Business goals are no doubt important, but in an analytic project it makes sense to balance the organization's goals with those of the Data Science department. Most individuals will recognize balance as a principle of art, but the notion of creating a sense of equilibrium between the business and the Data Scientist is just as foundational in today’s insight economy. To not cultivate this balance is to invite ruin into the organization.

1. Creating Value for Business: 2 Data Science
Questions You Must Ask from the Start
Damian Mingle
Chief Data Scientist

2. 11
Overview
Goals of Business Are Incredibly Important
However, when it comes to an
analytic project, those goals
should be in line with those of the
Data Science Department.
There must be some balance
between the business and Data
Scientist.
If this balance is not cultivated, it
could ruin an organization.

3. 22
What are the Data Science Goals?
Aim of Data Scientist:
• It is imperative to define goals in tandem with the business
objectives
• Also, obtain buy-in of your interpretation
How can this be done:
• This can be done by explicitly documenting what you expect the
output to be like
• Confirm its usefulness to the business unit you are supporting

4. 33
What is the Success Criteria?
Business concerned with Data Science ROI:
• Need to see activities of the Data Scientist which specify criteria for model
assessment
• Important for companies to see what a Data Scientist has defined benchmarks for
evaluation criteria
• The adage "to begin with the end in mind" should prompt the Data Scientist to ask
an appropriate series of questions of the business to ensure value creation

5. 44
Summary
Key Point: Data Science project success criteria are different than
the business success criteria.
Remember:
• Any Data Scientist with experience will say that it is always best
to plan with deployment from the beginning of a project.
• If the organization experiences a Data Scientist who is not
following this best practice, expect spotty results and a bit of
frustration from business counterparts.
• As an organization, it is vital to push your Data Scientist to work
hard and be assertive within the project – as well as to use their
mind and imagination.
At the end of the day, businesses want to give their Data Scientist
the permission to shape the future of their companies desires.

6. 55
Questions?

7. 66
Connect with Us
Damian Mingle
@DamianMingle
LinkedIn: DamianRMingle
www.DamianMingle.com
WPC Healthcare
@WPChealthcare
Linkedin: WPC Healthcare
www.WPCHealthcare.com