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Risk Analytics

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47 November 2016 www.InfralinePlus.com Expert Speak Majority of the oil & gas enterprises implement ERM (Enterprise Risk Management) as a compliance requirement. It means they will develop risk registers and governance framework but lacks a robust day to day monitoring and integrated reporting and alerts framework. The ultimate objective of any ERM framework is to mitigate risk before it happens, avoid black swans and identify some of the uncontrollable risks, monitor them on day to day basis and implement ERM as a decision support system. The root cause analysis reports of some the recent disasters in oil industry also point towards this by stating that risk control failure is one of the primary reasons. Risk Management has to be integrated in day to day business activities of a company. Its ultimate objective is to maximize shareholder’s value. Based on some secondary research it can be said that - Over 80% use industry trends and peer analysis to identify risks - Over 80% values importance of internal audit reports - Over 70% think key risk indices and performance indicators are same - Over 80% believes there is a lack of integration is the key issue - Nearly 40% have some unstructured risk taxonomy in place - Over 90% did not have any enter- prise risk monitoring dashboards Board and CEO give utmost importance to the following factors: - Measure performance against the key risk indicators - Periodic mea- surement for appropri- ateness - Deviation from a risk per- formance plan - Periodical review of risk governance policy, controls, and mitigations - Evaluate changes in internal or external environment - Monitor risk progress report an variance following the policies - Periodic review of risk control framework robustness - Use structured scientific and ana- lytical tools As a result, following step-based approach needs to be considered in order to facilitate transition from an elementary risk control framework to a more robust one. 1. Build the Risk Taxonomy 2. Develop inter-relationships between various risk drivers across different risk domains like strategic, opera- tional, financial and legal 3. Develop key risk indices and control measures 4. Transform it into a decision support system using analytical engines Risk Taxonomy is an important stepping stone in the entire risk framework. It is not possible to build a high rise building on a weak foundation and same is true for a risk management program. A risk taxonomy outlines are risk categories, their drivers, key performance areas and risk indices across entire organization. Post taxonomy creation, it is important identify inter-relationships across risk sub-categories and drivers. There is no point in having a thousand risk indices when all of them are related to each other. All risk drivers which are related to each other should be part of same risk indices. At a board level it is not advisable to have more than ten risk indices at the maximum. Even tree methodologies were used to develop relationships between Oil & gas companies need to develop a risk analytics engine Neeraj Gupta, Director, iEnergy Innovations Pvt. Ltd., feels that oil and gas is a high-risk industry and hence requires timely risk mitigation to avert crisis. As a solution, he recommends that oil and gas companies should adopt a step-by-step approach to build a decision support enabled risk framework. Neeraj Gupta, Director, iEnergy Innovations Pvt. Ltd. Oil & gas com- panies should adopt a step-by-step approach to build a decision support enabled risk framework
Transcript
Page 1: Risk Analytics

47

November 2016www.InfralinePlus.com

ExpertSpeak

Majority of the oil & gas enterprises implement ERM (Enterprise Risk Management) as a compliance requirement. It means they will develop risk registers and governance framework but lacks a robust day to day monitoring and integrated reporting and alerts framework. The ultimate objective of any ERM framework is to mitigate risk before it happens, avoid black swans and identify some of the uncontrollable risks, monitor them on day to day basis and implement ERM as a decision support system. The root cause analysis reports of some the recent disasters in oil industry also point towards this by stating that risk control failure is one of the primary reasons. Risk Management has to be integrated in day to day business activities of a company. Its ultimate objective is to maximize shareholder’s value.

Based on some secondary research it can be said that - Over 80% use industry trends and

peer analysis to identify risks - Over 80% values importance of

internal audit reports - Over 70% think key risk indices

and performance indicators are same

- Over 80% believes there is a lack of integration is the key issue

- Nearly 40% have some unstructured risk taxonomy in place

- Over 90% did not have any enter-prise risk monitoring dashboardsBoard and CEO give utmost

importance to the following factors: - Measure performance against the

key risk indicators - Periodic mea-

surement for appropri-ateness

- Deviation from a risk per-formance plan

- Periodical review of risk governance policy, controls, and mitigations

- Evaluate changes in internal or external environment

- Monitor risk progress report an variance following the policies

- Periodic review of risk control framework robustness

- Use structured scientific and ana-lytical tools As a result, following step-based

