Related

Predictive Analysis: What Is It And How Can It Benefit You?

on January 25

The Omaha Data Science Academy

on June 22, 2016

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.

 

More and more companies find it strategic to invest in their employees, even if it means allowing them to move on to greener pastures when the time comes. These companies care about the personal and career growth of their individual employees. They don’t back away from new talent who may need a little training. They see opportunity in new hires, unlike most who are afraid to waste money on training.

 

One such company is Contemporary Analysis (CAN). CAN provides predictive analytics to businesses with needs to unlock patterns in their data. President Nate Watson committed to investing in employees from the beginning. The result of his investments is the substantive alumni network of CAN.

 

Alumni networks are the metaphorical badges of honor for companies committed to their employees’ growth. Employees may move on to other businesses or start their own companies, but they continue to maintain positive relationships with companies like CAN who invested so much in their future. Past employees reach out to the network for advice, giving them a makeshift peer network even when they are the only data scientist in their company.

 

Watson comments, “By investing in our employees’ future, we get people not only willing to go the extra mile for us, but access to employees who have the tenacity to figure out how to solve problems. We lose really good talent, but a lot of the contracts we have right now are from companies that have our former employees in them.”

 

The opening comic portrays the decision to invest in employees perfectly: CFO: “What if we train them and they leave?” CEO: “What if we don’t…and they stay?” Companies like CAN know that whether employees stay or leave, resources are not wasted.

 

CAN doesn’t wait for the most highly trained analysts to walk through the door. CAN nurtures potential with patience for greatness.

 

Some companies make the switch to investing in their employees years after they begin operations. For CAN, commitment to training employees is embedded in their DNA.

 

Nine years ago, the same people who rely on data analysis to keep their companies moving today had never even thought of hiring a data analyst. This was during the recession. As a result, a lot of creative people with experience in data science were out of work.

 

Grant Stanley is the former CEO of CAN. Stanley saw the small pool of highly driven, intelligent, but under employed people as something special–something with which he could start a company.  

 

He then built CAN, the now 9 year old predictive analytics company. Stanley and his non-traditional co-workers would approach companies like Mutual of Omaha or West and say, “Give us the hardest problem you have and let us have a crack at solving it.” Many times they would get an opportunity because a solution was already tried by the “regulars” and failed. Giving CAN a chance provided no risk and very little outlay of cash.

 

Stanley is now CEO of Bric, a software company originally designed for small companies that now helps Fortune 500 companies plan and project manage using predictive analytics.

 

CAN approached the solution differently even from day one. Many times it felt like crash a course in learning the models necessary to succeed. However, CAN’s employees were already good at learning. They looked for solutions, sometimes in other verticals and industries, and applied that knowledge back to the original problem.

 

They found success even though they were younger and less funded than some of their well known competition. This problem solving ideology has become a cornerstone of how CAN does business, even to this day.

 

After years of solving difficult problem after difficult problem, the young data scientists were well trained. They now had resumes to qualify for more prestigious positions, even CEO or management positions. CAN learned to cope with employees moving on. They started an alumni network to capture the excitement of the “graduation” of the employees. The alumni network now boasts 15 former employees in 13 companies.

 

Nate Watson maintains the same mindset of investing in employees for CAN today.

 

If you look at CAN now, Watson has changed very little. Yes, CAN today has more resources and more consistent work, but their motto still reflects their passion to make businesses better: “Empower the great to build something greater.” This is not only true for how they work with clients, but also how they treat their employees. They aren’t afraid to smile and wave goodbye as their best employees seek other opportunities. That’s why they have such a strong alumni network.

 

In fact, last month CAN announced the start of the Omaha Data Science Academy (Oma-DSA), the ultimate goal of which is to train and place a data scientists in every company in Omaha. Their goal is not to replace the four year degree, but provide training for those who need an extra push before they become entry-level data scientists.The DSA’s motto of “Building Smarter Talent” likens back to Watson and CAN’s original mantra. 

