APICS PDM
Big Data in Supply Chains
Uses & Challenges
cliff allen
Agenda: Big Data & SCM
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What is Big Data and how does it relate to SCM?
Using Data on “the edges” (NPI & Fulfillment)
The role of forecasting; is it changing S & OP?
The sweet spot: Reverse Logistics
Omni-channel & SCM
Displaying meaningful results / communication
Encryption / Safety
Moving forward
Q&A
Traditional ERP vs. Big Data
• ERP is not going away……however
• Emerging are: The Edges:
– Channels
– Social media
– RFID
– PoS
– GPS
– Blueprint data
Digital engagement is the future
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If Facebook were a country, it would
be the world’s 2nd largest - 1.3B
78%
of small businesses now get at
least one quarter of new
customers via social media.
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Percent of 18-34 year olds who check
Facebook when they wake up - 48 %
61%
of young people refer to social media to
decide where to go when they go out.
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Social Media has overtaken adult
content as the #1 activity on the web
27%
of Americans check their social
networks several times a day.
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1 out of 8 couples married in the US
last year met via social media
35%
27%
Digital Convergence
of Americans check brand pages
regularly as part of their social media
activity.
of time spent online is for
social media.
© Deloitte & Touche LLP and affiliated entities.
Big Data: How Much
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Google processes 20K TB a day
Facebook has 2.5 PB of user data + 15 TB/day
eBay has 6.5 PB of user data + 50 TB/day
NSA touches 29K TB a day
* 1000 gigabytes = 1 Terabyte
* 1000 Terabytes = 1 Petabyte
A critical mass of new technologies and consumer and client
demand is ushering in a new era of computing, and with it the
“Post Digital Age”
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Digital
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4
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Web
Client/Server
1
2
Mainframe
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Projects measured in years
Vast divide between IT and business
Long adoption curves
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3
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Projects measured
in weeks
IT and business
collaboration
Accelerated
adoption
Projects measured in months
Bridging gaps between IT and business
Accelerated adoption
Projects measured in years
Vast divide between IT and business
Long adoption curves
The number of mobileconnected devices
exceeded the word’s
population in 2012
6 Billion
People worldwide have
access to a mobile phone
7
Complexity of data
Internet of Things
Internet of Things : Marketing & SCM
• Internet of things brings
real-time data via
scanners and sensors to
the channels and
suppliers.
• Creates real time Point
of sales data.
Making analytics relevant to the heart of clients’ business with Analytics domains
Customer
Analytics
Risk
Analytics
Finance
Analytics
Workforce
Analytics
Supply Chain
Analytics
Companies
should have a
more complete
intimate
understanding
of their
customers to
get them, grow
them, and
keep them.
Many leaders
want to take
advantage of
the benefits of
risk analytics to
limit risk
exposure or to
take certain
risks to
generate
returns.
Finance
managers have
applied
analytics to
better
understand the
present and
more
accurately
predict the
future.
Workforce
reporting and
analytics
achieves
greater
visibility and
deeper insights
into the most
complex
workforcerelated
challenges.
Apply
analytics to
achieve
forward-looking
insights
combined with
the disciplined
execution of
the supplychain function.
Big Data – Why Supply Chain?
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INCREASE CUSTOMER ENGAGEMENT—lost market share
IMPROVE PRODUCT/SERVICE QUALITY—Toyota
OPTIMIZE OPERATIONAL EFFICIENCIES—SW Airlines
PROVIDE FASTER TIME –TO-MARKET POTENTIAL FOR GREATER
REVENUE RECOGNITION—Apple & Samsung lead in APP market
• SENSE SMALL EVENTS TRIGGERS POINTS (BEFORE THEY
BECOME BIG IMPACTS PROBLEMS/PROXIES)—Nokia/Blackberry
since 2008
• IMPROVE RISK MANAGEMENT—Cost of BP oil spill
APICS Big Data Survey,2012
Supply Chain Inventory Levels
60%
Competitive Trends
79%
Actual Product Usage
Forecasting/planning/
scheduling
Actual/Real Time Demand
37%
34%
68%
Prescriptive Analytics
• The emerging technology of prescriptive analytics goes
beyond descriptive and predictive models by
recommending one or more courses of action -- and
showing the likely outcome of each decision.
