However interesting and generally appealing scenario thinking, as discussed in my previous article, may be, it only provides a broad, qualitative picture of the context within which one is considering a significant investment decision. But indeed, a very important picture, even with all its caveats. Yet, we need numbers when it comes to sinking capital. No decision executive will sign off on an investment proposal that only consists of a fascinating narrative. She or he will want to see some underpinning of the potential profitability and capital efficiency. And some what ifs. In other words: we need quantification, we need a cash flow outlook of some sort.
In fact, it is one of the more difficult, and therefore avoided, challenges: to combine qualitative with quantitative thinking. Many restrict themselves to one of the two worlds. Yet I believe one has to try to cross the border. Quantification alone can often not tell the story by itself, but only qualitative narratives have the danger of becoming arm-waving.
But this quantification, if done well, does not come easy. How can we put numbers on the future? One way is to assume that whatever was going on in the past will replicate itself going forward. For some variables that is quite doable. If you are investing in wind or solar energy, the wind speed patterns and annual numbers of sun hours at a particular location can reasonably be inferred from historic records, with some averaging over multiple years. However, for many variables such an approach would not be credible.
Nevertheless, this is exactly what was (and is) common across many sectors. In fact, it is well known that this practice was one of the main causes of the financial crisis in 2008. The notion of ‘risk’ was strongly related to the degree of stock volatility in prior periods. Risk models were used that were only driven by historic behaviour; there was no forward looking element (see NYT, 2009). In essence, the quantitative models made people stop thinking. For the calculation of the minimum coverage for Dutch pension funds (i.e. stretching out multiple decades) the use of the current interest rate is mandatory. Similarly for the oil and gas reserves calculations for the SEC (US Securities and Exchange Commission) it is required to use, for the purpose of asset valuation, the currentoil price for several decades of remaining production. Of course these last two examples have auditing and legal dimensions, but they do illustrate the dilemma when considering future cash flows: we know that the value that some important variable assumes today may not be representative for the future, but we (think we) have nothing else (that is auditable).
For investment decisions and strategy development we will often need both a scenario approach and quantitative analysis. It will depend on the investment project where the emphasis lies, but I would argue that for major capital decisions or strategies both should have equal weight. What we see in practice is that (if done at all) scenario work and quantitative investment evaluations are poorly linked, perhaps because these different approaches are serviced by different departments, they require different styles of working, different areas of expertise.
And of course, to come back to the earlier point, the quantification developed should use historic data as a basis, but needs also to include a forward looking, judgemental dimension. Scenario narratives and (probabilistic and judgementally forward looking) quantification should go hand in hand, in some way, for maximum understanding and clarity.
For quantitative analysis we require a choice of models and methods, fit for purpose, not too complicated, but yielding consistent results. And we need mathematics, to do things smartly, quickly and consistently. To deal with uncertainty in the numbers, we need probability theory and probability distributions. There is no way we can arrive at exact estimates of all future variables (costs, prices, schedules, sales quantities, tax rates, etc.). But what we can do is to try to estimate a range (under certain scenario assumptions).
One of the most important distributions for this purpose is the lognormal distribution. It is representative of multiplicative processes (as is the normal distribution for additive processes). This means that the product of variables with ranges of uncertainty will tend to be lognormally distributed. Examples are volumes (L*W*H) and revenues (number of units solds * price). The lognormal distribution is also used quite a bit to model share price behaviour. It has an elegant mathematical formulation and allows for modelling upsides and downsides (with a trick). A recent article I came across (Surovtsev, D. and Sungurov, A. “Vaguely Right or Precisely Wrong?”: Making Probabilistic Cost, Time and Performance Estimates for Bluefield Appraisal. SPE 181904. SPE Economics & Management Journal, July 2017.) confirms that most cost, schedule and production variables are best represented by such a distribution.
Rather than (only) relying on integrated systems and black-box like simulation software, for practitioners and analysts it may be useful to get into the guts of the lognormal distribution, understand its mathematical articulation and have some practical formulas to calculate things by hand. It gets a bit nerdy, but do check out a useful article for this purpose in our free knowledge base (in which more articles are to come).
A next blogpost will again be about global scenarios in a qualitative discussion: what can we learn from our predecessors?
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According to the Nigeria National Petroleum Corporation (NNPC), Nigeria has the world’s 9th largest natural gas reserves (192 TCF of gas reserves). As at 2018, Nigeria exported over 1tcf of gas as Liquefied Natural Gas (LNG) to several countries. However domestically, we produce less than 4,000MW of power for over 180million people.
