From maintenance operations in Manufacturing and Supply Chain Optimisation, to tailoring marketing offers to individual customers, see how companies are using predictive analytics throughout their business to generate significant ROI. Alan McMahon, Senior Analytics Consultant with Presidion, provide some exciting examples of Predictive Analytics in action in the Food and Drink industry. Alan also shared some of his 11 years of experience running predictive analytics projects to help people to understand what mistakes to avoid when starting out with Predictive Analytics. (Food & Drink IT Summit 2016).

1. Formerly SPSS Ireland
Applications in Predictive Analytics and
the Key Ingredients for Successful
Business Transformation
Alan McMahon
Senior Analytics Consultant

2. Advanced Analytics in the Food and Drink Industry
2
DATA
ANALYTICS
ACTION

3. Analysis &
Monitoring
Predictive
Analytics
Prescriptive
Analytics
Reporting
What
happened?
Why did it
happen?
What will
happen?
What
should I do
next?
The right solution for the right business problem?
3

4. Analysis &
Monitoring
Predictive
Analytics
Prescriptive
Analytics
Reporting
What
happened?
Why did it
happen?
What will
happen?
What
should I do
next?
The right solution for the right business problem?
4
Business Intelligence
Advanced Analytics

5. Where are organisations using Advanced Analytics?
5
Manufacturing
Supply Chain
& Logistics
Product Affinity
and Baskets
Customer
Satisfaction

6. How is it done?
6
Product Affinity
and Baskets
» What products do customers
buy?
» Who else buys the most similar
stuff?
» In a peer group, what do most
have that this one doesn’t?
» What other peer group is the
closest? Can I increase the
value?

7. How is it done?
7
Manufacturing
Finding patterns in maintenance operations
that could point to opportunities for
improvements
Identifying assets at risk of failure even
when they have no previous failure history
Unearthing characteristics that lead to an
increased frequency of failures
ASSETS
MAINTENANCE LOGSSENSORING

8. Typical Challenges?
8
Organisational Silos
No single source of truth
Numerous Product Categories
and Product Types
Increasingly
Competitive Markets

9. When does it work best?
9
Delivering Measurable
Outcomes – Return on
InvestmentDATA SUPPLY
(DATA AND TECHNOLOGY)
BUSINESS
OPPORTUNITIES
ORGANISATIONAL
READINESS
Lack of Focus Low Adoption
Poor Results
ACTIONABLE
INSIGHTS
World
of the
Possible
Key
Business
Processes
Strategic
Priorities

10. How should I approach it?
10
CRISP-DM

11. Best Practices? – http://www.presidion.com/blog/
11

12. linkedin.com/in/alanpmcmahon
linkedin.com/company/presidion
@Presidion
12
alan.mcmahon@presidion.com