1. Size the “Problem”

The first step is to develop a cash flow model that underpins the business case and sizes the “problem” (aka financial need). Economic evaluation is NPV‐based (discounted cash flow) and tested over a range of conditions that represent the relevant range for each of the key inputs and assumptions. Cash‐flow modeling should also distinguish between operations funding and capital financing to evaluate the overall size and profile of the financing need.

• Funding pays for operating costs and generally needs to be funded from operations. From an accounting perspective, funding is an income statement item, not a balance sheet item. Cash from operations, liquid assets, subsidies, and short‐term borrowings are the most common infrastructure funding sources.
• Financing pays for capital assets such as plant, property, and equipment and may involve raising the money through private or public capital markets. From an accounting perspective, financing is a balance sheet item, and may be categorized as either debt or equity.

2. Types and Sources of Capital

Private‐sector capital markets have been a source of capital for energy‐related resources and infrastructure for years, by many different organizations, and through many different markets and vehicles (see Figure 7.2).

3. Capital Structure

Optimal capital structure (financial leverage, cash and liquidity, and shareholder distributions) is not only about finding the correct settings, but also about aligning the elements and the owner's agenda. Capital structure for energy and infrastructure tends to be governed by issues of ownership control and dilution, which put virtually all forms of debt at the top of the pecking order for sources of capital (see Table 7.1). Project cash flows dictate the debt capacity for a given credit rating, which is a reasonable proxy for requisite financial strength. Equity generally fills the remaining needs.

Debt is perhaps the simplest form of financing, and it avoids diluting the ownership interest of equity holders. Debt service can be a tax‐efficient use of operating cash flows (for taxable entities), which reduces the weighted average cost of capital (WACC) by substituting lower cost debt for more expensive equity. Financial leverage can also reduce agency costs through increased fiscal discipline. However, the optimal proportion of debt in the composition of a corporation's capital structure has steadily declined since most executives went through business school.⁴

More highly leveraged companies tend to have lower credit ratings. An optimal capital structure provides sufficient financial flexibility to support a value maximizing strategic agenda while providing an efficient cost of capital. Many companies reserve‐based lending and credit ratings requirements, especially the important thresholds for investment grade (BBB−) and A1/P1 commercial paper access (long‐term A rating), have been tightened in response to the financial crisis and that markets are smaller and less accessible for lower quality credits. Debt/EBITDA is one of the more universal leverage ratios across most industrial sectors, but its limitations include not accounting for prospects or non‐producing reserves, the effects of industry cyclicality and commodity price volatility, and anomalous tax or depreciation. Production‐based metrics also overlook growth in working capital, quality of earnings, and liquidity. Liquidity became a very important issue in the recent financial crisis. Beyond establishing the overall proportion of debt within the capital structure, we must address optimal cash and liquidity, and an optimization of the construct of the debt portfolio—liability management.⁵

4. Ownership Structure

In simple cases, such as a commercial bank loan or even a bond issue, there may be no changes to equity and no implications for ownership structure. However, in many other cases, deals may have implications for ownership structure and the operating model. Ownership structure can be more of a constraint than an optimizing function in the financial blueprint of an infrastructure project. Once the amount of equity is determined as a function of project size and debt capacity, the key is to determine the optimal compositions of each of both the debt and the equity. On the equity side, there are many available variants in the ownership structure, including the partial public offering of a stake, minority interests and passive private placements, joint ventures, and variations in public–private partnerships.

Joint ventures can be used to provide operations funding, equity financing, or organizational capabilities. With energy projects growing in scale, complexity, and risk, they are increasingly difficult to go alone. There has been a surge in collaborative deals to gain access, build capabilities, and share both capital and risk. NOCs are another aspect of the energy industry that drives the prevalence of collaboration for knowledge transfer and capabilities building.

Public–private partnerships (PPPs), increasingly important phenomena in the upstream oil and gas sector, are a unique joint venture construct that involves a public institution (e.g., NOCs) alongside private enterprise, with equity contributed by both the private and public sectors. One important element in the case for PPP is the transfer of expertise from private partner to public entity. To be attractive and viable, the shareholding structure of the JV must secure the interest of both the public and private partner—namely, providing enough public capital and sufficient private sector expertise.

As discussed in the last chapter, the public sector tends to operate less efficiently, whereas the private sector must use more expensive capital. Private sector savings can be due to more efficient project management and shorter construction times, as well as lower administrative expenses. However, private sector capital can be several hundred basis points higher than the public sector.

An optimal capital structure is achieved with both public and private parties as shareholders—different knowledge transfer schemes determine the optimal shareholding mix. For example, the higher financing cost of the private sector may be offset by savings in outlays.⁶

5. Operating Model

The final design element is the operating model, to ensure adequate monitoring and management.

