Transforming ‘Engineering Activity’ into a CORAM | HCLTech

Transforming ‘Engineering Activity’ into a CORAM

Transforming ‘Engineering Activity’ into a CORAM
July 26, 2022

Much has been written in recent years about industry 4.0, which refers to how businesses are increasingly leveraging digital technologies to improve their bottom lines and customer experiences. But what exactly does industry 4.0 imply for utility organizations? What is the appropriate level of effort for your organization to invest in digital transformation? How can you bring more customer focus within asset management operations with new digital technologies?

Inculcating Customer Oriented Risk based Asset Management (CORAM) approach in the Utility Industry.

For utility organizations, customer feedback and involvement play an integral part in improving serviceability especially as we all play a role in meeting decarbonization objectives- increased focus on energy efficiencies, demand side management, electrification, and more. With the increase in customer involvement in utility operations, it is important to assure these customers of reliable service. The utility's limited financial and personnel resources prevent it from pursuing all its projects, forcing CXOs to make difficult trade-offs based on near real-time data. To make an objective decision, it is critical to analyze the benefits provided per dollar of investment at the net present value of each project. Utilities, therefore, must implement a customer-centric risk management framework as a part of modern asset management to evaluate all potential benefits (risk reduction, energy efficiency gains, green energy capacity expansions, and increased customer satisfaction).

It is common for thousands of households across any region to be without utility services following a rare storm or flood that has devastated parts of the power grid and disrupted and damaged both businesses and homes. If the power was knocked out by strong winds and lightning, a utility organization must first act quickly. Again, if the storm has affected multiple counties, the utility organization has to call in crews from nearby towns to help with repairs, as well as other utilities in many cases. The utility company must coordinate between incoming requests, remote teams, and inventory repairs. This has a huge impact on customer satisfaction and experience.

In an industry that is largely asset intensive, all asset management related issues/problems are engineering problems. Depending on the maturity of the engineering operations and maintenance strategies within utilities, organizations may choose to take a different path to digitalization by adopting either an enterprise asset management approach or a customer-oriented risk-based asset management (CORAM) approach.


CORAM activates a decision-making process and provides insights for improving customer service performance through an asset investment strategy. It has an impact on utilities' operational behavior; transforming an 'engineering activity' into a 'customer oriented’ activity, resulting in a better customer experience.

The core idea is to maximize profitability by balancing risk, cost, and service performance with the assets or the personnel operating all those things. The concepts of risk of service failure, high asset performance, and investment can be found in various areas of the ISO 55000: 2014. To align with customer expectations, an organization must determine its level of risk tolerance and be able to define and comprehend the risk.


Even though assets are replaced and maintained to provide value to customers, the utility companies must be aware of the possibility of asset failure and its potential consequences. This effect could be seen, for example, in the degree of service failure, an organization's reputation, or its environmental stewardship.

The key to influencing decision-making is to predict asset failure and identify potential consequences. The likelihood of an asset failing, and the consequences of an asset failure are linked. If an asset fails, it cannot provide value to the consumer and may result in lower customer satisfaction, high repair costs, damage to the company's reputation, or even human casualties. As a result, the likelihood of an asset failing may be negative. This explains why organizations should redefine their maintenance strategies and shift from reliability-centered maintenance toward the calculation of asset failure predictions and risk aversion.

Risk management framework

Most utility investment decisions are often made in silos with historically determined spending limits. Most of the work is prioritized through a consensus or professional judgment. Any references to service standards or company objectives are made after the fact, are not perceived by the customer, and frequently do not correspond to the latter's goals. These plans are simply not adaptable enough to account for changes in investment requirements caused by changing customer expectations or decarbonization.

Risk managers will continue to use the risk-based asset management (RBAM) strategy throughout an asset's life cycle with the sole goal of minimizing risk to the value stream to which they are attached. Many RBAM competencies have not changed. Most risk managers use a risk-based approach to asset maintenance and operations, prioritize reliability efforts on critical equipment and failures that impact operations, incorporate RCM principles to reduce downtime, lower maintenance expenditures, and minimize the total cost of ownership.

Organizations, on the other hand, must monetize all risks by predicting asset failure, calculating the associated consequences, and attaching financials to the consequences. The monetized value of risk is the most objective form of risk weighting, particularly for investment planning.

Asset condition monitoring, however, has also changed and I discuss it in the next section.

It is common for risk engineers to lead efforts and improve performance using the plan-do-check-act (PDCA) methodology. We now can use data mining and modeling, as well as advanced analytics skills, to enhance asset health and perform:

  • Opportunity identification
  • Defective performance measurement
  • Proactive root cause analysis
  • Cost/benefit analysis of improvements

This will also allow the utility industry to transition to more sustainable solutions. These forces, when combined, will help to meet local, national, and global GHG emission targets.

Investment planning

The money invested (size), the type of consequences to be minimized (benefits), and the length of time (life) during which the benefits accumulate vary amongst asset performance management projects.  Hence, investment planning is one of the most difficult decisions in asset management.

We must employ a data-driven technique to compare the various projects/portfolios. Simple mathematical techniques like NORMALIZATION can be used to make all projects comparable by bringing them on an equal economic footing.

Using the NORMALIZATION technique, all these discrepancies are neutralized, and all projects and portfolios are put on an even playing field. This data-driven methodology demonstrates the robustness and transparency in the investment portfolio decision making process. This structure enables the organizations to resolve disputes over funds allocation between divisions efficiently.



CORAM via digitization is an available solution today generating rapid and impressive returns via the proper definition of maintenance priorities and sound decision enablement. This requires comprehensive industrial knowledge from the service provider including:

  • Asset management maturity assessment
  • Understanding of business operations
  • Understanding customer services and customer experience
  • Deep business domain knowledge of asset management
  • Business process analysis and process mining
  • Information flow, data analytics (AI & ML enabled), and model management
  • Industrial communications, digital sensors, and IT integration skills

Keep an eye out for my whitepaper, where I'll go into detail on how data from the system of records can be used to justify and monetize the portfolio risk to enable asset investment optimization.

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