VirtualOil Portfolio benchmarking and forward month analysis

How’s your oil book looking? As prices continue their decline, the industry is making rapid adjustments, including project shut-ins and corporate restructurings. With WTI at $55 per barrel and the forward price five years out hitting $66, energy firms are scrambling to lock in value while bargain hunters start to sniff out attractively priced oil and gas investments.

As a simulation exercise, SAS has created a fictitious oil portfolio nicknamed VirtualOil, which readers can use as a generic benchmark against their physical oil commodity book’s performance. Each month, we reflect on what the visual analytics can tell us about the portfolio’s movement. This chart represents both Mark-to-Market and Value-at-Risk, at the barrel level, of the rolling five-year portfolio. This month, VirtualOil still shows a value of $12.29 per barrel over our $50 strike price, even though the portfolio is heavily weighted toward the first few months. The optionality becomes more valuable as we approach the strike price.

VirtualOil Five-Year Rolling Portfolio

VirtualOil Five-Year Rolling Portfolio

 

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Is fraud really the biggest issue in health care cost?

200314219Health care fraud is often depicted as the great, five-headed hydra in Greek mythology. When you cut off one head, two more grow back.  But more to the point, health care fraud has been presented as one of the primary (if not the primary) causes of unnecessary healthcare spend.  However, just because fraud sounds bad and clearly is a problem, sometimes it is too easy to simply blame fraud with such broad strokes.

According to the World Health Report 2008, fraud and error account for roughly seven percent of the cost of claims in the United States (Adjusted to USD 2013, that comes out to $487 Billion annually). However, compare that with the analysis of PriceWaterhouseCoopers Health Research Institute 2007, which puts avoidable costs at 54 percent. Likewise, Berwick & Hackbarth, 2011, says that “waste in healthcare” is 47 percentof claims.  Waste takes on many forms, including:

  • Medical errors.
  • Extreme treatment variation.
  • Fragmented healthcare delivery.
  • Inefficient administration.

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Vocabularies: Deciphering the language of business rules

A vocabulary example (click to enlarge)

Vocabularies example (click to enlarge)

Having met and discussed business rules with many customers over the last year, several questions arise in nearly every business rules conversation. Business rules can vary a lot by industry, but understanding the need for business rules in decision processes is common across every application. In all cases, quite a bit of time is spent focusing on vocabulary creation – something that is necessary before any business rules are written.

Vocabularies need to be recognizable to the business and must be organized in a way that reflects the natural logic of the business application. A data driven approach to selectively creating or deriving a vocabulary has been very useful and well received by customers in every industry.

So what is a vocabulary? In its most common form, a vocabulary is a "fundamental tool for communication and acquiring knowledge," according to Wikipedia. In the context of decision management, a vocabulary is a set of terms that are used to create business rules. It is part of the business rules language, along with operators that define how the terms are combined.

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Sensors, those amazing (very) little things!

IoT - connected devicesThe first sensors appeared many decades ago, and have been around for quite some time in various forms, even though they’ve really only entered the popular vocabulary over the past few years thanks to the Internet of Things.

How do sensors work? A sensor detects events, or changes in quantities, and provides a corresponding output, generally as an electrical or optical signal.

Today, sensors are used in everyday objects such as touch-sensitive elevator buttons and lamps that dim or brighten by touching the base as well as a large number of other places most people are unaware of. For example, they are used in manufacturing, medicine, robotics, cars, airplanes and aerospace.

The largest challenges when it comes to sensors occur after measurements have been made. At that point, you have to decide: Where do I collect the data being generated and how can I use it, for example, to improve my operations by decreasing variability and improve quality?

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Making 'management by walking around' more productive

two business people looking at ipadThe idea of "management by walking around" has been around for a while.  First brought to prominence in Tom Peters and Robert Waterman’s best-seller In Search of Excellence, the concept is that managers get out of their offices and meet employees in their work areas to get a sense of how things are going, listen to whatever is on their minds, and explore what is working and what isn’t.

In our modern, technology-driven world where people communicate more with email, social media and other channels, it’s more important than ever to make the effort to interact  face-to-face with your teams.  Read More »

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Winning arguments to convince your boss about Hadoop

hadoop-logoGetting universal buy in for Hadoop needn’t be an uphill struggle. In many cases, it only takes one pilot project to realize the benefits of low cost storage combined with powerful analytics.

