Contemporary Analysis

Data Science

Nate Watson

2018 NCAA bracket picks using Machine Learning.

Contemporary Analysis (CAN) and Cabri Group and have teamed up again to use Machine Learning to predict the 2018 NCAA Men’s Basketball Tournament. This is different than last year as we are picking the entire 2018 bracket instead of just upsets.

Historically, only 26% of tournament's games end in an upset (this includes games from all rounds). That's 17 out of 64 games. Last year we did really good. Only failing to predict 3 upsets and getting 50% of our predictions right. We are going to need to improve a bunch to win that 1M/year for life from Berkshire Hathaway--including that wee bit about having to work for Berkshire Hathaway to be eligible. This year we added far more variables and used an ensemble model. Will we be perfect? Probably not. Here is the problem with using Machine Learning to try and predict a perfect bracket:

Bridget Lillethorup

Eleven Nebraska startups that could be the next big thing

Nebraska is not California. Omaha is not San Francisco. This sounds glaringly obvious but sometimes entrepreneurs in the Midwest get caught up in proving that we're the same as any other startup scene in the country. But we're not... and that's okay! It doesn't mean we don't have big ideas here. It doesn't mean there's no tech leadership here. And it certainly doesn't mean you can't build a disruptive tech company here. The Silicon Prairie may not have the same quantity of startups as Silicon Valley, but we have just as much quality. You just have to know where to look.

Nate Watson

Machine Learning Upset Prediction Project Proves its Value

At the beginning of the project, we set out to show how the 2017 NCAA College Basketball Tournament could be a proving ground for Machine Learning analysis. There are very few places in the world where we can use the same model to predict multiple outcomes in a short period of time, have a ready-made scorecard (Vegas), have the general public understand what we are trying to do, and have a chance to "beat" the algorithm with their own knowledge.

Gordon Summers

2017 NCAA Tournament Machine Learning Prediction Results

After the first weekend of basketball, our Machine Learning Prediction tool has good results.

Nate Watson

March Machine Learning Mayhem

Machine Learning and the NCAA Men’s Basketball Tournament Methodology

 <<This article is meant to be the technical document following the above article. Please read the following article before continuing.>>

“The past may not be the best predictor of the future, but it is really the only tool we have”

 

Bridget Lillethorup

Why you should invest in your employees

Investing in employees means more than just treating them well by giving them benefits and a flexible schedule. It means putting time and resources into individuals who have potential for greatness, but may need a little guidance.

Nate Watson

Spreading the Good Word about Predictive Analytics

Contemporary Analysis (CAN) is recognized nationally as a leader in the data science field and is regularly asked to "Spread the Good Word of Predictive Analytics" by presenting on various topics at conferences around the US.  In fact, CAN has presented at six conferences in the past 14 months, including:

Grant Stanley

Predictive Analytics improves M&A Activity

There have always been two major ways to expand your business:  Grow it, or Buy it.  This brings up some interesting questions about which is more beneficial.  The correct answer is usually based on cost of customer acquisition and customer lifetime value.  Right now, with the cost of client acquisition being so high, companies are turning to buying distressed businesses.  One, it eliminates competition, and two, the customers can be acquired "on sale".  While mergers and acquisitions are common across all industries, there seems to be a significant propensity for growth by buying in the banking industry.

The unique problem that is causing an increase in the " buy them" thought process is that in banking their revenue generating power has dwindled with the decline of interest rates.   Not only that but as clients leave for competitors by natural attrition, there is a dire need for new customers.  Buying seems to solve both of these.

While it may solve the issue of new customers at a reduced cost, how to transfer the old customer base to the new bank has always been a major problem.  First, you have a bevy of new customers who have not gone through your buying process.  You have no idea who they are and why they are in the product they are in.  Secondly, you can fix problem number one by keeping the staff from the bought bank, but they're not sure if the customers are in the correct products anymore either because they don't know what products they have to sell.

Grant Stanley

Why Customer Segmentation Will Improve Your Marketing

I have been married for almost 10 years. I have gotten good at buying gifts, even clothes. I can match blouses and jewelry, dresses and belts, shoes and jeans. My secret? I look at the mannequins. Mannequins were designed to attract your attention in a store window and to lure you into the store. Then inside, they are designed to show you some of the combinations you could make with their clothes. Essentially they are designed to get you to buy more than one thing. This is perfect for guys. All we have to do is point to the mannequin and ask a store sales person where we can find those certain pieces of clothing.  We can buy the mannequin lock stock and barrel and end up with a complete outfit for our brides.

Grant Stanley

Refocusing Business Intelligence on Client Needs not Wants

When my partner, Tadd Wood, and I started Contemporary Analysis we decided that we were going to focus on developing a great final product, instead of focusing offering our products at a low cost or focusing great customer service. Not that our prices or our customer services is lacking, but that they are not our focus. We did this because I learned from owning previous businesses that people care about price before they sign the contract, they care about customer service when the product is being delivered, but once the final product is delivered all they care about is the quality of deliverable.

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