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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:
 

• InfoTech– Omaha, NE- “Politics and Big Data”
• 2015 Predictive Analytics World– Chicago, IL- “How Predictive Analytics Fundamentally Changes Marketing”
• Internet of Things Summit– Overland Park, KS- “The Implementation of Data Science into Production”
• Big Data Summit– Kansas City, MO- “Finding and Managing Data Science Talent”
• Vistage Sales Seminar– Omaha, NE- “Improving Sales and Customer Service using Predictive Analytics”

• 2016 Predictive Analytics World– San Francisco, CA- “How to implement Predictive Cross-Sales” 

 
CAN is thrilled to spread the word about the data revolution that the world is undergoing, and about the business advantages that can be exploited from understanding that data.  Because data science is an emerging field, many firms have questions about:
How do companies implement data science?  
How should data scientists be managed?  
 
Here are some important things to consider:
Every current data scientist comes from another field
Because data science is a new field, there is very little formal, university training available.  Although data science programs are under development at UC-Berkeley, Northwestern, and UN-Omaha (among others), current data scientists have all made the transition from some other area of expertise.  Some of the most common fields producing data scientists are Mathematics, Economics, and Political Science, and other scientific professions that measure and use data.
Data Scientists are not your average employee
Data scientists feel an innate need to solve problems.  This causes them to be creative thinkers who can think outside the box and operate when there is no box.  They tend to get deeply invested in problems, and use their creativity to find or simulate the right data.  Data scientists are tenacious, and because they place such a high value on finding answers, it is paramount that their solutions be utilized.
Managing a Data Scientist can be tricky
Data scientists are not necessarily businesspeople.  It’s a manager’s job to understand what a data scientist is trying to say, and to help them explain what their solutions mean to the rest of the company.  Additionally, data scientists are not to be managed agilely – the time it will take to find the answer to a hard problem cannot be predicted or scheduled.  Lastly, it is imperative that data scientists not be moved from projects or given menial tasks: they will get bored and leave.
Implementing Data Science is also tricky
There’s an old saying that “it’s hard to teach an old dog new tricks”, and this idea translates to business practices.  It is often difficult for firms to embrace new, proactive methods when they’ve been doing things the same way for years.  Occasionally, resistance to the implementation of data science is borne out of a fear of what will be found – data scientists are known for shining a light in places where light has never been shone before.  Another challenge is being patient once data science has been implemented.  Data science is very difficult, and predictive models require considerable fine-tuning before their true potential can be realized.  Confidence and complete company “buy in” is crucial to the implementation of predictive analytics, particularly in the earliest stages.  
The rewards are immense
When properly implemented, predictive analytics will take a firm to previously unattainable heights.  We live in an age where information is king, and firms who learn to obtain more accurate information in a shorter amount of time will have a distinct advantage over those who do not.  Generally, the first step down this road involves implementing data science. There exists a staggering amount of information in your company’s data… all you need is the key to unlock that knowledge!
 
Let us know how we can help you build predictive analytics into your company. We would be glad to help.
For more information or to gain knowledge as to who and how we have helped implement predictive analytics, go to our website at:
www.can2013.wpengine.com
or connect with the president on LinkedIn at: http://www.linkedin.com/in/natewatson
or send us an email at:
support@canworksmart.com
Download our Predictive Analytics ebooks:
[contact-form-7 id=”4029″ title=”Predictive Analytics eBook”]

Recently, Contemporary Analysis (CAN) was asked by the Indianapolis Business Journal to weigh in on how Predictive Analytics is changing the marketing space. We believe by combining predictive analytics and marketing, called contextualized marketing, marketing can move closer to the holy grail of one person, one sale.  Most companies do this by purchasing a software–it’s dactyl, most companies have a line item in their budget, and it gives a third-party marketing company reoccurring revenue. While CAN itself doesn’t have a piece of software to sell, we believe that contextualized marketing is the right move for companies and that those with the edge are “the ones using data scientists to predict who inside of a group of people have the propensity to buy.”
Because CAN doesn’t have the software solution, we approached the solution from a slightly different angle. We provide modeling and results in way that can be easily added to your current tracking software. This way, a company can begin the transition from shotgun marketing to tactical marketing with a low cost of entry. Once implemented, the case can be made for the software using predictive analytics to be purchased and used if needed.
Additionally, because software companies provide a tool and very little in the way on why the tool is important, most software implementations fall flat. We believe our value is helping companies manage the change management necessary to implement the software and to understand how to use them effectively–which greatly increases both the adoption and the ROI from the adoption.
Let us know how we can help you build data science into your marketing. We would be glad to help.
For more information or to gain knowledge as to who and how we have helped implement contextual marketing, go to our website at:
www.can2013.wpengine.com
or connect with the president on LinkedIn at: http://www.linkedin.com/in/natewatson
or send us an email at:
support@canworksmart.com
 
