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:
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