Comingling of Sourcing, Sales, Trading, and Hedging

The organizational capabilities required for best practice sourcing, hedging and trading, and financing are increasingly blurred. But for many energy and chemicals companies, functional silos get in the way. Best practice requires the capabilities and coordination of purchasing, treasury, sales, and operations departments.

For example, there are ways to shift or share this risk with suppliers through alternative forms of contracted price agreements. This involves the procurement or manufacturing organizations. Alternatively, there are ways to manage this risk through physical or financial hedging—this involves the procurement and often treasury organizations. There are also ways to shift or share this risk with customers through product pricing. However, any impact on delivered volumes represents de facto exposures if volumes suffer from “hedged” prices. This degree of freedom involves the sales and marketing organizations. Finally, the company may elect to self‐insure and opt to do nothing to manage the risk, but capitalize itself appropriately for the level of risk that is to be absorbed. This ultimately involves the corporate treasury, which must ensure adequate capitalization for the anticipated level of risk.

There is increasingly a need to leverage capabilities, and ensure coordination across sourcing, production, marketing and sales, (potentially trading) treasury, and HQ. Expansion of the typical strategic sourcing agenda, beyond vendor management, incorporates elements of strategic risk management, including operations, contract redesign, and physical and financial hedging.

Strategic Risk Management

Overcoming the typical pitfalls requires a more rigorous and complete perspective of the issues and degrees of freedom, as well as leveraging capabilities and coordinating execution seamlessly across the organization. Figure 7.4 illustrates the progression of decision points to address in strategic risk management, beginning with “what risks to own,” and continues through to how best to manage each exposure.⁸

Risk Strategy (What Risks to Own)

Net economic exposures are typically a combination of both sales and spend, depending on the business. Better candidates for centralized sourcing are those with less category differentiation and greater scale benefits; in recent years, strategic sourcing initiatives have driven waves of centralization, standardization, demand management, and discounts. Strategic sourcing brings an increased focus on understanding the supply markets and cost‐to‐serve as part of fair return sourcing. However, considerable opportunity remains to understand net economic exposures and to establish priorities, tools, and guidelines to optimize risk–return trade‐offs with effective use of risk mitigation mechanisms.

The first step involves making active design choices around what risks to own and what risks not to own (i.e., shift, hedge, share, pass through), based on strategy, capabilities, and relative advantage (see Figure 7.5). Both the competitive and economic context will influence choices between doing nothing, physical or financial hedging, and even trading.⁹

For example, many companies with large fleets (e.g., airlines) consume vast quantities of fuel, and are thus naturally short (i.e., jet fuel in this case). However, this short position becomes a choice. In days when no airlines hedged, and the impact was small, it made sense to do nothing, and effectively “self‐insure” (i.e., bottom left quadrant) and capitalize accordingly (i.e., surplus cash and equity to buffer risk). As the impact got more material and the cost of self‐insuring too great, airlines would then pass along this exposure to customers in their product pricing (i.e., bottom right quadrant).

However, some airlines embraced both physical and financial fuel hedging as a source of competitive advantage to support aggressive pricing in select markets, making the top left quadrant more justifiable, in terms of competitive and economic position. Ultimately, we would not expect a progression to fuel trading for the airlines (i.e., top right quadrant) because fuel is more of an ingredient than it is a product, and they have no competitive advantage in market insight.

Risk Capacity (Metrics and Targets)

The second step is to establish relevant risk guidelines based on capacity to own risks, and to a lesser extent risk appetite, with specific hedging targets and benchmarks. This involves defining objectives, priorities, and constraints (e.g., enhance liquidity and debt capacity by reducing cash flow volatility).¹⁰ An enterprise's capacity for risk may be expressed in terms of its financial strength, for which credit rating is a common proxy.

Requisite financial strength, and the associated credit rating, is a corporate target that is often set with consideration to many factors, including external threats, competitive dynamics, vendor bargaining power, pricing pressure, and capital needs.

Once a target is set—for example, a moderate investment grade of BBB/Baa2—the company is loath to allow its position to deteriorate. Therefore, a useful capacity for risk is one‐half of a “notch” within the credit rating. We can translate this rule of thumb into a dollar‐size shock by triangulating within conventional credit metrics (e.g., one‐half a turn of EBITDA). We can also test capacity for risk from an equity perspective, by translating one‐half of a notch of credit capacity into earnings per share (eps@risk).

