is a powerful tool for addressing consequence-based risk.”
“To overcome data limitations, organizations can combine diverse data sources, historical incident records, threat intelligence feeds, industry benchmarks, and expert insights, to build a well-rounded picture,” Morris detailed. “Scenario analysis and qualitative assessments help fill in gaps when quantitative data is sparse. Engaging cross-functional teams for continuous feedback ensures these models evolve with real-world insights.”
He added that industries with mature reporting systems, like utilities, healthcare, and transportation, tend to have more reliable data, making CBCRM particularly effective. “In contrast, sectors still embracing digital transformation might face more uncertainties, yet focusing on their most critical functions can still yield meaningful risk assessments.”
Rustagi identified that the most effective way for industrial organizations to address data limitations and uncertainties is by integrating data sources across the enterprise. “For example, a manufacturing execution system may lack information on the cost of replacing a specific asset, while an asset management system might not capture the production impact if that asset goes offline.”
“By integrating these systems within a risk management model, organizations can gain a more comprehensive and accurate understanding of the real consequences of an incident,” she added. “This holistic approach enhances decision-making and reduces uncertainty when evaluating potential risks. The power and energy sectors were early leaders in adopting consequence-based risk management, but we’re seeing broad adoption across the manufacturing, transportation, and life sciences sectors today.”
Detecting key metrics for evaluating risk management in OT/ICS environments
The executives assess which metrics or KPIs are most effective for evaluating the performance of consequence-based cyber risk management initiatives in OT/ICS environments.
Freeman said that the most effective metrics are those that are defined in quantifiable values. “The previously mentioned MITRE report includes several potential metrics that could be used to measure security maturity and growth over time. It should be noted that there are no ‘perfect’ metrics; instead, organizations should adopt a collection of metrics to measure growth across a variety of security facets.”
“First, there should be governance-based metrics,” Smith detailed. “For example, each year how many staff, and how many touch points for each, supported the implementation, evaluation, or update of consequence-driven policies, standards, asset maintenance, or design documents. This includes identification and regular review of the critical mission and functions by all levels of staff. Second, annually evaluate the adoption maturity of each CIE principle. A gold standard of overall maturity is critical function verification via live testing.”
“Overall Equipment Effectiveness (OEE) is the true test of an organization’s risk management program,” Rustagi said. “When an industrial environment scores high on availability, productivity, and quality–the three components of OEE–it indicates that the organization has put the right measures in place to mitigate high-consequence risks, whether those are cyber threats or other threats that can produce similar results, like operator error, equipment misconfiguration, or mechanical failure.”
Morris listed effective KPIs include operational downtime and financial impact addressing economic consequences of disruptions; critical function uptime covering reliability of systems that keep operations going; lead time to replace (LTTR) dealing with how quickly critical parts or systems can be replaced should physical damage or disruption caused by cyber sabotage occur, and time to recovery (TTR) attending to how quickly systems bounce back post-incident.
He also enumerated mean time between incidents (MTBI) covering the frequency of high-impact events; risk reduction scores that measure improvements pre- and post-mitigation; vulnerability remediation rate dealing with the speed at which known vulnerabilities are addressed; and compliance and audit results addressing adherence to industry and regulatory standards.
“These metrics are essential for understanding performance. One especially important metric—but often overlooked by many cyber teams—is the lead time to replacement (LTTR),” Morris added. “Our experience with critical infrastructure entities where failure is not an option shows that LTTR is necessary. It also encourages the cyber team to work closely with the engineering and operations teams to track it effectively, which enhances IT-OT integration and collaboration.”
Future of consequence-based risk management with AI, ML technologies
As AI and ML technologies continue to advance, executives examine their impact on the implementation of consequence-based cyber risk management strategies within industrial organizations.
“AI/ML, generative AI, and neural networks are still in their infancy, particularly within the industrial security community. As such, it is too soon to identify the myriad of ways these elements can be used to address risk management within an organization,” Freeman identified. “However, I believe the greatest value of these systems to the risk identification and mitigation effort will stem from their utility to check our internal and organizational assumptions with regard to our existing security and mitigation programs.”
She added that these technologies can be implemented to evaluate the blind spots in security programs or where estimates may be insufficient to calculate impacts following disruptive cyber events.
