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Untitled Document

Mining for modern-day gold – risk management best practices for the oil and gas industry

By Ross Graham, Louis Caron and Louis Fabbi – RiskAdvisory (A Division of SAS)

Accounting rule changes, Sarbanes-Oxley and volatile energy commodity prices have forced oil and gas companies to seek better risk management programs. Now more than ever, assessing credit risks, quantifying cash-flow-at-risk and building "what-if" scenarios are increasingly important to the industry. Ignore them and suffer.

Embracing this new environment calls for continuously improving risk management programs, which in turn will provide senior executives with the enhanced analytical insights they need to provide shareholder value and manage earnings-per-share – mine for modern-day gold if you will – efficiently and effectively. Following are real-world examples of energy entities tackling the diverse challenges their industry faces through enhanced risk management.

Modernization through transformation

An old-line eastern US-based producer of oil, natural gas and electricity – with a major pipeline asset, large underground storage systems and millions of retail customers – transformed itself into a modern energy producer and service provider by employing more advanced risk management techniques.

The systems quantified variations in customer demand, power production, weather and energy costs to develop predictive models and "what-if" scenarios for untold numbers of events. Guided by this detailed information the company's senior management and traders could act upon knowledge-based decisions that limited their exposure and kept them within pre-defined risk boundaries. The information offered an additional advantage – giving them the awareness to exploit risk when the conditions were right.

But change was difficult initially. Data was being generated from more than one hundred different programs, generating unique outputs and confusing tags. The company integrated the data to build a foundation for effective risk analysis and accelerated analysis from two weeks to two days – or sometimes even hours and minutes – giving it competitive advantages. Now senior management looks at customized dashboard reports to view their entire risk profile and to scrutinize each business unit's contribution.

Measuring the future

International integrated super major oil and gas companies enter into long-term contracts with other companies every day. As a result, these companies must measure the credit risk they are exposed to and they also need to know the potential future exposures they may have if customers go bankrupt or become unable to pay bills.

In the case of one super major, it had no way of determining its potential future exposures to counterparties and was painstakingly reporting its basic credit positions manually. This was no way to run a multi-billion dollar business.

To address the situation, the company's chief risk and chief information officers approved and deployed a technology solution that provided a full range of advanced modeling techniques for accurately measuring and monitoring the known risk factors associated with energy assets and contracts. Because of the solution's flexibility, the super major was able to accurately model and assess credit risk in a framework unique to the organization's needs.

Surpassing management deadlines

A leading North American natural gas and integrated oilsands company needed speedy development of better risk management and business forecasting practices. In general the executives were responding to the fact that the oil and gas industry usually lagged behind the financial services industry in terms of its ability to analyze transactions for data that can generate "what-if" scenarios or credit analytics. But volatile energy commodity markets had created great uncertainties for production and hedging practices, not to mention revenue outcomes, and created the need for improved scenario planning.

The company had been using the industry-leading deal capture and reporting software solution for six years. The product provided physical and financial position reporting, as well as basic risk analytics for market and credit risk management. To create models for advanced analytics, they supplemented the trade capture system with additional software to provide an enhanced analytical view.

Three years later, the trade capture system continues to provide risk analytics as well as proactive, forward-looking models such as revenue-at-risk, cash flow analysis, credit risk analysis, and automatic daily value-at-risk calculations.

Analysis NOT collection

When an organization can see that its analysts are spending 80 percent of their time collecting data and weaving it together, something is wrong. They should be spending 80 percent of their time analyzing data.

In this case the organization was a governmental agency responsible for energy royalty revenue accounting and budget forecasting and it was attempting these functions using decentralized processes that weren't repeatable, auditable or secure. While the forecasting models could be readily found – in countless Excel spreadsheets – the results came together in untold numbers of calculation codes, with every cell having the potential to produce errors or corrupt outputs.

Realizing its predicament, the agency migrated its existing revenue forecast model to a business intelligence platform, providing it with the functionality needed to manage data, build analytical models, publish reports and conduct ad-hoc reporting quickly – all within a secure environment.

Marketer abandons spreadsheets

Canadian winters are known for the length of their biting cold, providing an eastern Canadian natural gas and electricity marketer with the right environment for acquiring new clients: greenhouse operators. Business was growing like wildfire but its customers were demanding enhanced energy services. Indeed, the marketer found that its spreadsheet-based IT infrastructure was being outpaced – exponentially – because of the rapid pace of its new member additions.

The solution? The marketer weaned itself from spreadsheets and adopted a comprehensive and sophisticated deal-capture system for every transaction detail. While energy transactions are notoriously complex, this installation provided monitoring for credit risks and real-time mark-to-market. At the end of the day, the new system provided the flexibility and expandability needed to keep up with the marketer's growing business.

Principles for risk management best practices

All companies – no matter whether they are oil and gas companies, government agencies, utility companies, or marketers – must advance along the learning curve in their efforts to improve and broaden their risk management capabilities. The biggest challenge in that effort continues to be consolidating massive amounts of data from hundreds of sources into one complete and flexible data warehouse that can be mined for modern-day gold – knowledge and fact-based forecasting beyond operational needs. Sadly, much of the available data is all too often confined to small teams that operate, for the most part, in isolation from the rest of the company. Valuable data which could be used to drive better decision-making gets buried – usually in spreadsheets – within these isolated management pockets, preventing transformation into a more innovative enterprise-wide risk management capability. Spreadsheets are tremendously flexible but inherently woeful in creating the best-practice business controls needed today.

Organizations that recognize the shortcomings of spreadsheets and a silo risk management approach, realize that there is a tremendous amount of potentially actionable data within their organization – if only they could consolidate it effectively.

As the marketer proved, deal capture solutions are a great start, but across a larger organization disparate data systems pose difficulties. Integrating data across different departments and business units has a human factor as well, creating business and political challenges that can interrupt implementation. Typically, the business challenges involve data or knowledge hoarding. A business unit may resist data sharing in an attempt to maintain degrees of power. Cooperation comes begrudgingly, if at all.

Politically, creating an integrated risk view allows firms to benchmark performance on a risk-adjusted basis. Alongside the non-data related issues, the data warehouse can be the easy part of the project!

In our experience, a significant majority of oil and gas companies are still consolidating the data from untold billions spent on information technology systems. Through that process, they are coming to see that they have at their fingertips a proverbial gold mine within their existing systems. But how can they use the consolidated data to propel the firm forward, moving further beyond operational management toward integration with more forward looking processes?

If integrated properly a company can become so data-friendly as to understand that a hurricane in the Gulf of Mexico or a mild winter in New England can affect energy prices nationwide, as can variations in customer demand, energy costs and power production. New technologies can construct predictive models and "what-if" scenarios to reveal the potential business effects of countless combinations of events like those. These scenarios allow senior management to devise business and risk strategies that mitigate financial risks and enable them to consider exploiting events for profit.

Oil and gas industry companies can adjust to this new environment and make the most of the untold billions they've already invested in IT. Taking the next step requires courage and conviction, but the rewards are there.

About RiskAdvisory (A Division of SAS)

RiskAdvisory offers comprehensive risk management software solutions that are reliable and easy to understand, giving clients the ability to achieve industry best practices with respect to deal capture, quantification and reporting of energy risk. Our Risk Solutions for the Energy Industry give oil and gas companies, energy hedge funds, financial institutions, energy marketers and utility companies a holistic view of data management risk analysis and risk reporting so that they can achieve comprehensive risk management throughout the enterprise.


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