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Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
BUILD
ANALYTICAL
MATURITY
Copyr ight © 2015, SAS Institute Inc. All rights reser ved.
I. INTRODUCTION
II. WHAT IS IT?
III. APPROACH & METHODOLOGY
IV. MARKET OBSERVATION
V. CUSTOMER STORY
Copyr ight © 2015, SAS Institute Inc. All rights reser ved.
NATAN MEEKERS
Data & Analytics Advisor
natan.meekers@sas.com
+32 2 766 08 35
NatanMeekers
@NatanMeekers
Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
What happened?
Standard
reports
Where exactly is the problem?
Query
drill
down
Why is this happening?
Statistical
Analysis
What if these trends continue? Forecast &
predict
What is the best that can happen?
When is a problem happening ?
Alerts
Raw
data
Clean
data
Optimise
Competitive Advantage $
Degree of Intelligence
THE PATH FROM DATA TO VALUE
Copyr ight © 2015, SAS Institute Inc. All rights reser ved.
40BUSINESS
ANALYTICS
YEARS OF
CUSTOMER
SATISFACTION &
LOYALTY*
#1
58OFFICES
WORLDWIDE
Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
WOULD YOU RATHER
LOOK AHEAD
OR BEHIND?
Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
ANALYTICS WHAT EXACTLY IS IT?
Philip R. Bevington McGraw-Hill, 1969
DATA REDUCTION
& ERROR
ANALYSIS
Copyr ight © 2015, SAS Institute Inc. All rights reser ved.
ANALYTICALLY
UNDEVELOPED
ANALYTICALLY
AWARE
ANALYTICALLY
INFORMED
ANALYTICALLY
RELIANT
ANALYTICALLY
INNOVATIVE
LEVEL 1
LEVEL 2
LEVEL 3
LEVEL 4
LEVEL 5
Isolated analytics
use.
Unsophisticated
tools and
practices
predominate
Predictive analytics
usage is part of
mission critical
applications only.
Full benefits are not
understood by a
majority in the
organization.
Analytics usage
consists primarily of
tactical and ad
hoc approaches.
Analytics dev. and
deployment is
constrained, yet
departments have
their own experts
and/or initiatives.
Analytics talent
is centralized into
larger groups.
Management
understands and
supports analytics
for strategic value,
thus bringing
business units into
alignment
Company is
committed to
analytics as part of
its future growth
plan.
Business units
embrace their own
transformational
analytical plans.
Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
APPROACH & METHODOLOGY
PREDICTIVE
ANALYTICS
EXPLORATION,
VISUALIZATION &
DESCRIPTIVE
STATISTICS
DASHBOARDING &
REPORTING
Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
Hybrid Analytic APPROACH FOR Complex Problems
ENTERPRISE DATA
KNOWN
PATTERNS
UNKNOWN
PATTERNS
COMPLEX
PATTERNS
UNSTRUCTURED
DATA
ASSOCIATIVE
LINKING
HYBRID APPROACH
RULES
Rules to surface
known issues
ANOMALY
DETECTION
Algorithms to
surface unusual
behaviors
PREDICTIVE MODELS
Identify
patterns and
relationships to
anticipate
future events
TEXT MINING
Enhance
analytic
methods with
unstructured
data
NETWORK ANALYSIS
Associative
discovery through
automated link
analysis across
heterogeneous
data
Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
Hybrid Analytic APPROACH
DATA
DEPLOYMENTDISCOVERY
Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
• Assess your current readiness
• Available Skills
• Information Processes
• Technical Infrastructure
• Culture
• Conduct a gap analysis
• Identify starting points
• Develop a roadmap
APPROACH & METHODOLOGY
BIG DATA ANALYTICS IMPROVES DECISIONS
Strategic
Decisions
Tactical
Decisions
Operational
Decisions
Big choices of Identity
and Direction
Long term
How to manage performance
to achieve the strategy
Middle term
Daily high-volume
business decisions
Short term
VALUE = NUMBER OF DECISIONS x VALUE IMPROVEMENT PER DECISION
Ex. Focus on
physical stores
Ex. Changes in
assortiment
Ex. Product
promotions
53%
41%
47%
25%
6%
15%
0%
10%
20%
30%
40%
50%
60%
Make data-driven
decisions "very
frequently"
Make decisions
"much faster" than
market peers
Execute decisions
as intended "most
of the time"
PERCENTAGE OF RESPONDENTS BY DATA CAPABILITIES
Top performer
Everyone Else
TOP
PERFORMERS
Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
16%
13%
7%
10%
6%
3%
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
Revenue (organic, non-
acquisition)
Operating cash flow Operating costs
BOTTOM LINE IMPROVEMENTS YOY
Advanced Analytics & Big Data
All Others
Source: Aberdeen Group, July 2014
Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
BIG FOOD COMPANY
1.000.000.000 UNITS / DAY
10.000 PRODUCTS TO MARKET
Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
Seasonal
influences
Different sales
regions
Many product
categories
Complexity of
perishable nature
of goods
Retail trends
Abundance
of
departments
Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
PRODUCTION
How many units do we
need to produce?
When to produce these
products?
MARKETING
What is the impact of my
campaign on sales?
Can I drive demand with
my campaigns?
SUPPLY CHAIN
Optimize routes to supply
Better planning
50% LESS BIASED FORECAST
ABILITY TO SHAPE DEMAND
Copyr ight © 2016, SAS Institute Inc. All rights reser ved.