Big Data – The Mystery
• Questions for executives:
• What happens in a world of data transparency?
• If you could test all decisions, would you be more
competitive?
• How would your business change with real-time data?
• Can data replace some management?
• Are Amazon, Alibaba, & Zulily Marketing or Supply Chain
Companies?
• Is Data security is an growing concern when increasing
trends for complex gathering and harnessing of data are
exploding?
Big Data – Game changers
Big Data - Amazon
• Amazon has filed a patent for a shipping system
designed to cut delivery times by predicting
what buyers are going to buy before they buy it
— and shipping products in their general
direction, or even right to their door, before the
sales click.
Big Data: Supply Chain
Game Changing Technologies
RFID & PoS Data:
• Real time consumption
• Shelves become the inventory manger
• Too much inventory can push “deals” out to
users while shopping via GPS
• Merchandising and product location
• Users include Office Max & Best Buy
Big Data: Supply Chain
Customer Analytics Blueprints
• Customer Profile: 360-degree view of the
customer
• Micro-segmentation: Create segments of one
• Next Action: Predict and Influence customer
decisions
• Loyalty Programs: Keep customers by using
data applied to particular segmentation
Big Data: Supply Chain
Eyesee: The eye recognition cameras
• Eyesee: $5,100 Mannequin uses IBM Cognos
software
– collects data from patrons — logging things like
age, gender and ethnicity
– recognizes words to allow retailers to eavesdrop
on what shoppers say about the mannequin’s
attire
Eyesee: The eye recognition cameras
• Calo (2009): People
can be so fake:
Truth in privacy
overcomes truth in
observed situations
Big Data: Supply Chain
Customer Analytics Blueprints
• In store cameras with consumer behavior
• Walmart: Shopperception
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Avg Visit duration
% of vistors thru Transit Zones
Touches per product / Pick-ups
Return to shelf
Conversion: Touches and not returned
Heat maps: color coded
7x24 shelf analysis with multiple and
simultaneous people tracking:
• Traffic Flow analysis based on
zones/time
• Heat Maps of conversion rates for each
SKU.
• Hot activity zones in shelf
More Shopper insights:
• Multiple events on the shelf.
• Entrance / bounce paths
• Average times in zones
• Product traction analysis
• Real comparative shelf layout
performance
Omni-Channel changing everything
Omni channel is here to stay…
- Make Up For Ever – The cosmetics company
put iPads in some of its stores to let shoppers
browse products and virtually try various makeup combinations by uploading their own photos
- Loyalty cards are on their way out and will be
replaced by customized rewards that
incorporate social information, shopping
behavior, and more.
PepsiCo Believes In The Power Of Data &
Analytics To Drive Supply Chain
 Near Real-time Data & Dashboards
 Identifies Actual & Predictive OOS &
Overstock Issues At SKU/ Store Level
 Enables Root Cause Analysis
 Actionable Tasks Prioritized By Profitability
 Drive Sales & Execution
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New Product Introductions
Closing Distribution Voids
Promotion Execution & Effectiveness
Store Merchandising & Replenishment
Order & Shipment Forecasts
Retail Pricing Compliance
P
Big Data - Visualization
Big Data - Visualization
-Visual Analytics methods allow decision makers
to combine their human flexibility, creativity,
and background knowledge to gain insight into
complex problems.
