Your favorite SAS posts from 2015

500161942Why do you read SAS blogs? Do you come solely for the technical tips? Do you follow your favorite blogger and ignore the rest? Or maybe you just read the posts that relate to your industry or your current business challenge.

I've heard from some of you that you try to read every post, but that can be hard. With more than 30 SAS blogs, it's easy to overlook some of the best posts over the course of a year.

In case you missed them, here are our top ten posts for 2015, based on total number of pageviews. The list includes a great range of topics, from spilled nail polish to machine learning.  Read More »

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The price is right: Four steps to better pricing decisions

It’s hard to believe that another year is over. 2015 is behind us; 2016 is ahead. As I looked back over this year, I recalled starting last year at the National Retail Federation Big Show.Lemonade_stand I presented in the SAS booth on “Optimizing Pricing Decisions.” The presentation was simple and used the concept of a lemonade stand to explore the challenges retailers face when executing pricing decisions, embracing price optimization, and finding ways to make strategic pricing decisions profitable. As I thought about the audience’s response, my memory was jogged, and I found myself jogging down memory lane to when I started as a pricing analyst many years ago. Back then, I found myself trying my best to embrace pricing analytics and evangelize a new concept in an organization that was not ready for change. I didn’t know then, but I was about to start my own pricing journey.

Ironically, over 12 years later, many retailers are embarking upon their own pricing journey: A journey designed to discover incremental margin gains, competitive advantage, and increased revenues. However, there are many roadblocks that make success difficult. Here are the most common:

  • Poor data quality and insufficient data.
  • A pricing strategy that's reactive instead of proactive.
  • Limited analytical techniques and skill sets.
  • A lack of clear measurements for adoption.

While roadblocks exists, there is a path to pricing journey success that has worked well for the companies I've supported along the way. It’s a four-step process that ensures roadblocks are tackled, challenges avoided, and helps make success quick and easy. Read More »

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Breaking down the great walls of data

concrete wall with geometric windowsDespite many experts touting 2016 as a significant year for innovation, IT is still chaotic, with many teams stuck in an old world. Organisations are implementing countless digital and data projects in an attempt to improve business models and streamline processes.

Sadly, these rarely reflect any kind of coherent company-wide IT strategy and often just add disorder to an already disrupted environment. IT simply keeping the lights on is no longer enough.

IT everywhere

These challenges resonated with many of the attendees at the recent SAS Live event in London, where Jill Dyché presented a keynote on “The New Executive’s Analytics Experience.”

She talked about how it’s currently a toss-up as to which business department has control of data – for different organisations, this could be marketing, finance or even IT. Many organisations think they're doing the right thing by deploying data analytics within the company, but the resulting confusion from a bad implementation is often more detrimental than the project is beneficial.

Siloed departments are one of the biggest barriers to making the most of big data. Depending on where you sit in your organization, analytics may look very different. The question of who “owns” the data function is at the forefront of many corporate agendas, but the answer is still vague.

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A fun holiday problem in PROC IML

Santa working on gift wrapping assembly lineSanta Claus and his elves are gearing up for another holiday season, busy filling orders and wrapping gifts for all of the good little boys and girls. Since snowglobes are popular gifts this year, Santa Claus has dedicated an entire department to build and wrap the 32,768 snowglobe orders that came across his desk. After several long days and nights, Santa and the elves have finished wrapping each snowglobe in preparation to be loaded onto Santa's sleigh.

However, just before loading all 32,768 boxes of snowglobes into Santa's sleigh, one of the elves realizes her wedding ring accidentally fell into one of the boxes that she was wrapping. The question is..."Which one?" The problem is the boxes are indistinguishable from each other and have been shuffled around so much, there's no way to narrow down which box, or even which group of boxes, is more likely to contain the missing ring.

One of the elves suggests opening all of the boxes to find the ring. That would take too much time, another elf points out. "We've only got a couple of days until Christmas Eve... there's no way we can re-wrap the snowglobe boxes in time."