ONE WHO DOES NOT
LOOK AHEAD
REMAINS BEHIND.
BRAZILIAN QUOTE

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BI congres 2016-4: Hoe groei je als organisatie in analytische maturiteit? - Natan Meekers -SAS

  • 1. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. BUILD ANALYTICAL MATURITY
  • 2. Copyr ight © 2015, SAS Institute Inc. All rights reser ved. I. INTRODUCTION II. WHAT IS IT? III. APPROACH & METHODOLOGY IV. MARKET OBSERVATION V. CUSTOMER STORY
  • 3. Copyr ight © 2015, SAS Institute Inc. All rights reser ved. NATAN MEEKERS Data & Analytics Advisor natan.meekers@sas.com +32 2 766 08 35 NatanMeekers @NatanMeekers
  • 4. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. What happened? Standard reports Where exactly is the problem? Query drill down Why is this happening? Statistical Analysis What if these trends continue? Forecast & predict What is the best that can happen? When is a problem happening ? Alerts Raw data Clean data Optimise Competitive Advantage $ Degree of Intelligence THE PATH FROM DATA TO VALUE
  • 5. Copyr ight © 2015, SAS Institute Inc. All rights reser ved. 40BUSINESS ANALYTICS YEARS OF CUSTOMER SATISFACTION & LOYALTY* #1 58OFFICES WORLDWIDE
  • 6. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. WOULD YOU RATHER LOOK AHEAD OR BEHIND?
  • 7. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. ANALYTICS WHAT EXACTLY IS IT? Philip R. Bevington McGraw-Hill, 1969 DATA REDUCTION & ERROR ANALYSIS
  • 8. Copyr ight © 2015, SAS Institute Inc. All rights reser ved. ANALYTICALLY UNDEVELOPED ANALYTICALLY AWARE ANALYTICALLY INFORMED ANALYTICALLY RELIANT ANALYTICALLY INNOVATIVE LEVEL 1 LEVEL 2 LEVEL 3 LEVEL 4 LEVEL 5 Isolated analytics use. Unsophisticated tools and practices predominate Predictive analytics usage is part of mission critical applications only. Full benefits are not understood by a majority in the organization. Analytics usage consists primarily of tactical and ad hoc approaches. Analytics dev. and deployment is constrained, yet departments have their own experts and/or initiatives. Analytics talent is centralized into larger groups. Management understands and supports analytics for strategic value, thus bringing business units into alignment Company is committed to analytics as part of its future growth plan. Business units embrace their own transformational analytical plans.
  • 9. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. APPROACH & METHODOLOGY PREDICTIVE ANALYTICS EXPLORATION, VISUALIZATION & DESCRIPTIVE STATISTICS DASHBOARDING & REPORTING
  • 10. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. Hybrid Analytic APPROACH FOR Complex Problems ENTERPRISE DATA KNOWN PATTERNS UNKNOWN PATTERNS COMPLEX PATTERNS UNSTRUCTURED DATA ASSOCIATIVE LINKING HYBRID APPROACH RULES Rules to surface known issues ANOMALY DETECTION Algorithms to surface unusual behaviors PREDICTIVE MODELS Identify patterns and relationships to anticipate future events TEXT MINING Enhance analytic methods with unstructured data NETWORK ANALYSIS Associative discovery through automated link analysis across heterogeneous data
  • 11. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. Hybrid Analytic APPROACH DATA DEPLOYMENTDISCOVERY
  • 12. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. • Assess your current readiness • Available Skills • Information Processes • Technical Infrastructure • Culture • Conduct a gap analysis • Identify starting points • Develop a roadmap APPROACH & METHODOLOGY
  • 13. BIG DATA ANALYTICS IMPROVES DECISIONS Strategic Decisions Tactical Decisions Operational Decisions Big choices of Identity and Direction Long term How to manage performance to achieve the strategy Middle term Daily high-volume business decisions Short term VALUE = NUMBER OF DECISIONS x VALUE IMPROVEMENT PER DECISION Ex. Focus on physical stores Ex. Changes in assortiment Ex. Product promotions
  • 14. 53% 41% 47% 25% 6% 15% 0% 10% 20% 30% 40% 50% 60% Make data-driven decisions "very frequently" Make decisions "much faster" than market peers Execute decisions as intended "most of the time" PERCENTAGE OF RESPONDENTS BY DATA CAPABILITIES Top performer Everyone Else TOP PERFORMERS
  • 15. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. 16% 13% 7% 10% 6% 3% 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% Revenue (organic, non- acquisition) Operating cash flow Operating costs BOTTOM LINE IMPROVEMENTS YOY Advanced Analytics & Big Data All Others Source: Aberdeen Group, July 2014
  • 16. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. BIG FOOD COMPANY 1.000.000.000 UNITS / DAY 10.000 PRODUCTS TO MARKET
  • 17. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. Seasonal influences Different sales regions Many product categories Complexity of perishable nature of goods Retail trends Abundance of departments
  • 18. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. PRODUCTION How many units do we need to produce? When to produce these products? MARKETING What is the impact of my campaign on sales? Can I drive demand with my campaigns? SUPPLY CHAIN Optimize routes to supply Better planning 50% LESS BIASED FORECAST ABILITY TO SHAPE DEMAND
  • 19. Copyr ight © 2016, SAS Institute Inc. All rights reser ved. ONE WHO DOES NOT LOOK AHEAD REMAINS BEHIND. BRAZILIAN QUOTE