-Example:
- To predict demand, Amway China applied SAS
time series forecasting to data from 70 million
orders placed over the past three years
improving delivery and inventory by +20%
Utilizing Big data to discover and explain
Is not as easy as you might think…
– Poor and sparse samples, surrogates, bias…
– As number of dimensions increases it becomes
increasingly difficult to add in any data point
without giving rise to some kind of statistically
significant ‘pattern’ or ‘cluster’
– And parametric distributions become unreliable
– It is very difficult to discover useful things that are
unknown by experts
Utilizing Big data to discover and explain
Data Visualization
Once Visualized
The sweet spots for Big
Data & SCM
S & OP
Reverse Logistics and
Sustainability
The Role of Forecasting
• Forecasting is a vital function and impacts every significant
management decision…. And is always inaccurate
• Finance and accounting use forecasts as the basis for
budgeting and cost control
• Marketing relies on forecasts to make key decisions such as
new product planning and personnel compensation
• Production uses forecasts to select suppliers, determine
capacity requirements, and to drive decisions about
purchasing, staffing, and inventory
Sales & Operations Planning
• Is an executive decision-making process
• Balances demand and supply
• Deals with volume in both units and $$$ at
aggregate level
• Ties operational plans to financial plans:
one set of numbers
• Is the forum for setting relevant strategy
and policy
From APICs : – Deep Analytics
The data and the application of analytics is at the heart of S&OP
Analytics-based reporting tells the S&OP planning teams:
Where they are (Current state of the business)
What actions need to be taken and driven down into
tactical and operations S&OP processes
What results and trends are emerging from their decisions
What corrective steps do the S&OP planning teams which
to take
High Level Enterprise Resource Planning Model
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T
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2-10 Years
Forecast
Only
Annually
Forecast
Only
Bi-Monthly
Forecast
PoS real
time
&
Weekly
D
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Forecast &
Orders
Daily
Orders
Only
Strategic
Planning
Business
Planning
Sales & Operations
Planning (Can be real-time
With Analytics)
Master
Scheduling
Detailed Planning
& Scheduling
Resource
Planning
Rough-cut
Capacity
Planning
Capacity
Requirements
Planning
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The monthly sales and operations planning process & Collaborative
Planning, forecasting, & replenishment with Big Data
Second real
time Data
Check
With Analytics
& CPFR this is
real time
cutting 1 week
or more in POS
data
Pre-S&OP
Meeting
STEP 1
Data
Gathering
End of month
Supply
Planning
STEP 2
Demand
Planning
Exec S&OP
Meeting
Decisions
STEP 4
STEP 3
First real
time data
check
STEP 5
Recommendations
For executive S&OP
Capacity constraints
2-nd pass spreadsheet
Management forecast
1-st pass spreadsheets
Statistical forecasts
Field sales worksheet
Wallace: 2nd edition Sales & Operations Planning
Data and S &OP
Big Data – CLSC & Reverse Logistics
Utilizing Big data Improve CLSC Supply Chains
• Supply Chains and Marketing converge with improved POS,
velocity with RFID, reduction of lead-times with “make->sell”
compression of data & inclusion of “sell-> return.”
Reverse Logistics: Hi Tech Trash
• Two Million tons of e-waste goes to landfills each year
• 163K PCs & TVs become obsolete every year
• Eight categories of reverse flows
No
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Products that have failed; are unwanted, damaged, or defective; but can be
repaired or remanufactured and resold.
Products that are unsold from retailers, usually referred to as overstocks that have
resale value.
Products being recalled due to a safety or quality defect that may be repaired or
salvaged.
Products needing “pull and replace” repair before being put back
in service.
Products that can be recycled such as pallets, containers, computer inkjet
cartridges, etc.
Products that are old, obsolete, or near the end of their shelf life but still have
some value for salvage or resale.
Products or parts that can be remanufactured and resold.
Scrap metal that can be recovered and used as a raw material for further
manufacturing.