 

Further on down the road, of course, there will be an alumni network for the Data Science Academy. Watson comments, “We want each cohort to be able to connect every cohort as they move between companies and up in each company. Having that peer network is going to be key to the success of graduates.”

 

Watson hopes that the Oma-DSA will inspire even more businesses to invest in their employees.

 

–The Oma-DSA’s Alpha class starts September 19th–the graduation party, already RSVP’d by some of the most forward thinking companies in the surrounding area, will be on December 8th.

 

CAN isn’t the only business with an impressive alumni network. Strong alumni networks like CAN’s, however, do seem unique to the tech world.

 

Aron Filbert at Lyconic is proof of this. Lyconic provides software designed to improve security guard management. Lyconic’s products are proven to increase accountability and decrease turnover rates among guards. 

 

Filbert needed a talented software developer to create Lyconic. However, he knew that he could not compete with the corporate world in pay. He gave his employees other perks to make up for this, like casual dress, time off, a lax work schedule, fluidity in moving up at Lyconic, and so on.

 

These other perks, in particular Filbert’s commitment to train and grow with his employees, helped Lyconic build a strong alumni network. Filbert’s greatest success story is a man named Carl Zulauf. He worked for Lyconic for a little over one year, gaining valuable experience alongside Filbert.

 

He moved on to a start-up company in New York City where he was compensated very well.

 

Filbert speaks of Zulauf with pride, not resentment. This is what makes Lyconic and CAN’s alumni network unique to growing tech world: they believe in each other, and that leads to success for everyone. Most businesses only care about the success of their company, not the growth of individuals.

 

Three significant results of having an alumni network.

 

Companies use their alumni networks in different ways. Since the beginning, CAN noted three positive and long-lasting results for their alumni network.

 

The physical result: CAN’s alumni network includes some of the biggest names in Omaha as well as some of the most promising startups. Names like HDR, Avantas, TD Ameritrade, Kiewit, Flywheel, and even Ebay are sporting former CAN employees. As well as 4 founders of data science software companies: Eric Burns at GazellaWifi, Luis Lopez at Crumb, Grant Stanley at Bric, and James Rolfsen at Kojuba. With each movement out, a vacancy occurs that can be filled is filled by new employees that need only training and an opportunity.

 

The social impact: The alumni network is an active and working peer connection hub. Former employees of CAN left on positive terms which means they still keep in touch and occasionally ask for help on projects or advice on business moves. The reverse is true as well: CAN doesn’t hesitate to reach out to the alumni network with questions and advice.

 

The emotional fulfillment: As Watson continues to invest in his employees and sees other companies like Lyconic do the same, he feels a deep sense of pride for the community CAN helped build.

 

As more and more companies make the switch to investing in employees, what does the future of business look like?

 

Investing in employees allows companies to retain the value of each individual, even after they are gone. As more businesses decide that money spent on staff training is money well spent, their pool of resources grows beyond their own company. Their former employees continue to have value in an alumni network. In a sense, by investing in employees you never really have to cut the cord when they move on from your business. This doesn’t get rid of competitiveness between companies completely, but it does allow different businesses to act as support for each other’s growth.

 

Watson of CAN ends with this note, “Investing in people will always be my personal mantra. I hope it continues to permeates the atmosphere of CAN, the Oma-DSA, and the Data Science Community long after I’m gone.”

 

You learn. You move up. You let go. You come back and talk shop. You train someone else. You maintain connections and continue to encourage each other. That’s CAN. That’s the Oma-DSA. That Lyconic. That’s all companies committed to individual achievement. That’s the beauty of investing in employees.


Related

Where in the world CAN you find us?

on May 23

Check out Data Science Central

on May 11

CAN is excited to announce, in partnered with the Interface Web School, the creation of Omaha’s first Data Science Academy (Oma-DSA). 

This is something we have been working on for a long time. It is actually a continuation of a service we currently offer to clients where we train a company’s first data scientist. We feel this unique person, trained in both data science and business problem solving, is needed by their company to help implement the ideology more than produce mathematical models or produce visualizations.

