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IIASA´s analytics journey

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by

Jorge Muñoz

on 4 May 2016

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Transcript of IIASA´s analytics journey

Drone
Site Assessments
Competitor Inventory Analysis
Operation
Layout
Fleet
Web Ripping
Forms
Data Search
Saving data
in separate files
Creating
presentations
Tasks repeated every month...
This generated recurring issues...
Manual labor
Data error
Data Collection and Nurturing
Time consuming tasks
Wasting resources
Losing visibility
...and not enough time to analyze
what's hidden in our data
Or automatic
targeted alarms
Leads Follow-Up
Email notifications
Opportunity Notification
Government auctions
Data Quality
Lost Sales
Sales Rep
Targeted Activities
Improving analysis
Using
ETL tools
Reaching our goals
Centralized
Improved
efficiency
In queries and
getting data
Clean &
Organized
Tables
Data
Create a centralized
Datawarehouse
Generate data
quality rules
Mobile Apps
LISTEN
Strategy
Talk
Digital tools
Brand
Acquisition
Retention
Recovery
But, this model only works with good information
Our Marketing organization follows a strategic structure with strong market focus, composed of three elements
When we embarked on our analytics journey what we found was a little bit different...
We needed...
We needed to organize our data
Analytics Maturity Model
Product
Traditional
Segment
OUR ANALYTICS JOURNEY
This information is included to our Datawarehouse
To know our customers...
...and competitors
PROCESS PERFORMANCE
Centralized information has also allowed us to improve
With automatic commercial reports
But we have learned that we must be careful
Easy access to a lot of information may result in the excessive creation of reports
And the key point is, what kind of reports do we need?
Equipment population capture
Public tenders
Equipment Registered with MTOP
Public Tenders
Customer Data Nurturing
ID, mail, phone, influencers
SCHEDULE PLANNING
INFLUENCER UPDATE
LOST SALES REPORTING
LEADS MANAGEMENT
POPULATION UPDATE
ACTIVITY INPUT
What is coming in 2016?
LEADING
Metric today
that shows how
you will do.
Creates the news.
LAGGING
Historical metric
that shows how
you have done.
Reports the news.

Descriptive
Analytics that help
you understand
how things are going
When?
Where? Who?
What? Why?
Predictive
Analytics that help
you forecast future
performance results
2016?
Information Process
Analytics Tools
Prescriptive
Analytics that suggest a prescribed next step or action
Sales Forecast
Segmenting Retention
Strategies
Leading vs Lagging
Yellow light indicates the coming of the red light
Lagging
- A lagging indicator

follows an event.

For example, did we
meet our sales budget?


Leading
- A leading indicator helps
predict
future events.

For example, will we meet
our sales budget this year
based on the opportunities
that we are managing?

Data capture Apps
Influencer
Qualitative
Data
Customer Buying
Process
Schedule
your maintenance

Churn Propensity
Rate
Upselling/Cross-Selling
Credit Scoring
Customer Lifetime Value
Targeting Strategies
Content
Management
Predictive
models
Big Data Software under consideration
Jorge Muñoz Cassagne
Thank you
CHANGING THE GAME TROUGH DATA
Channels
Lead Dashboard
Yellow light indicates the passing of the green light
Full transcript