Smith recognized that AI increases the risk of technology being leveraged maliciously but has limited ability to affect consequences. Focus on consequences helps mitigate the impact regardless of the source of the threat.
“AI impacts owners and adversaries use of open-source intelligence (OSINT),” he added. “From the attacker’s perspective, it makes research and exploits more accessible. Owners must do more than limiting the release of technical design details and equipment specifications. Leveraging CIE Principle 11 (Engineering Information Control) owners should adopt organizational controls and education to avoid feeding sensitive information to public models via AI prompts.”
“AI- and ML-based technologies for behavior analytics and anomaly detection are already well-established, but a much wider range of risk management capabilities has emerged with the advent of AI agents,” according to Rustagi. “AI agents are ideal for gathering data from disparate sources, analyzing large datasets, and other tasks that can be burdensome and time-consuming for security and risk management teams. There has been a rapid adoption of AI agents and AI-based solutions in this space because the technology is so good at removing obstacles that get in the way of accurate risk assessment and effective risk management.”
Morris said that AI/ML revolutionizes CBCRM by enhancing predictive analytics, real-time anomaly detection, and automated incident response. “These technologies improve the accuracy of simulations and scenario planning, enabling organizations to prioritize risks better and allocate resources effectively. While AI/ML tools boost capabilities, they also call for robust governance to ensure data quality and reliability.”
Risk management at crossroads: Geopolitics, cyber threats, and beyond
The executives moved on to the effects of the current geopolitical tensions and emerging global cyber threats that influence the future development of consequence-based cyber risk management approaches, particularly in the context of OT/ICS environments.
Freeman noted that if risk identification and reduction programs are properly managed, they should be resilient to both geopolitical tensions and emerging global threats.
“The water industry finds itself in the middle of geopolitical tension as a part of critical infrastructure. We have much more well-resourced adversaries than 15 years ago,” Smith mentioned. “Organizations are ramping up their adoption of CIE into their risk management process. Adoption starts with executive visioning and prioritization around critical mission and early wins. In practical terms for OT systems, this is the development of new consequence-based standards ahead of major capital projects and augmenting existing internal quality review processes with cyber-informed principles.”
Morris identified that rising geopolitical tensions and state-sponsored cyberattacks drive organizations to adopt more comprehensive and dynamic risk management approaches. “Integrating real-time threat intelligence, enhancing scenario planning, and bolstering public-private collaboration is becoming key. Regulatory shifts and increased investment in advanced technologies will likely push consequence-based strategies to evolve further, ensuring resilience in critical OT/ICS environments.”
Regulatory influence on consequence-based cyber risk management
The executives address the current role of regulators and policymakers in shaping consequence-based cyber risk management practices and explore how their influence might evolve in the future.
“Regulators and policymakers play a key role in ensuring that security programs are incentivized effectively without relying on traditional market forces. This is particularly important as organizations seek to identify and reduce the risk that results from reliance on third-party suppliers or service providers,” Freeman said. “Traditionally, these organizations would exist outside of an organization’s risk mitigation program as there are limited opportunities to influence their security practices. Regulators and policymakers can ensure that third-party suppliers or service providers remain invested in the security process by holding them accountable in the event of an incident or adverse cyber activity.”
Smith noted that today, agencies provide or reinforce advisory-level guidance. “This indicates the best practices and policies with some documentation requirements. Following the pattern of government advisories, these recommendations will become additional procedural requirements followed by actionable/enforceable standards.”
“For the water sector, the evolution of the cyber risk and resilience assessment (Cyber RRA) portion of the America’s Water Infrastructure Act (AWIA 2018) is already following this pattern,” Smith added. “Very recently, the EPA started following up on Cyber RRA responses asking how water utilities are improving their adoption of risk mitigation controls. These onsite EPA visits are happening while organizations are preparing to file their required update as part of the regular 5-year AWIA cycle.”
Morris said that regulators and policymakers set essential standards and guidelines—such as those from FERC/NERC, CISA, and NIST—that ensure organizations conduct thorough risk assessments and maintain robust response plans. “They foster public-private partnerships and drive compliance through detailed reporting requirements. Looking ahead, we can expect tighter oversight, global harmonization of standards, and incentives for cybersecurity investments, which will further integrate consequence-based approaches into everyday practices,” he concluded.
