When is it time to look at a custom software solution?

If you’re asking this question you’ve already seen where the current solutions fall short. This is a pretty typical situation when you’re looking for a solution to a problem.

The best way to approach this is to first re-evaluate your requirements. Depending on how those requirements were compiled you may or may not have the expectations set correctly.

Frequently people who write requirements will put in “would be nice” requirements that become “must have” requirements in a later revision.

Assuming your requirements are accurate and the current solutions are falling short, you should consider custom software.

Depending on the solution you need the expense of this can be quite daunting. Typically the biggest obstacle is understanding the risk versus the reward. We can help you evaluate this process and make a suggestion based on our findings.

When it comes to actually building the custom solution our preferred method is to work in phases. Phase one will always be a “high definition wire frame” form of the final solution. That way we can get people using the solution to see what needs to be changed or removed.

At Contemporary Analysis we build these solutions “backwards” from most other companies. While a majority of companies build solutions to look pretty on the user interface first, they tend to piece together the data on the back end. Over time the data set can be problematic and force the entire project to get rebooted for better data.

We build the data side first. While this isn’t very pretty on the front end for version one, it allows for much more agile changes and adaptation of the end result.

At the end of the day we build solutions that can adapt to changes and the needs of the end users.

Group of young business people working in the office

How do I get my own internal team of Data Scientists?

We realized there was an industry wide shortage of people trained in the ways of Data Science. So, to meet the needs of a (then) fledgling segment of business, we created the Omaha Data Science Academy (ODSA)

The ODSA gives us the option to train an entire team for you. We’ve found the best (internal) data science teams come from people who already work for you.

Chances are the team you need is already employed and looking for a challenge and career advancement. We see the adoption of data driven decisions accelerate with teams that come from within.

Of course, that isn’t always an option. So, we can help carry the load of your data science needs until you find the right people. Regardless if you’re hiring true data scientists or looking for people who can be trained up, we’ve got the flexibility and options to make it work in the long run.

Can you train my team to do new skills?

Absolutely. We realized there was an industry wide shortage of people trained in the ways of Data Science. So, to meet the needs of a (then) fledgling segment of business, we created the Omaha Data Science Academy (ODSA)

The ODSA can train individuals or teams data science principles. We offer the flexibility to give them a crash course on all things data science if needed, or we can offer select versions.

For many of our clients the need to level set a team is a priority. We can access individual team members and see what they need.

Teams often benefit from a group training so everyone is working off the same fundamentals. But we have also run people through the normal data science academy programs when needed.

As a software agnostic company we’re able to source experts in just about any platform you may want additional training in.

Working on computer

How long are your typical engagements?

The short answer is as little or as long as you’d like us to. We work at the pace of our clients and their needs. Frequently the circumstances and situation change so we adapt to meet those needs.

When we engage with a client we put everything in a statement of work (SOW). The SOW format is great because it allows us to work directly with clients when needed, work independently of clients when beneficial, and adapt when needed.

We are somewhat unique in the fact we can be your data science team, we can supplement and train your data science team, and we can step in when needed by your data science team.

We’ve been engaged in a few projects that were a few hours worth of work. Other clients want to have a bank of hours to tap into when needed. And yet others engage and disengage over the course of several years.

Ultimately, as long as we’re on the same page as our clients needs and expectations, we’re here to help when they need us.

Business Team Handshake Collaboration Concept

Have you ever worked with a Fortune 500 company?

“Yes” is the very short answer to that question, several times. At Contemporary Analysis we’ve worked with companies of all sizes and types. We’re just as comfortable working with a small startup as we are a large multi national organization.

The “size” of the company isn’t as big of a deal to us as their ability to embrace data driven decision making. We found that smaller companies who are looking for a competitive advantage are quicker to make changes with data.

Larger companies are slower to move by nature, but also face the “This is the way we’ve always done it” syndrome. Internal politics, budgetary constraints, staffing, physical location, and more can help feed this mindset.

To that end we created our Data Hierarchy series to help educate the C-suite. Data driven initiatives pushed from the team level up the chain of command can be seen as an expense at first.

However, when the data solution is in place it may end up saving the company significant amounts of money compared to the initial costs.

What is the air speed velocity of an unladen swallow?

Sometimes you just need to quote Monty Python. …Enjoy!

GALAHAD: There it is!

ARTHUR: The Bridge of Death!

ROBIN: Oh, great.

ARTHUR: Look! There’s the old man from scene twenty-four!

BEDEVERE: What is he doing here?

ARTHUR: He is the keeper of the Bridge of Death. He asks each traveller five questions–

GALAHAD: Three questions.

ARTHUR: Three questions. He who answers the five questions–

GALAHAD: Three questions.

ARTHUR: Three questions may cross in safety.

ROBIN: What if you get a question wrong?