Full article IBJ article:  http://www.ibj.com/articles/54753-smarterhq-gobbles-up-venture-funds

Contemporary Analysis (CAN)–A new president of CAN was announced earlier this month. Nate Watson, long time employee, Sr. Project Manager, and Head of Sales will take over for Grant Stanley, in early June. Grant said the lead change was a long time coming, “I am staying on as the Chairman of the Board so I can provide vision and strategy, but I am relinquishing the day-to-day operations to Nate.”
This change comes as Grant takes over as CEO of a new startup, Yield. Yield provides a tool for design and marketing companies to better project staff capacity for a given scope of work. It allows management to know how much work a designer has left and alerts the manager to when the designer is running out of work. Yield and CAN will remain close as the two are set to do work for each other for the rest of the year. “It will be a great predictive project for CAN”, says president-elect Nate, “Yield gets the leadership of Grant, we (CAN) gets to keep the strategist and visionary our company is known for, and we (CAN) get to build predictive analytics into a new product slated to change a whole vertical.”

New Leader

Nate has been steadily taking on more and more of the operations since mid-2014 when he began managing the projects he was selling. It was an important step for the company because it no longer meant there was a drop off in knowledge between setting up the project, and the implementation of the project. “We will operate like we always have. We will help companies use their data to understand and get a better handle on how to make decisions faster. When you let data do some of the heavy lifting, it’s amazing some of the insights a leader can get. They still have to make the final decision, but predictive analytics gives them access to relevant data to make decisions in seconds instead of spending hours combing through a pile of reports.”

New Verticals

Nate also brings new energy and ideas to the business. After adding political campaigns to CAN’s capabilities in 2014, Nate managed 2 governor campaigns, 2 local campaigns, and 2 bond issues. In fact, politics became 33% of the total business CAN secured in 2014. “We faired pretty well getting 3 of 6 through the primary and going 3 for 3 in the general.” In fact, CAN predicted the turnout of the primary election to within .27% or 876 votes out of 324,227, and the final vote count to within 2.8% or 1,577 out of 56,324–all 3 weeks before the election. These numbers catapulted them into the spotlight for regional and national campaigns and many took notice. To date this year, CAN has taken on a Governor campaign, two ballot initiatives, and looking to add a presidential candidate later this year.

New Ideas

CAN is working on a number of new ideas as well. Later this year, they are going to release their first piece of software. CAN’s analytical software is designed to help non-mathematical leadership interact with and learn from their data without the need to employ data scientists and includes the ability to run scenarios on live data. This will accelerate political buy-in and implementation time of analytics into a company. Their software will give CAN an entirely new revenue stream and will allow CAN to sell to much smaller companies. “We are hoping this product allows all companies to use their data to create better marketing, sales, customer retention, HR, and forecasts,” says Nate.  The system is slated to come out in the fall.
CAN is also being asked to develop auditing capabilities as well as a predictive analytics and a data science recruitment arm. “Finding, hiring, and training data scientists is a real problem for companies. The lack of data scientists is the bottleneck we think we can solve. We understand how to attract and vet data scientists better than traditional HR and hope we can partner with companies to lend them our knowledge.”
With these new ideas and growth, CAN is also going to need more staff. Currently open are positions for two new data scientists and a sales person. “We are looking for those individuals who are gritty, and can solve a problem when the solution isn’t easily found. This goes for both data scientists and salespeople.” “After all,” says Nate “finding solutions to problems–really hard problems–is how CAN has been known for the last 8 years.”
 
More data on Contemporary Analysis can be found on their website at: www.can2013.wpengine.com or by connect with Nate Watson on LinkedIn at: http://www.linkedin.com/in/natewatson