The Hadoop topic provoked passionate conversatoin at a recent roundtable discussion attended by over 25 people from a range of industries including Retail, Telco, Gaming, Travel, Banking and Government. On hand to provide expert opinion were Cloudera (a Hadoop reseller) and experts from the SAS Data Management practice. This Customer Intelligence breakfast roundtable was held in London on November 18. We started by asking two key questions: Read More »

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SAS coders descend on 30 schools for the Hour of Code

One of many Hour of Code tutorials that get kids excited about computer science

One of many Hour of Code tutorials that get kids excited about computer science

Last year during Computer Science Education Week, some in the corporate community participated in The Hour of Code. To those who visited classrooms, thank you! Telling students about the exciting careers in computer science not only inspires leaders of tomorrow, but it also leads to more graduates equipped to innovate and address tomorrow’s challenges. And they will be needed. By 2020, we will have a million more computer science jobs than qualified applicants. This gap is serious!

Computers are such an integral part of our lives today that we may forget the computer code that makes the things run. Coding is the power behind the scenes that facilitates innovation. Besides producing applications that are a part of our everyday lives, such as email and social media, coding improves the quality of our lives and keeps us safe.

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House of Cards: The analytical hit

House of Cards is a political drama set in Washington, DC.

House of Cards is a political drama set in Washington, DC.

It can still be hard to believe that another entertainment channel outside of the traditional network giants would make an impact on public sentiment and feeling. However, the Netflix streaming content channel and its cult phenomenon House of Cards is doing just that.

Take a blend of analytics, A-list actors open for change, and an audience that provides input on the show’s story line and make up. The result? A series that has millions watching and talking about the drama, making Netflix investors smile, and turning heads in the halls of television stalwarts, such as NBC and HBO.

Of course, innovative approaches for entertainment distribution are happening constantly in the digital age. The invention of radio, traveling theater and the iPod all have allowed content to be more readily available to those that seek to be entertained. What has always been challenging and hard to predict, however, is the ability to “set your entertainment to stunning.”

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Is your supply chain a burning house?

Bremerton, Washington

Bremerton, Washington

I grew up in a town called Bremerton, Washington.  It is situated on the Kitsap Peninsula right in the middle of Puget Sound.  Given its location so close to the ocean there are a lot of naval installations in the vicinity.  The majority of the residents work at the Trident Missile Base (nuclear missiles), the Keyport Underwater Warfare Base (torpedoes), or the Puget Sound Navel Shipyard (ship repair).  This type of employment created a huge middle class. In addition to these blue collar workers, Bremerton had a supporting cast of people there to help with every need.  Doctors, lawyers, shop keepers ... you name it ... they were there to support the town and the surrounding area.

One of the residents, a lawyer, had a huge house built on property overlooking one of the great views of Puget Sound and Mt. Rainier.  It was a beautiful home fit for a very successful family.  In addition to the home, the property offered landscaped gardens, elegant trees, and a garage designed for six to 10 cars.  People from Bremerton would take visitors on drives around the town and, invariably, swing by the lawyer's house to have everyone gawk at the fancy house on the hill.

Oddly, over the years, very few if any, people ever saw the inside of the house.  If anyone ever was allowed on the property, it was to tend the gardens or clean the various fixtures.  If there was a gathering of friends, the entertaining was done on the grounds, not in the house.  This behavior caused everyone to wonder what wonderful treasures were inside.  It led to a mystique about how fancy it must be to keep others out.  How else would such privileged people live?  Everyone could see how successful the family was.  Who could hold it against them to be so private.  They lived in luxury, as everyone could see, and everyone aspired to have the trappings of success just like the lawyer's family.

Now, you must be asking why would a blogger aligned with inventory optimization and supply chain planning bring up a story about a lawyer's house in his hometown?

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Data visualization: first, prepare your data

94802938We are in the age of big data. But just because modern software makes it easy to handle large data volumes, it's worth asking: do you always need all that data? In other words, if your analytics software can accommodate and even thrive in this big data environment, does that mean that any data source is a candidate for these new big data tools?  For me, the answer is a resounding no.

Since these big data tools can handle large amounts of data (some scale to billions of rows and thousands of columns), there is a natural temptation to just drop in all your data and let it fly.  But should you? My answer, again, is no.  To get the most out of these tools, you need to do more than just drop data in and churn out a report.

You should concern yourself first with data quality, design and reporting structures.

Unfortunately the power of these tools makes it easy to get away with poor data quality and design.  If you drop in a relatively small set of data (say 10 million rows dropped in a system capable of handling billions of rows), a poorly designed set of data will still perform in an acceptable manner, meaning your reports and dashboards will render in a couple seconds.  But as more and more users consume precious space in these environments, it may be only a matter of time before an IT administrator must start to make hard decisions on managing the environment.

Do you scale up the system by buying more hardware to handle the data volume?  Do you limit who can load data and what size data can be loaded?

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