Become a Hero for Data Science in Your Company

Looking to be an agent for data-driven change at your organization? Here are some actions we believe will not only help you win, but also help your company win too!

Your Origin Story

Some organizations are more reluctant than others to dive into Data Science and Analytics.  The buzz words are flying around them and the pressure is building, but it continually falls in a future roadmap instead of plans to start today.

There is no denying that the fear is real. Data Science is a term that can be intimidating to those that don’t understand the process and skills required. An organization that historically makes decisions behind closed doors will struggle to experience data-driven efforts unearthing both company weaknesses and their “secret sauce.”  Currently, most company’s decisions may have been successful based on gut feel, or maybe one huge Excel file. Gut feel and large Excel files aren’t scalable… and they are only right until they are very wrong. Maybe those decisions that did not succeed ended in sudden leadership restructuring or, sadly, layoffs.

Being a data science hero means fighting off fear “monsters” around every corner including:

Fear of failure. 

Fear of criticism.

Fear of change. 

Fear of the unknown.

Fear of being terminated.

How do you bring the right hero powers to battle?  Here are some powers we believe will not only help you win, but also help your company win too!

 

Redefining Success

Data Science is a science. If data science is intimidating, a growing term in the industry is “Decision Science.” After all, data science in business is all about driving better decisions. It starts with a hypothesis, then a well-designed experiment, and through iterations of learning it gets more accurate.  Sometimes, the outcome doesn’t agree at all with your hypothesis. 

When defining the initial project scope, discuss the accuracy required for “success” and how to fail fast when the answer is either not attainable with the current data or how you will use that “failure” to inform your next project. A definition of success we like to use when starting out is: Do you have more evidence to make a better business decision now than before?

For more information, check out our blog about successful data science projects here.

 

Collaboration

Everyone knows “garbage in” equals “garbage out”.  Working closely with the business injects every project with years worth of industry knowledge.  Using visualization tools allows the team to share insights throughout the project, unveiling the story behind the numbers.  Business users can easily and quickly sniff out data issues and find lots of opportunities for improvement.  There never fails to be a hidden complexity in the data only recognized by the experienced eye. 

In the end, this collaboration will be the key to better evidence for a business decision and a better data solution.



Communication

A data science project is not something you can do behind the curtain. Stakeholders need to be part of the process.  They should walk away with descriptive statistics at every update that they can use to make more informed decisions early and often. These early wins build trust throughout the organization and get everyone excited for the next steps.  Breaking down the process into bite-sized chunks full of valuable information will not only help in educating all parties, but also will have them begging for future projects.

 

Are you ready to become a Hero for Data Science at your company?  Contact us for a free consultation:

Schedule Your Consultation.