INTERNAL BENCHMARKING CAN INCREASE REFINERY PROFITS

Kevin Waguespack
Arthur Andersen LLP
Houston

An internal benchmarking approach called margin opportunity analysis (MOA) is suggested to improve refinery planning and increase profitability.

The MOA is more meaningful than performance measures such as external benchmarking because it measures a refiner's actual performance vs. its own theoretical best performance under prevailing market conditions, logistics, and refinery assets.

The inherent inaccuracies involved in using benchmarking normalization factors to allow consistent comparisons between competitors are avoided.

Making the MOA an institutionalized step in the refiner's ongoing tactical planning process can generate savings on the order of $0.50/bbl ($17 million/year per 100,000 b/d of capacity).

The MOA technique also can be applied to other continuous process industries, such as ethylene plant operations, with similar results.

BACKGROUND

The U.S. refining industry has undergone dramatic changes during the last 15 years, for reasons including: dwindling domestic oil supply, increasingly stringent environmental legislation that increases processing costs and limits the regions available for exploration and production of oil, removal of government incentives for small refiners, and quantum improvements in computer technology.

The net result of these concurrent developments is an industry that has significantly downsized, with a resulting shift in competitive edge toward bigger, more highly sophisticated plants.

Tactical planning is a critical support process in the refining industry and carries a large share of the burden of maximizing plant profitability. Use of identified best practices in tactical planning allows refiners to increase their bottom line without commensurate capital investment.

TACTICAL PLANNING

Key process steps for almost any manufacturer can be simplified into buy, make, and sell processes (Fig. 1 (80143 bytes)).

The planning process supports key operating decisions in the refinery, such as crude selection, process unit operation' and product slate determination.

The tactical planning process, above all other support processes, is critical to the economic success of the operation.

Tactical planning is defined as the short-term operational planning process that positions a company to take proactive measures in response to changing markets (crude and refined product supply, demand, and price) and plant resource availability (process unit capacities). The tactical planning process bridges the span between longer-term budgetary planning and implementation (Fig. 2 (59972 bytes)).

Because the planning process is considered a support process, it is rarely targeted for proper measurement and control. But proper assessment of a company's tactical planning process can point out weak links in the system that reduce profitability.

The planning process relies heavily on the use of large, linear program (LP) models to select feedstock, set operating targets, and dictate the most economic product slate, based on the prevailing market conditions forecast over the planning horizon.

It is important to note that the tactical planner concentrates solely on defining and controlling incremental economics. Utilizing the given assets most effectively once they are operating is the planner's objective.

Fixed costs are generally not a concern to the planner as these costs will be essentially the same, regardless of the type of crude purchased or the endpoint of the refinery's cracked gasoline.

As shown in Fig. 3 (77819 bytes), the planning process can be defined systemically by three key steps: plan development, plan implementation, and planning effectiveness measurement. A successful planning process cycles through these steps on a regular basis, relying on the people, technology, and work processes to increase the economic value of the operation.

PROGRESS REVIEW

There are two major reasons a refiner should review its tactical planning process:

Tactical planning is a critical support process ideally structured to foster continuous improvement. If the planning process does not promote and drive continuous profit improvement, other attempts at profit improvement may be less than optimal, delivering less overall value to the company than originally perceived.
For example, minimizing feedstock cost is not necessarily an appropriate target if current economics favor running a high-quality crude oil. Rather, maximizing net operating margin should be the main objective. It is the tactical planning process that is relied on to ensure optimization of resources.
Tactical planning underutilizes recent technological developments. The last 15 years have seen quantum improvements in computer technology, potentially improving planning effectiveness in two ways:

Actual plan development time is significantly shorter and allows significantly more "what if" analyses and incremental economic analyses to be conducted. To solve an LP model 15 years ago usually involved one or two batch computer jobs submitted overnight. Today, LP models are solved on a PC or workstation, providing a solution in 5-10 min.
A large portion of plan implementation can be successfully automated today. Some examples include: more sophisticated process control systems; use of real-time, rigorous on-line optimization models (ROMS) to optimize process unit operations; and on-line product blend optimizers. Advances in this type of technology are designed to accelerate the plan implementation process, without the need for error-prone human intervention.

The planning process, however, also has been subject to increased attrition and turnover of employees, resulting in a net decline in plan development expertise. Today, the planning analyst position is seen as a developmental position for engineers with 5-10 years of experience, who spend 2-3 years in the planning group before moving on to another position. The planning/LP "gurus" of the past are indeed a rare breed today.

These concurrent changes in technology and planning demographics result in only modest improvements in the commercial effectiveness of refinery planning. Computing technology is not being fully leveraged in the planning process.

PLANNING ASSESSMENT

Two of the key challenges in conducting an assessment is its generally qualitative (i.e., subjective) nature, and a lack of peer group data available for benchmarking. These problems can be overcome by developing a consistent, systematic scoring process that evaluates the key components of the tactical planning process by grading each key work task.

The author suggests that refiners form a "pilot" or cooperative group of refining planning experts from several companies. Such a group can eliminate assessment bias and allow general consensus to be reached about score weighting and critical factors that must be achieved to get a 'best-in-class' rating.

A well-defined planning assessment process allows the qualitative assessment to be converted into a quantitative "scorecard" performance measure.

As illustrated in Fig. 4 (76935 bytes), the scoring system is designed such that the three main categories of effective planning are broken down into critical "subtasks" that must be performed in each step. These subtasks are scored by evaluating each task separately on the key components of the work process: people, technology, and processes (Table 1 (24451 bytes)).