Think about this – imagine every Nigerian holding a 20W light bulb, that’s how much power we generate in Nigeria. In comparison, South Africa generates 42,000MW of power for a population of 57 million. We have the capacity to produce over 2 million Metric Tonnes of fertilizer (primarily urea) per year but we still import fertilizer. The Federal Government’s initiative to rejuvenate the agriculture sector is definitely the right thing to do for our economy, but fertilizer must be readily available to support the industry. Why do we import fertilizer when we have so much gas?
I could go on and on with these statistics, but you can see where I’m going with this so I won’t belabor the point. I will leave you with this mental image: imagine a man that lives with his family on the banks of a river that has fresh, clean water. Rather than collect and use this water directly from the river, he treks over 20km each day to buy bottled water from a company that collects the same water, bottles it and sells to him at a profit. This is the tragedy on Nigeria and it should make us all very sad.
Several indigenous companies like Nestoil were born and grown by the opportunities created by the local and international oil majors – NNPC and its subsidiaries – NGC, NAPIMS, Shell, Mobil, Agip, NDPHC. Nestoil’s main focus is the Engineering Procurement Construction and Commissioning of oil and gas pipelines and flowstations, essentially, infrastructure that supports upstream companies to produce and transport oil and natural gas, as well as and downstream companies to store and move their product. In our 28 years of doing business, we have built over 300km of pipelines of various sizes through the harshest terrain, ranging from dry land to seasonal swamp, to pure swamps, as well as some of the toughest and most volatile and hostile communities in Nigeria. I would be remiss if I do not use this opportunity to say a big thank you to those companies that gave us the opportunity to serve you. The over 2,000 direct staff and over 50,000 indirect staff we employ thank you. We are very grateful for the past opportunities given to us, and look forward to future opportunities that we can get.
Headline crude prices for the week beginning 15 July 2019 – Brent: US$66/b; WTI: US$59/b
Headlines of the week
Unplanned crude oil production outages for the Organization of the Petroleum Exporting Countries (OPEC) averaged 2.5 million barrels per day (b/d) in the first half of 2019, the highest six-month average since the end of 2015. EIA estimates that in June, Iran alone accounted for more than 60% (1.7 million b/d) of all OPEC unplanned outages.
EIA differentiates among declines in production resulting from unplanned production outages, permanent losses of production capacity, and voluntary production cutbacks for OPEC members. Only the first of those categories is included in the historical unplanned production outage estimates that EIA publishes in its monthly Short-Term Energy Outlook (STEO).
Unplanned production outages include, but are not limited to, sanctions, armed conflicts, political disputes, labor actions, natural disasters, and unplanned maintenance. Unplanned outages can be short-lived or last for a number of years, but as long as the production capacity is not lost, EIA tracks these disruptions as outages rather than lost capacity.
Loss of production capacity includes natural capacity declines and declines resulting from irreparable damage that are unlikely to return within one year. This lost capacity cannot contribute to global supply without significant investment and lead time.
Voluntary cutbacks are associated with OPEC production agreements and only apply to OPEC members. Voluntary cutbacks count toward the country’s spare capacity but are not counted as unplanned production outages.
EIA defines spare crude oil production capacity—which only applies to OPEC members adhering to OPEC production agreements—as potential oil production that could be brought online within 30 days and sustained for at least 90 days, consistent with sound business practices. EIA does not include unplanned crude oil production outages in its assessment of spare production capacity.
As an example, EIA considers Iranian production declines that result from U.S. sanctions to be unplanned production outages, making Iran a significant contributor to the total OPEC unplanned crude oil production outages. During the fourth quarter of 2015, before the Joint Comprehensive Plan of Action became effective in January 2016, EIA estimated that an average 800,000 b/d of Iranian production was disrupted. In the first quarter of 2019, the first full quarter since U.S. sanctions on Iran were re-imposed in November 2018, Iranian disruptions averaged 1.2 million b/d.
Another long-term contributor to EIA’s estimate of OPEC unplanned crude oil production outages is the Partitioned Neutral Zone (PNZ) between Kuwait and Saudi Arabia. Production halted there in 2014 because of a political dispute between the two countries. EIA attributes half of the PNZ’s estimated 500,000 b/d production capacity to each country.
In the July 2019 STEO, EIA only considered about 100,000 b/d of Venezuela’s 130,000 b/d production decline from January to February as an unplanned crude oil production outage. After a series of ongoing nationwide power outages in Venezuela that began on March 7 and cut electricity to the country's oil-producing areas, EIA estimates that PdVSA, Venezuela’s national oil company, could not restart the disrupted production because of deteriorating infrastructure, and the previously disrupted 100,000 b/d became lost capacity.