approach needs to be considered in order to facilitate transition from an elementary risk control framework to a more robust one.1. Build the Risk Taxonomy2. Develop inter-relationships between

various risk drivers across different risk domains like strategic, opera-

tional, financial and legal3. Develop key risk indices and control measures4. Transform it into a decision support system using analytical enginesRisk Taxonomy is an important

stepping stone in the entire risk framework. It is not possible to build a high rise building on a weak foundation and same is true for a risk management program. A risk taxonomy outlines are risk categories, their drivers, key performance areas and risk indices across entire organization. Post taxonomy creation, it is important identify inter-relationships across risk sub-categories and drivers. There is no point in having a thousand risk indices when all of them are related to each other. All risk drivers which are related to each other should be part of same risk indices. At a board level it is not advisable to have more than ten risk indices at the maximum.

Even tree methodologies were used to develop relationships between

Oil & gas companies need to develop a risk analytics engine

Neeraj Gupta, Director, iEnergy Innovations Pvt. ltd., feels that oil and gas is a high-risk industry and hence requires timely risk mitigation to avert crisis. As a solution, he recommends that oil and gas companies should adopt a step-by-step approach to build a decision support enabled risk framework.

Neeraj Gupta, Director, iEnergy Innovations Pvt. ltd.Oil

& gas com-panies should

adopt a step-by-step approach to build a

decision support enabled risk framework

Page 2: Risk Analytics

48

ExpertSpeak

November 2016 www.InfralinePlus.com

triggers events of a particular risk, assigning a likelihood percentage based on number of similar events in the past (Fig 2.0). Even tree helped in prioritization of key risk indices as once you complete your analysis, one can easily find out the top five or ten indices that have relatively more chance of occurring and not necessarily based on past events but also on the existing processes as well.

It is recommended that oil & gas companies adopt a step-by-step approach to build a decision support enabled risk framework. - Develop a comprehensive tax-

onomy across four areas of risk i.e. strategic, operational, financial and compliance and map it across all the business units of an organization. It is the foundation of the entire risk framework.

- Explore inter-connectivity between various risk drivers identified in taxonomy to create a risk

It is recommended that oil & gas companies

adopt a step-by-step approach to build a decision

support enabled risk framework. There is a need to develop a comprehensive taxonomy across four areas of risk

i.e. strategic, operational, financial and compliance and map it across all the business units of an organization. It is the

foundation of the entire risk framework

Fig 1, Identifying risk Inter-relationships (Boleslaw et.al 2015)

Fig 2, Developing Risk event tree

Diagram (Fig 2.1) shows how key risk indices were prioritized and converted into a decision support system.

Fig 1, Identifying risk Inter-relationships (Boleslaw et.al 2015)

Page 3: Risk Analytics

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November 2016www.InfralinePlus.com

to assign weightages by looking at historical data or susceptibility of a business unit based on annual probabilistic analysis performed.

- Develop synergies with other existing data systems (ERP, SCADA etc.) to have one version of truth. These systems or other

historical data can be used to build analytical engines.

- Perform regular monitor of key risk indices. Frequency of monitoring may vary. E.g., for high risk field operations, all compliance data should be monitored on daily (or even hourly, if required). And a probabilistic consequence analysis should be performed. For other strategic decisions like bidding decisions, cost and schedule simulations can be used whenever required and a probabilistic estimate may be obtained using previous risk drivers or new compliance requirements.

connectivity map. It helps in identifying the common risk drivers affecting multiple risks to avoid duplication of monitoring efforts across multiple business units.

- Use existing key performance indices to derive key risk indices. Event tree should be used in order For suggestions email at [email protected]

Companies need to perform regular monitor of key risk indices. Frequency of monitoring

may vary. E.g., for high risk field operations, all compliance data should be monitored on daily

(or even hourly, if required). And a probabilistic consequence analysis should be performed. For other strategic decisions like bidding decisions,

cost and schedule simulations can be used whenever required

Fig 2.1, Decision Model for Risk Control Framework


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