Reuse can cycle quickly but what
about the others? With Analytics
prescrpitive works for all 3
A business process approach
• Product acquisition is a major driver of success
• Creating effective remarketing channels is another
major driver
• Research emphasis has largely been on reverse
logistics, disassembly and remanufacturing
operations; not acquisition timing; This is where
Prescriptive analytics takes place
• Product returns represent a value stream, not just
a waste stream
Time-sensitive product return streams
• Short life-cycles; high obsolescence risk
• Returned products losing value rapidly
• “Value of time” a key prescripter
– Examples:
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PCs
Printers and Computer Peripherals
Mobile Phones
Telecommunications Equipment
Product Acquisition
• The collection of used products potentially
accounts for a significant part of the total cost,
which can be compared with the last mile issue in
distribution of products in the forward supply
chain.
• The collection may occur by door to door, through
service center, through sales center and
sometimes by customers.
• Answer: Proximity and ease of access for
customers & timely returns based on prescriptive
analytics
• Sorting
Purification
Compounding
Analytics in non-traditional supply
chain markets
Advanced Technology & Hospitals
• Lean beyond shop floor
• Current State data
– Doctor data tracking has
helped reduce the
average stay for adult
inpatients from 4.2 days
in 2011 to four days in
2012.
– Such efforts also have
reduced the average cost
per admitted patient by
$280, which saved the
health system a total of
$13.8 million from 2011
to 2012.
Advanced Technology
• Process:
– Surgical Supplies Pick &
Return
Advanced Technology
• Success:
– Eliminated 12,000
supply errors
– Saved 600 hours of
O.R. time
– Reduced inventory by
15%
– Real-time
Performance
Reporting
Usage, Benefits, and Success of BA
The data Scientist and business exec cannot communicate.
 Why BI/BA projects fail
1. Failure to recognize BI projects as crossorganizational business initiatives and to
understand that, as such, they differ from typical
standalone solutions
2. Unengaged or weak business sponsors
3. Unavailable or unwilling business representatives
from the functional areas
Usage, Benefits, and Success of BA
 Why BI/BA projects fail
4. Lack of skilled (or available) staff, or suboptimal
staff utilization
5. No software release concept (i.e., no
iterative development method)
6. No work breakdown structure (i.e., no
methodology)
Usage, Benefits, and Success of BA
 Why BI/BA projects fail
7. No business analysis or standardization
activities
8. No appreciation of the negative impact of
“dirty data” on business profitability
9. No understanding of the necessity for and
the use of metadata
10.Too much reliance on disparate methods
and tools
Big Data: Is Our Security Keeping Pace?
Big Data: Is Our Security Keeping Pace?
Are We Headed Towards “Impossible Privacy”?
Another Case: Google
•Google has every single email you ever sent using
Gmail. They have it stored, indexed, and they have
built models of your behavior.
•Yahoo and Facebook have been doing similar
things.
How secure do you feel?
Big Data: Is Our Security Keeping Pace?
The “Cloud”: The Risks
“The internet of things”
•Internet security breaches happen often.
•If the server goes down, your devices can’t access data. (Both
Amazon and Gmail have gone dark).
•Lack of access if you have no Internet access
•If a hacker gets your password, you may be locked out of all your
devices.
Your security is only as good as the weakest link in the
chain
Big Data: Is Our Security Keeping Pace?
In December & January Target reports another
hack for 110 million records
Was this done by a global cybercrime group or an
individual?
Big Data: SCM Jobs
Careers in Analytics
Supply Chain & Your Career
What type of salary can you expect from supply chain positions?*
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Vice President/General Manager $175,260
Corporate Division Manager $142,000
Supply Chain Director/Manager $114,275
Logistics Director/Manager $109,760
Business Analyst / Data Analyst $101,000
Operations Manager $98,235
Purchasing/Procurement Director/Manager $85,070
Traffic Manager $69,480
Warehouse Director/Manager $84,730
Coordinator/Analyst $67,000
*Data from Logistics Management 30th Annual Salary Survey, released April 2014. Salary potential may vary depending on
location, experience and education.
PORTLAND STATE UNIVERSITY
Big Data is easy!
Questions?