In the past, we heard that while companies know how to find and hire a data scientist, they fear not being able to utilize this person or even know how to correctly scope how to use predictive analytics in their business. This caused them to not execute or to execute poorly and leave a bad taste in the organization’s mouth.

CAN has discovered that having a data science advocate (instead of just a data scientist) usually fixes the hangup with implementation in most companies trying to use data science for the first time. The realization there was a considerable lack of talent when looking to fill this need, led us to develop a school that teaches not only entry level data science, but also how to address the political red tape prevalent in changing how an operation thinks and makes decisions.

This academy will help CAN reach its goal of putting a data science advocate in every company in Omaha. While audacious, we feel this is a must to keep Omaha companies relevant in an economy where we are not just in competition from a company down the street but from every other company doing similar work around the world.

 

Details.

This certificate will teach some of the most important techniques and tools necessary to introduce data science into company culture, get necessary political buy-in, find, manipulate, and analyze the data present inside your company’s database, make predictions of outcomes, and create visualizations that can help non-technical users understand and see the identified trends and patterns inside the data.  

The Oma-DSA is designed to help set a company down the road of data discovery and data-driven decision making. While not the heavy mathematician or economist created by four year degrees, the graduate will leave the Academy with the confidence and the skills of an entry level data scientist and be able to have conversations with business units, build predictive analytical MVPs, and be able to know and manage the skill sets needed for future data scientist projects.

The Certificate Consists of 4 Modules: 

  • Basics of Python Programming
  • Data Manipulation and Management
  • Statistics and Computational Modeling
  • Data Visualization

 

All classes meet 2 nights per week for 22 weeks over the course of 28 weeks for a total of 154 hours of in-class instruction to complete the certificate.

 

For more information on course offerings and to apply, go to https://interfaceschool.com/course/data-science-academy/.

You may also contact Nate Watson, director of the academy, at nate@canworksmart.com if you have specific questions about offerings or custom classes. 

 


Related

Why you should invest in your employees

on August 8, 2016

The Omaha Data Science Academy

on June 22, 2016

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 WorldSan 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.canworksmart.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:


Related

Why I work at Contemporary Analysis

on January 16, 2012

Why Corporate Hierarchy is Important

on December 4, 2012

On Entrepreneurship, Risk and Uncertainty

on January 8, 2013

Today’s flexible work trends favor the clever, well educated and self–motivated. Trends such as BYOD, MOOC’s, results-only workplace, and Holocracies such as Valve and Spotify emphasis the importance of creative, well executed ideas developed by self-motivated employees.

Flexible work trends have emerged because “scalability” allows organizations to realize large gains from ideas, instead of only operational efficiencies. For example, one clever Tweet can reach millions of people, while thousands of mediocre Tweets can fail to ever be read. Today the value is in creativity — efficiency and even automation are just prerequisites.

Today’s flexible work trends are the opposite of the trends of the 80’s and 90’s that emphasized efficiency and cost cutting: six-sigma, just–in–time, out–sourcing, the great moderation, and leverage buyouts. All of these strategies were about extracting more value from what was already being produced. While, today’s trends and technology place a premium on quality and cleverness over efficiency: typically by creating flexible work environments.

However, today’s work trends are not without problems. We have created a flexible work environment at CAN and here are several of the challenges we have experienced.

Read more…


How would your hiring process change if you only focused on the candidates best suited for the job?

Predictive analytics takes data from every applicant and employee — then identifies the patterns in your company’s collective experience to create a hiring formula that helps you select the candidates best suited for success at your organization.

For instance, CAN was approached by a large trucking company that — due to competitive industry standards and long days away from home — had a problem with driver retention. After analyzing their data, we made three important hiring recommendations to help them reduce driver turnover by 10%.