Objectives, Exposures, and Tactics

The third step in a design process is to identify and characterize a complete inventory of economic exposures—source, size, and drivers—and the exposures to be managed (see Figure 7.6). This involves defining, measuring, and analyzing all exposures (e.g., commodities, FX, interest rates), with special attention to aggregating, netting, natural offsets, and correlations. This includes determining the extent to which each exposure needs to be, and can be, managed, plus an evaluation of the spectrum of available tactics.

For example, take the case of a domestic manufacturer of industrial products. This company was growing in several emerging markets through both export and foreign direct investment despite the challenging headwinds of both commodity and currency price volatility. Despite vertical integration, they were largely unable to find ways to shift or share risk with suppliers through alternative forms of contracted price agreements. And in some cases, passing foreign exchange risk along to customers, via USD pricing, put contracted volumes at risk, simply creating a de facto exposure. This company designed a currency strategy to support overseas competitiveness in local emerging markets during the initial years of establishing a market presence by hedging net economic exposures with layers of both swaps and options.

Hedge Horizon, Hedge Ratio, and Instruments

The fourth step in the design process is where most companies that are new to hedging think they should begin. This involves numerous degrees of freedom, but is ultimately about the design of any physical or financial hedges that are required. This involves comparing the suitability of various hedging tools and determining how to incorporate these tools into a systematic program that will achieve stated goals, views, and risk preferences, for each exposure.

There are many potential hedging instruments, including swaps, forward contracts (outright forward, window forward, nondeliverable forward), options (plain‐vanilla, barrier/digital options), and zero‐cost structures (collar, participating forward, embedded premium option). Any assessment of the instruments goes beyond simple cost, and includes opportunity costs, risk profile, and so forth.

Swaps and forwards tend to be the most popular instruments for hedging currency, commodities, and interest rate exposures, largely because they do not carry an explicit fee. Surprisingly, it is still difficult today for managers to get approval to spend money to buy insurance. However, “free” insurance does not garner the same level of scrutiny, or require the same levels of approval (this is a common flaw in the design of enterprise operating models). And the cost of these hedge instruments is contained within the opportunity forgone of a symmetrical pay‐off profile, and the bid–ask spread. Similarly, for more sophisticated users willing to entertain options or structured products, collars and participating forwards tend to be the most popular. Again, these instruments carry no explicit cost because their cost is contained within the opportunity forgone of a symmetrical pay‐off profile, and the bid–ask spread.

Unfortunately, conventional wisdom can have disastrous consequences.¹¹ Symmetrical hedges are ill‐suited to longer‐dated hedge horizons and more volatile underlying assets, which increases the risk of the hedge going underwater (out‐of‐the‐money, or negative NPV). Underwater hedges can grow to represent extraordinarily large unrealized losses that must be disclosed for public reporting purposes. Typically, pressure will mount for these hedges to be unwound—often at exactly the wrong time—forcing recognition of the loss and eliminating the original protection of the hedge.

Notwithstanding, there is often too much focus on hedge instruments and not enough planning around the other design aspects. Hedging policy should include hedge horizon, hedge amounts, hedge ratios, use of layering (as a means to reduce cost and mitigate risk, illustrated in Figure 7.7), instruments, and authorities and control processes.¹²

Business Models for Trading

Trading business models require distinct organizational capabilities (and in some cases, positional assets) to confer a “right‐to‐play” and ultimately, “a right‐to‐win.” Three models represent pure‐play archetypes, but in practice, blended forms are more prevalent, drawing on: (1) asset‐based trading, (2) information‐based trading, and (3) services models.

Hedging and Trading Operating Model

The final design step is an appropriate risk management operating model, with consideration to organizational architecture, management processes, decision rights, information flows, and governance:

• Centralized decision rights to avoid double hedging, “wrong‐way hedging,” facilitate netting, and achieve economies of scale.
• Streamlined approval and control processes for timely and accurate reporting and appropriate treatment of “costless” symmetric versus asymmetric hedges.
• Risk‐adjusted scorecards and analytical engines; metrics incorporate returns on economic risks—such as risk‐adjusted return on capital (RAROC) and economic profit (EP). RAROC and EP measures are part of the standard toolkit for trading profitability analysis both on a “top‐down” strategic level and a “bottom‐up” transaction level.
• Potential conflicts with performance management systems and incentive programs to ensure alignment.
• An execution platform with the necessary information, analytical support, plus timely and efficient execution.

Performance Measurement in Trading

Risk‐adjusted scorecards and analytical engines play a key role in the successful implementation of risk management strategies. Performance measurement in trading is evolving to meet strategic needs, but most trading operations have built systems to monitor performance by counterparty, by segment, by security, and by professional. Performance measures must relate returns to their economic risks—such as risk‐adjusted return on capital (RAROC) and economic profit (EP). These measures require appropriate resolution of numerous complex performance measurement issues.