The people, technology and process scores for each key task form the foundation of the planning assessment and ensure scoring objectivity. Examining the matrix of scores across the key tasks and the three key infrastructure components allows a refiner to develop an action plan for improvement.

Quantifying the effectiveness of tactical planning also encourages participation in group studies for benchmarking purposes.

The tactical planning scorecard can be designed to show both the refiner's self assessment and the independent assessment against a backdrop of peer group scores. Thus, the scorecard indicates the areas requiring the most improvement and provides a measure of "distance-to-go" to achieve an outstanding rating, in both task scores and in people, process, and technology scores.

Table 2 (29225 bytes) presents the key steps involved in performing the tactical planning assessment using the pilot group concept.

MOA

Companies today are realizing that continuous improvement without appropriate performance measurements is a noble yet misguided endeavor. The vast majority of refiners, however, do not link economic performance measures directly with company strategy.

Many refiners probably share a vision related to being a low-cost producer. Somewhere in that vision is the goal of increased refinery operating margin. But how much can the refinery operating margin be increased with existing assets and markets?

Dissecting the company's performance into its key work processes gives both magnitude and direction to the questions: "How much operating margin are we 'leaving on the table?"' and "What do we need to work on first?"

A margin opportunity analysis is a process that measures deviation of historical actual performance from predicted optimal performance, using the existing assets and markets. The MOA can be used with or without the pilot group assessment.

The focus of an MOA is on a profitability index (e.g., variable margin) with appropriate itemization of contributions from the different business processes. This highlights the areas with the greatest impact on the performance gap. This concept is best illustrated graphically, as in Fig. 5 (86133 bytes).

Only by examining the barriers to achieving optimal profitability can the performance gap be reduced over time.

The analysis begins with an output measure (operating margin) and can continue to the lowest level of performance measurement-people measures-if necessary.

To accomplish this, the margin opportunity analysis must become a key process within the overall tactical planning process. It must have a process "owner" who is responsible for direction and completion of the measure, and it must have identifiable "customers" - people who use the information to create change. Only then can one obtain ongoing profitability improvement.

The methodology for conducting this analysis is very similar to the tactical plan development process itself, and it uses the same decision support tool-the LP model.

The analysis is best conducted on a monthly basis. This schedule provides a measure consistent with the close of the accounting department's books and the reporting of yield accounting and financial performance (Table 3 (76695 bytes)).

The actual methodology employed to conduct the MOA depends on the operation and the focus of the analysis. The general approach, however, is to begin with a model that is constrained to match actual pricing and volumetric data. The analysis then continues such that each constraint is individually removed to measure the profit opportunity associated with it.

At the end of the analysis, the optimal margin is calculated using existing market prices and refinery assets' subject to open crude selection, an open product slate, and maximum process unit utilization (Fig. 6 (76695 bytes)).

The magnitude of the overall margin opportunity, as well as the contribution of each manufacturing process step, can be measured and acted on to truly achieve low-cost producer status.

PROFIT IMPROVEMENT

The profit-generating potential from employing a margin opportunity analysis cannot be understated. Margin increases on the order of $0.50/bbl are achievable simply by conducting an MOA and letting the problem areas expose themselves.

Because costs in oil refining are heavily concentrated in selecting the optimal feedstocks and producing the optimal product slate, small improvements in feedstock selection and gross product value provide great leverage to the profit margin.

Fig. 7 (80913 bytes) illustrates that a margin increase of 30% is obtained by decreasing crude costs by 1.6% ($0.25/bbl) and by increasing the gross product value by 1%.

The MOA process can be very enlightening because, in many cases, the solutions are not overly complicated or mathematically complex. Consider the following examples:

A U.S. Gulf Coast coking refinery emerged from a down-sizing initiative with a discontinuation of monthly laboratory and technical yield reports, because of their perceived lack of value. The MOA pointed to a potential model yield problem as a cause for large deviations between the actual margins and the modeled margins.

Subsequent analysis showed that two of the crude oils processed by the refinery had experienced API gravity declines of 1.5 and 2.00 over the previous year, with corresponding yield degradation. A lack of communication between both the laboratory and process engineering groups and the planning group resulted in an outdated LP model, reflecting the older, better quality crude assay data.

Because of this discrepancy, these two crudes were often selected as the most favorable to process at the refinery, many times replacing what were later discovered to be much more profitable crudes.

The impact on profit margin in this case averaged $0.30/bbl over 6 months-a total of more than $5 million. The declining API gravity trend could have been discovered earlier with proper reconciliation of LP model yields to actual plant data.

The planning group in a cracking refinery operating on the U.S. East Coast continuously developed operating plans calling for maximum crude runs, as limited by the atmospheric pipe still. An MOA indicated that the optimal crude rate should have been set almost 10% below the level actually run.

According to the analysis, the refinery was losing money, on an incremental basis, at crude unit utilization rates greater than 88% because of a cat cracker limit. Further review indicated that the LP model did indeed indicate negative incremental margins during monthly plan development.

The plant manager, whose performance was linked to refinery volumetric output, had insisted on maximizing crude runs. "After all," he rationalized, "both regional refining margins and utilization were high."

Quantifying the exact margin impact in this case was difficult because of the unknown elasticity of prices in the region (i.e., the relationship of gasoline, diesel, and fuel oil prices to increasing supply). The planning analysts, however, conservatively estimated (using total price inelasticity) that the overall margin impact during one quarter of operation was $0.20/bbl or $0.7 million.

Over-charging crude could have been avoided in this case by conducting proper crude rate parametrics during plan development.

While numerous case studies can be presented that show significant savings, the true value of an MOA can be determined only by the individual refiner. One thing is known for sure-until the MOA process is executed, the refiner will never know what its profit opportunity really is.