Read more…


Related

Why you should invest in your employees

on August 8, 2016

The Omaha Data Science Academy

on June 22, 2016

Eventually, we will digitize our bodies, information and objects; creating a network of everything in the world. All of the information in the world is digitized, the next step is to digitize our objects to create the Internet of Things. The concept of the Internet of Things was popularized by RFID’s helping manage Inventory flows, but that is just the surface of a far more fascinating application of technology.

Objects can now connect themselves to the Internet. Cisco Software estimates that as of July 29th, 2013 there are 8.7 billion connected objects, or 0.6% of all objects in the world. Embedded sensors and actuators allow them to sense, communicate and adjust to the environment. Objects are able to register and report pain, communicate and respond to humans and other objects.

The following are some examples of how these connected objects, the Internet of Things, will impact our world. Read more…


What if you knew about — and could fix — breakdowns before they even happened?

CAN helps companies prevent breakdowns by letting them to listen to their assets. Using sensors and actuators, we collect data on heavy machinery, buildings, and products. With this data, we build models to predict breakdowns and mechanical failures.

Learn how we helped a Fortune 500 Telecommunications company predict and prevent critical roof failures — saving millions in downtime, replacement hardware, and customer refunds. In addition, learn how we helped a Fortune 500 Construction company predict and manage breakdowns of their fleet of large haul trucks. Read more…


Related

Preparing for a Pandemic

on October 21, 2013

Suppose you have a bad feeling. Perhaps there is an aching somewhere in your body telling you that something just isn’t right. Or maybe you’ve grown accustomed to being energetic and suddenly that feeling has been replaced with a sense of fatigue. Your body is trying to tell you something, and even though you don’t know what it is you do know that something’s wrong.

And so you decide go to the Doctor. Your trusted medical professional starts by asking you a few simple questions. Together, you both start to get a clearer picture of what is bothering you based on the symptoms your body is demonstrating.

Quite often, you’ll hear a basic diagnosis and be given some healthy advice. However, there are times when the situation is more complicated. You might proceed to a physical examination. More often, blood samples are taken so that tests can be done. Unless they have all of the necessary information a doctor simply cannot make an accurate diagnosis or provide you with an accurate treatment plan.

In the business culture, our companies and work environments can also get that feeling when something isn’t right. Unhealthy attitudes or poor performance can be indicators of unbalance within your company. After all, large organizations often function as one entity and when the “body” of your company isn’t performing at a healthy level, it is only logical to seek out the cause.

At Contemporary Analysis you will find experts in Business Medicine. We like to ask questions about how your company is performing. How does your market feel? Is your sales team selling up to their potential?  Are your clients changing their behavior? Are you experiencing a lack of clarity about your businesses direction? What type of treatments have you tried already? What do you think is driving people to buy your product? Why would any of your employees want to leave the company?

Together, we can create a long list of variables which might be aspects (symptoms) of the problem, or perhaps they are causes for some of the larger problems. Then, through process of elimination we’ll provide you with the most likely diagnosis. We can eliminate the side effects of having poor sales performance by addressing the issues that are affecting your employees. We can generate healthier client relations by helping you to find a more attractive target audience. You will be able to increase your employee retention by acting on our “Doctor’s Orders” in order to keep your most valuable assets feeling strong and happy within their work environment.

We will evaluate your business’s problems quickly and efficiently, then tell you what you can do to address them. Our approach is serious, but we don’t get hung up on formality and convention. When you bring your business to CAN you can rely on us exceeding your expectations, no matter how high you set them.



Related

Public Transportation & Data Science

on August 6, 2013

Preparing for a Pandemic

on October 21, 2013

Traditional business intelligence leaves executives with the same amount of work, but with even more information to sort through. The number of decisions, the unit of work, is not diminished.

Traditional Business Intelligence asks, “What information do you need to make better decisions?” The outcome is hopefully beautiful well designed reports and dashboard that support decisions.  The problem is that you still have to make decisions.

Decisions are work.  Having more information doesn’t reduce the amount of work required to make decisions. In fact, it makes decisions more work.  More information does not create less work.

The flaw is thinking that the business decisions are calculations. Read more…



Looking for something?