A Higher Form of Asset Intelligence.
The Crucial Role of Problem-Solving in Managing Reliability in Asset-Intensive Organizations
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In the realm of asset-intensive industries, where equipment and machinery are pivotal to operations, ensuring reliability with minimum cost is paramount. At the heart of Managing Reliability lies a fundamental aspect: problem-solving. This critical element is something that everyone does every day in their work. Problem-solving is not merely about fixing issues as they arise. Rather, it encompasses a proactive approach to identify, analyze, and address potential problems before they escalate and are detected as functional failures. The organization’s capability to solve problems accurately and within the business context is a key to reliable performance. Failure to understand the cause of a failure inevitably leads to more failures and losses.

One of the primary challenges in asset-intensive organizations is the sheer complexity, interconnectedness, and dependencies of systems. A breakdown in one component can have cascading effects, leading to downtime, increased maintenance costs, and compromised safety. Effective problem-solving acts as a pre-emptive measure against such scenarios, fostering a culture of continuous improvement and operational resilience.

A robust problem-solving framework involves several key stages and steps. It begins with identifying the problem and defining the problem statement. Once the problem statement is defined, prioritize and decide to work on the problem. The next step is thorough analysis, which  involves collecting and analyzing data that aids in understanding the root cause of the problem. Based on the data analysis, solutions to mitigate the problem will be developed, and these solutions will be tested against the defined problem statement. Once testing is done, the implementation of the solutions comes next. To close the loop on an enterprise-wide level, monitor and validate performance improvement to close out the problem and share the learnings.

This figure above shows the Problem-Solving methodology cycle

 1. Identification – Operations, Maintenance, Threat Identification, and Safety Critical can help with problem identification.

2. Definition – What is the actual expected impact can help define the problem.

3. Prioritization & Decision – Quantify the risk and prioritize the problems to decide which problem needs to be addressed first.

4. Understand the Problem – Collect and analyze the data for the next phase. Also, understand the cause of the problem through causal reasoning and causal Learning. Perform FMEA and Value Stream mapping.

5. Solution Development – Develop solutions to mitigate the problem. This can be in the form of projects, Management of Change requests (MOC), Engineering Designs, Technical Expertise, and Standards development.

6. Solution Implementation – Test the solutions against the problem statement and implement the solutions. Implementation involves planning, scheduling, and execution.

7. Validate and Close – Monitor and validate the expected performance and improvement. Close out the problem and share what you learned within and outside the community for greater benefits and reliability excellence.


Techniques of Problem-Solving


1. Reliability Data Analysis – There is a list of core techniques, both qualitative and quantitative, available to support problem-solving. In terms of data analysis, the set of tools such as Pareto Analysis, Weibull Analysis, Crow-AMSAA, Fault Tree Analysis, Life  Cycle Cost Analysis (LCCA), and RAMS modeling are quite useful to process collected data and provide actionable insights.

2. FMEA – Apply this technique to identify all possible Failure Modes (FM), ways in which something might fail, in a design, a manufacturing or assembly process, or a product or service. This can be applied at the component, equipment, functional systems, and unit or asset level.

3. Value Stream Mapping – This technique or management method helps visualize the end-to-end business process and identify interfaces, resources, the flow of information, and the time consumed. It also helps to identify opportunities for improvement process times to improve productivity and efficiency. This aids in the identification of opportunities for improvement, including bottlenecks, rework, load-levelling, queue times, reliability, yields, and processing times to improve productivity and efficiency.

4. Causal Learning and Causal Reasoning – Causal Reasoning are the five WHY questions used in everyday problem-solving situations. Causal Learning provides a way to discover the causes of current performance, learn from the causes, and take action to improve future performance.


Expectations and contributions from multiple collaborative teams involved for Problem Solving


1. Reliability Department – Staffed with experienced personnel skilled in advanced reliability data analysis and problem-solving techniques. This data analysis by the reliability team aids the operations and maintenance team in investment decisions, risk mitigation, and bad actors improvement. It is expected that reliability engineers spend 70% of their time focusing on proactive and long-term activities.

2. Frontline Operations, Maintenance Staff, and Supervisors – This team encounters problems with the equipment before anyone else. It is expected they know the well-developed basic troubleshooting skills for their equipment and process scope and responsibility. Supervisors are expected to support and develop problem-solving skills continually and own the resolution of the problems frontline operations and maintenance staff encounter. Also, they should know how to access available staff resources to support the problems they encounter and be empowered to engage them when required during any phase of problem-solving. This team helps in day-to-day problem-solving.

3. Exclusive Problem-Solving Team – There is a sponsor for each team, with extended leadership team members  accountable for the team’s performance. The team can be physically or virtually located in the same area. The team is resilient and is not affected by past failures. Also, this team remains impartial, delivering unbiased results while maintaining respect for others in the organization. This team keeps other team members involved and updated on the progress. Communication with other teams is the key to success. This team understands the benefit of true collaboration and teamwork without underestimating the importance of meeting as a group regularly.

4. Operations and Maintenance Team – If the frontline operators need additional support to solve a problem, the multi-discipline is typically the next group to support the frontline team on the shop floor. Team members within this team can self-organize into the troubleshooting skills for their equipment and process. Team members are expected to have skilled technical expertise for operations and failure modes that can affect the equipment and process they operate and maintain. They know how to access and consult available subject matter expert resources to support team members on the problem they encounter and are empowered to engage SMEs as and when required.


Problem-solving is one of the key elements in managing reliability. It supports overall reliability management and operationalizing an Asset’s reliability strategy. Continuous improvement is the hallmark of effective reliability management, and problem-solving serves as the engine driving this improvement cycle. Organizations that prioritize problem-solving as a core competency empower their teams to tackle challenges head-on, foster a culture of innovation, and ultimately enhance operational reliability in asset-intensive environments.




In conclusion, problem-solving is not just a skill but a strategic imperative for managing reliability in asset-intensive organizations. By embracing a proactive problem-solving mindset, leveraging robust frameworks, fostering collaboration, and embracing innovative technologies, organizations can navigate the complexities of asset management with agility, resilience, and sustained success.

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