Another elf, realizing they have two industrial-sized scales on hand, recommends weighing each package, two at a time, to find the package weighing the most. Each snowglobe box weighs exactly 3 pounds. Whichever package weighs more than 3 pounds, the elf reasons, must contain the missing ring. However, it will still take a considerable amount of time to weigh two boxes at a time, potentially as many as 16,384 different times.

A third elf chimes in and says, "Why not weigh half of the 32,768 boxes on the first scale and half on the second scale? We'll be able to see which scale weighs more, thus we'll be able to narrow the box containing the ring down to 16,384 boxes. Then, we'll split the 16,384 boxes in half and weigh 8,192 on one scale , and 8,192 on the other. We'll continue in a similar fashion until we're down to only two boxes. Then we'll be able to easily determine which box contains the ring. It turns out we'll only need to do this 15 times, since 2^15 = 32,768." The elves agree this process is more efficient and conclude it will allow them to locate the box containing the missing ring before Santa begins his journey.

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Santa, may I please share this data visualization with you?

Hidely-hodely, everyone! As you might imagine, the size and variety of the gift inventory at the North Pole puts Wal-Mart to shame. And while we’ve been at this for hundreds of years, we still make too many of some things and not enough of others. No elf can forget the year we were left with 15 million unclaimed wooden hoops because, apparently, pushing a hoop down a hill with a stick was no longer the deer’s ears.

Every year I recommend ways to improve inventory planning and, hopefully, avoid a repeat of the Great Betsy Wetsy Shortage of ’51. But, there’s a resistance to change and a bit of an old elves network. My ideas are ignored. After all, I’m just an associate gift strategist.

But this year, by golly gumdrops, it’s going to be different! I’m about to drop the associate title I’ve had for 213 years because they can’t ignore me this time!

I’m going to walk into Santa’s office…well, my VP…maybe my director…my manager’s office and present valuable information on peoples’ gift giving plans in a way so simple, even a yeti could understand. I’m using SAS® Visual Analytics to share research data that’s sure to keep the North Pole free of thousands of unwanted One Direction lunchboxes.

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Oil, options and inflation: Looking for a silver lining

Year-end outlooks from most analysts project the low-price environment in the oil market will continue for most of next year, but some pundits emphasize that the market has bottomed out and suggest recovery, though gradual, may be seen if increasing demand outpaces supply growth and sops up some of the current excess. But the year is wrapping up with few encouraging signs for the short term.

The price of oil certainly didn’t take much solace from the latest OPEC meeting, dropping under $40 and testing lows not seen in a decade. Rig counts lost another 10, inventories are full, and the prompt month contract is hitting lows not seen since the 2009 post-crash period. Announcements of major reductions in oil firms’ cap-ex for 2016 reflect these realities.

For its part, the most recent Energy Information Administration (EIA) Short-Term Outlook has West Texas Intermediate crude (WTI) prices averaging $49 per barrel in 2016. The forward curve has grown steeper on a relative basis, with the prompt month looking at $35 while prices a year out are $43. That $8 differential gives a clear indication the market expects to see prices increase in the latter part of 2016.

At the front end of the curve, option volatilities are down from 65 percent to 35 percent, impacting the value of the options VirtualOil bases its business on. But the portfolio is still making good money (see chart), largely because our hypothetical, options-based company is not exposed to the layoffs, mergers and bankruptcies facing the physical industry.

VirtualOil Rolling Five-Year Portfolio Dec 2015

VirtualOil Rolling Five-Year Portfolio Dec 2015

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Big data is coming to town!

Finger touching network gridsYou’d better watch YouTube, you’d better not cry
You’d better not post, I’m telling you why
Big data is coming to town

He’s making many lists (and selling them too),
he’s writing it twice (for redundancy’s sake),
He’s gonna find out whose naughty or nice
Big data is coming to town

He sees you when you’re sleeping (at least his drones do)
He knows if your awake (based on your cell phone usage)
He knows if you’ve been (rated) bad or good
So (do good) I mean be good for goodness sake

42-40999995You’d better watch YouTube, you’d better not cry
You’d better not post, I’m telling you why
Big data is coming to town

With little tin apps and little toy drones,
Rootie-oops-oops and rum-a-tum tunes.
Curly head dolls that toddle and coo (thanks to AI),
Elephants (Hadoop), boats and kiddie ubers too
Big data is coming to town

The kids in girl and boy land
Will have a coffee or two
They’re going to build the web 3.0
All around the world

You’d better watch YouTube, you’d better not cry
You’d better not post, I’m telling you why
Big Data is coming to town
Big Data is coming to town
Big Data is coming to town

You get the picture, now explore some additional hot topics in big data, such as the Internet of Things (IOT) and see how the IoT can benefit your industry.

