Discover how Data trends can enable you to make better decisions. Learn how to use data to optimize your reporting, supply chain, and automated solutions.

1. Somewhat or
More Familiar
59%
Extremely
Somewhat
Not Very
8%
Very
16%
35%
41%
WHAT’S TO GAIN?
DESCRIPTIVE
WHAT HAPPENED?
Get in touch with reality, a
single source of truth.
Largely Reporting
PREDICTIVE
WHAT WILL HAPPEN?
Understand the most likely
future scenario, and it’s
business implications
PRESCRIPTIVE
WHAT SHOULD WE DO ABOUT IT?
Collaborate for maximum
business value, informed
by advanced analytics
External
Supply chain optimization
isn’t linear, but the 1st & 2nd
generation of planning
solutions are built that way
Concurrent optimization in
combination with cognitive
learning delivers greater
insights and flexibility, but no
proven ROI
VOLUME+VELOCITY+VERACITY+VALUE
Because of DATA
Managers can now measure, and learn more about their business, in order to translate the
new known knowledge into better and improved decision making
More data at a faster rate than ever before are being emitted through forms of:
messages, updates, images, social networking, readings from sensors, GPS signals, cell
phone usage, and more.
SMART DATA EQUALS MORE REVENUE
Top ranking companies in their industry using data-driven decision making
are on average, 5% more productive and 6% more profitable
THAN their competitors
OPTIMIZATION
LEARNING
REPORTING
YIELDS BETTER...
Disparate systems make
getting to data difficult – 5-7
ERPs solutions and 2-3
instances
IT budgets – tighter than ever
Struggling with massive data
complexity
Internal
Product traceability data 61%
38%
55%
36%
45%
27%
42%
26%
36%
28%
33%
20%
30%
23%
21%
24%
39%
33%
36%
20%
36%
21%
Supply chain visibility
Geo-location and mapping data
Mobile applications
RFID transmission
Unstructured data in warranty
Temperature and product streaming
Voice and video data
Internet of things (e.g. sensory devices
Sentiment data from user-generated
Sentiment data from socialmedia
on equipment, vending machines. etc.
and quality logs
comments on ratings, reviews and blogs
(e.g. Facebook, Twitter, etc.)
DATA
MOVING
FORWARD
ONLY 20% of companies feel their supply chains are working well
in the Supply Chain
SMART
Initiative in the Supply Chain
Data
Rules
Engines
Deployment
Process Flows
Database
Structures
Structured
Simple rules: single “ifs” to single
“thens”
Optimization based on a “known”
function or mathematical outcome
Within the organization
Inside-out with a focus on the
efficient response
Relational
Structured and unstructured
Adaptive rules: multiple “ifs” to multiple “thens”
through cognitive learning
Concurrent optimization, cognitive learning
and combinational math to drive discovery and
new insights
Cloud-based to synchronize inter-and-intra-
enterprise flows
Outside-in with a focus on sensing and
adaptation
Relational and non-relational to mine data in
lakes, streams and clouds
Current State Evolving Techniques
COGNITIVE
WHERE IS THE NEXT STEP-CHANGE IN
DRIVING AN INTELLIGENT RESPONSE?
Highly automated optimization
solutions that get smarter over
time
CURRENT VS. EVOLVING
WHERE ARE THE IMPROVEMENT OPPORTUNITIES
SOURCE: http://www.information-age.com/technology/information-management/123458486/big-data-dead-rise-smart-data
http://supplychaininsights.com/big-data-and-analytics-the-new-underpinning-for-supply-chain-success/
https://hbr.org/2012/10/big-data-the-management-revolution/ar
HOW TO OBTAIN SMART DATA
Data-driven decisions are
better decisions
PERFORMANCE USING TYPES OF DATA
=BIG DATA
DATA
FAMILIARITY WITH DATA
WHO SEES IT AS AN OPPORTUNITY?
>$500M revenue
79%
SMART DATA
The purpose of smart data (veracity & value) is to filter out the noise
and hold the valuable data, and when done effectively can be used
by the enterprise to solve business problems.
<$500M revenue
40%
are manufacturers
58% are retailers
42%
DATA OUTLOOK
Data Initiative
No Initiative
If a businesss simply uses volume & velocity, that qualifies as a BIG DATA problem.
However, a lot of this data comprises noise.