ARTHUR: Then you are cast into the Gorge of Eternal Peril.

ROBIN: Oh, I won’t go.

GALAHAD: Who’s going to answer the questions?

ARTHUR: Sir Robin!


ARTHUR: Brave Sir Robin, you go.

ROBIN: Hey! I’ve got a great idea. Why doesn’t Lancelot go?

LANCELOT: Yes. Let me go, my liege. I will take him single-handed. I shall make a feint to the north-east that s–

ARTHUR: No, no. No. Hang on! Hang on! Hang on! Just answer the five questions–

GALAHAD: Three questions.

ARTHUR: Three questions as best you can, and we shall watch… and pray.

LANCELOT: I understand, my liege.

ARTHUR: Good luck, brave Sir Lancelot. God be with you.

BRIDGEKEEPER: Stop! Who would cross the Bridge of Death must answer me these questions three, ere the other side he see.

LANCELOT: Ask me the questions, bridgekeeper. I am not afraid.

BRIDGEKEEPER: What… is your name?

LANCELOT: My name is ‘Sir Lancelot of Camelot’.

BRIDGEKEEPER: What… is your quest?

LANCELOT: To seek the Holy Grail.

BRIDGEKEEPER: What… is your favorite color?


BRIDGEKEEPER: Right. Off you go.

LANCELOT: Oh, thank you. Thank you very much.

ROBIN: That’s easy!

BRIDGEKEEPER: Stop! Who approacheth the Bridge of Death must answer me these questions three, ere the other side he see.

ROBIN: Ask me the questions, bridgekeeper. I’m not afraid.

BRIDGEKEEPER: What… is your name?

ROBIN: ‘Sir Robin of Camelot’.

BRIDGEKEEPER: What… is your quest?

ROBIN: To seek the Holy Grail.

BRIDGEKEEPER: What… is the capital of Assyria?


ROBIN: I don’t know that! Auuuuuuuugh!

BRIDGEKEEPER: Stop! What… is your name?

GALAHAD: ‘Sir Galahad of Camelot’.

BRIDGEKEEPER: What… is your quest?

GALAHAD: I seek the Grail.

BRIDGEKEEPER: What… is your favorite color?

GALAHAD: Blue. No, yel– auuuuuuuugh!

BRIDGEKEEPER: Hee hee heh. Stop! What… is your name?

ARTHUR: It is ‘Arthur’, King of the Britons.

BRIDGEKEEPER: What… is your quest?

ARTHUR: To seek the Holy Grail.

BRIDGEKEEPER: What… is the air-speed velocity of an unladen swallow?


BRIDGEKEEPER: Huh? I– I don’t know that. Auuuuuuuugh!

BEDEVERE: How do know so much about swallows?

ARTHUR: Well, you have to know these things when you’re a king, you know.

[suspenseful music]

[music suddenly stops]


[suspenseful music resumes]

CAN photo 17

Is Contemporary Analysis (CAN) a startup?

Contemporary Analysis (CAN) has been around long enough we can’t consider ourselves a startup anymore. But that doesn’t change the mindset of the company.

Startups are scrappy and have lofty ambitions. They also have passion for what they’re doing and are eager to take on new adventures. So, in much the same manner, CAN is a “startup at heart”.

With the diversity of our clients and the problems we solve we have to remain passionate about our industry. We seek those who fuel the same fire and make allies with companies who share our vision.

With our custom software solutions we are constantly looking at what the right fit/structure is. Is this a stand alone offering or is this our next subsidiary waiting to happen?

So “no” we aren’t a startup. But if you’ve got a fire in your belly and a problem we can solve together, we’ll gladly step into the fray with you.


How many data scientists do you have?

We pride ourselves on prioritizing the features of a software and pairing it to the greatest ROI. With our ability to train your staff on any software that is currently offered the opportunities are endless.

We get asked this question a lot. While its an easy answer to throw out a quick number the “Why” is much more germane to our business model.

In our early days we had several data scientists on staff. Because these people are hard to find and they are in high demand they were “lured” away from us at 2-3 times the salary. We completely understood the situation and remained friends with our “alumni” data scientists.

However, the desire to jump into complex problem solving or to work on things that are from all over the data science spectrum never leaves our former employees. Many of them continue to do night and weekend work for us when their current employer allows it.

Instead of having a full time staff, we run a lean shop that can scale up and down as needed. We have a core group of 5 people and we can scale up to as many as 15-20 with our “bench” of specialists.

We work with data scientists who need to be challenged with complex and unusual problems. This makes us great for research and development projects because nothing is out of bounds. Our team also has a rich work life balance being able to be there for families and friends when they need to.

Overall the setup we have attracts the right kind of talent. We are in the unique place of being able to work with anyone who wants to, but not anchoring them to a desk with a specific task.

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