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Introducing the Internet of Turkeys

When we talk about the Internet of Things and “analytics at the edge,” we’re talking about modeling data as close as possible to the device – not far away in some warehouse or data storage appliance. So, generally, the edge is anything with a sensor that is transmitting data: an appliance, a car, a manufacturing robot, and so on.

sensors attached to turkey inside a smoker

Kevin's turkey is ready to cook - and ready to transmit data.

But could the edge be a turkey?

You’d be surprised what a Brainiac can come up with over a holiday weekend. One of our lead developers in R&D, Kevin Smith, was able to connect his Thanksgiving dinner to the Internet and run some basic analytics on the cooking process. With the right technology, there’s no reason you couldn’t repeat this with your holiday turkeys later this month. But what did he do, exactly?

Kevin has a ceramic smoker with a Wi-Fi enabled thermostat and a built-in web server that can be queried to get access to the smoker’s internal data. He put his turkey breast and drumsticks in the smoker and outfitted them with probed sensors as well (see image).

Two other R&D employees, Scott Kolodzieski and Vince Deters, helped Kevin set up an event stream processing server so he could analyze data streams coming from the smoker and the turkey. He then ran streaming data into a table and used SAS® and Python to summarize and generate periodic reports. Read More »

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The final post

Hey Folks,

This is Ed, and I have some sad news to share.

A few months ago, Willie started to lose his appetite. We took him to the vet, and he was diagnosed with cancer. Unfortunately, the cancer had progressed beyond treatment. So, we brought him home and spoiled him with treats and kept him comfortable and hugged him and loved him. I’m devastated to tell you that Willie died peacefully on December 7.

It is difficult to describe the bond that we had. It was like marriage in that we were truly equal partners. It was like the bond between a parent and a small child, because every minute of every day I knew where he was and what he was doing. It was like the bond between soldiers, because we stepped into harm’s way on a regular basis and survived because of trust and teamwork. When we were working together, we moved like one organism with six feet rather than two independent individuals.

Before I started working with Willie, my family moved through public spaces like a discombobulated wrecking ball. Back then, my children were toddlers. My wife had her hands full chasing two rambunctious little boys, toting all the gear that comes with small children, and dragging a blind guy on her arm all the way. After I came home from The Seeing Eye with Willie, everything changed. Willie and I could now take the lead and provide a target that the children could follow, which took a lot of pressure off my wife so she could bring up the rear and clean up any destruction that was left in our wake.

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Latin America embraces analytics, faces familiar challenges

Lima_fountain

Parque de la Reserva, Lima, Peru

In traveling and speaking at SAS events in South America this summer -- at SAS Forum Chile in Santiago and at events in Buenos Aries, Argentina and Lima, Peru -- I had the wonderful opportunity to speak with local customers and learn about their progressive organizational approaches.

In talking with these customers, it became evident that their business and IT stakeholders faced similar challenges and priorities. Many have taken significant steps in using analytics and business insight to inform their strategies and business decisions. Still, many are also struggling to promote the proper and consistent use of analytics across all business functions. Few had problems applying analytics in an ad-hoc fashion. Rather, their challenge is applying analytics in a repeatable way, and embedding it as a core component of daily business.

An analytics executive at a major regional content and entertainment company shared with me how they were able to effectively manage and leverage analytical and BI resources through an enterprise Center of Excellence (CoE). They established a CoE to strategically work with business users across the organization. The CoE provides timely and relevant analytical insight while also helping the business users develop their own skills. This is a great example of using a CoE to evolve the maturity level of an organization.

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