Working in data analytics for fortune 500 companies, we've distilled a practical framework to discover opportunities in data analytics projects in 6 high level steps.

1. Field guide to deploy
artificial intelligence
like a start-up

2. So they want to launch an
artificial intelligence project
How do you start?

3. Use these 6 steps to
maximize the value of
data analytics whilst
reducing risk and
controlling budget.

4. TALK TO PEOPLE
Working with data means managing people, process
and technology. In that order. Go out and socialize.
Think broad. If you’re in na enterprise, cross borders.
Set up calls. Have lunch and followup coffees.
You need to understand the context, politics, facts,
dependencies, roles, capabilities.. The broader your
picture is, the better.

5. DEFINE THE
BUSINESS CASE
Make sure to address a real problem.
Involve senior leaders from the start.
Valuate the opportunity through
risk reduction or profit.

6. IDEATE
DATA PRODUCTS
What form will they take? Reports, applications
of embedded in other products?
In what context will they be used?
The sky is the limit, in this phase
The business case could likely to be solved in
many ways. You could probably come up with
various data products. Keep technology
abstract for now.

7. BUILD
A PROTOTYPE
Time to show something tangible. But don’t
waste resources. Depending on the urgency,
resources and audience, pick the right format.
Build wireframes to test complex ideas
Use open source technology to accelerate delivery
Do you expect project funding afterwards? Consider
designing the prototype as a minimum viable product.

8. RUN
A FIELD TEST
Test your prototypes in the wild. Useful
feedback often comes early in the process and
you want to gain as much input as possible
before investing.
Join meetings and socialize your data product.
Use A/B testing.
Capture all feedback and prioritize afterwards.

9. IMPLEMENT
Your vision has materialized now, and you have
feedback. Time to turn this into a project.
All elements for your business case are now at hand.
Prioritize feedback and use agile principles to gradually
improve your models.
Remember technology evolves fast. Consider a short-
term and long-term roadmap.

10. We are a machine learning consulting for IT and business teams. We
advise, research and build data analytics solutions for Fortune 500
corporations, with a startup mindset.
We are based in Belgium and covering EMEA, USA and APAC.
Contact us through office@tropos.io or visit our website,
http://www.tropos.io
LET’S DISCUSS YOUR CHALLENGE