planning conference

A P R I L 2 0 –2 2 2 0 1 6 | ATLA NTA , G EOR G IA US A
PREDICTIVE BUSINESS
ANALYTICS FORECASTING
& PLANNING CONFERENCE
BIG DATA
EARLY BIRD
PACKAGE
ONLY $1499 USD
WHEN YOU REGISTER BY
MARCH 18, 2016!
IBF MEMBERS RECEIVE AN
ADDITIONAL $100 OFF!
D ATA M I N I N G
Institute of Business
Forecasting & Planning
tel:
+1.516.504.7576 |
email:
info@ibf.org | web: https://ibf.org/events/atlanta2016
Predictive Business, Analytics, Forecasting & Planning Conference | To Register, please call: +1 516 504 7576 or visit: https://ibf.org/events/atlanta2016
W E D N E S D AY | A P R I L 2 0 , 2 0 1 6 | 1 : 3 0 P M – 4 : 3 0 P M
PRE-CONFERENCE WORKSHOP: PREDICTIVE BUSINESS ANALYTICS & BIG DATA
WITHIN THE SUPPLY CHAIN AND OPERATIONS (IBF MEMBERS ONLY)
Predictive Business Analytics & BIG Data Within
the Supply Chain and Operations
Big Data is all around us, especially in today’s global supply chain arena, which
includes uncertainty, complexity, volatile demand, product proliferation,
globalization and ultimately risk. Currently, there are about 15 million
gigabytes of new data collected every day. That’s more than eight times the
information located in all U.S. libraries!
In this session, we will begin with the basic terms and definitions of Big Data
from organizations such as IBM, GE, Accenture and Aberdeen Group. We’ll
then go through some case- lets of organizations that are leveraging Big
Data and Predictive Business Analytics to drive bottom-line results, such as the NBA, NFL, Schneider Electric, The US Postal Service,
Harley Davidson and more.. Next, we will focus on industry profiles of WHO is leveraging Big Data, WHAT they do with it, and HOW
they manage the processes. We’ll also explore a few more case studies of organizations that have mastered the people, processes, and
program aspects of BIG DATA and Predictive Business Analytics. We’ll also profile the tools and techniques that are emerging to drive
success. And finally, we’ll provide a few helpful hints for success and identify a few barriers to success as well.
Attendees Will Learn:
• The terms and definitions of Big Data, Predictive Business Analytics and the 4-Vs
• Which industries and companies are utilizing Big Data and Predictive Business Analytics to improve the bottom line and mitigate risk
• Emerging tools that can drive success in Predictive Analytics
• A few helpful hints for successful implementation, the 4-E’s and barriers to success
Gregory L. Schlegel
Adjunct Professor, Supply Chain-Risk Management | LEHIGH UNIVERSITY, Graduate Program
Founder | THE SUPPLY CHAIN RISK MANAGEMENT CONSORTIUM
Adjunct Professor, ERM-Enterprise Risk Management | VILLANOVA UNIVERSITY, EMBA Program
VP / Principal | SHERTRACK LLC
EDUCATIONAL SESSIONS
KEYNOT E SPEA K ER
“The Promise of Analytics –
The Art
of the Possible”
Rick Davis
Vice President, Business Intelligence
Business Intelligence, Kellogg’s
2
1
Nursing Your Inventory and
Operations Back to Health:
A Three-Step Process
This presentation will introduce a three-step process to reduce
inventory levels. The first step 1 creates short-term, tactical actions
in the S&OP meeting cycle using a new metric called Inventory
Health. Inventory Health considers safety stock, lead time, and
forecasts to determine the overall “health” of a SKU, a family of
SKUs, or the overall aggregate health of an entire Distribution
Center. Step 2 creates short-term, tactical action in the S&OP
Supply Review by challenging the ERP and Planning System set
points that influence inventory level: Safety Stock, Min Order Qty,
Lead Time, Min/Max Production Qty, etc. Step 3 creates longerterm, strategic collaboration between Marketing, Finance, and
Supply Chain in the S&OP Executive Meeting by gaining insight to
a business’s SKU portfolio. Inventory levels and SKU replenishment
strategies are mapped onto a classic ABC/XYZ matrix to see how
current-state inventory and replenishment compares to best
Predictive Business, Analytics, Forecasting & Planning Conference | To Register, please call: +1 516 504 7576 or visit: https://ibf.org/events/atlanta2016
practices. From our experience, these methods, in conjunction
with other planning process improvements, resulted in a 28%
reduction in Finished Goods Days On Hand in Ecolab Healthcare
NA over a period of three years. Join us in this session to learn how
we did achieved this success.
You will learn:
• How to quickly create action and attention using a new
Inventory Health metric
• Methods to evaluate classic inventory levers of Safety Stock,
MOQ, Min/Max/Multiples
• A novel way to gain insights by combining ABC-XYZ analysis
with inventory levels and replenishment strategies
• Better approaches for data management and forecasting
analytics
Michael Mercedes
Former Program Manager, Global Healthcare
Ecolab
2
Creating Understandable Analytics to
Inform New Product Forecasts
New product forecasting is one of the most difficult, and most
time consuming aspects in demand planning and presents its own
unique set of challenges. With the explosion of big data in today’s
business, the use of analytics around new product forecasting has
become not only important, but crucial to successful forecasting in
today’s markets. In this session, the discussion will be a detailed and
focused outline on some practical analytics techniques which can
be applied to new product forecasting and about the best-in-class
analytical approaches currently used within the pharmaceutical
industry, and how they can apply to a spectrum of other industries.
You will learn:
• How to apply practical and understandable analytics to
develop better new product forecasting
• How to create specific tools to aid in the execution of analysis
to improve speed and consistency
• How to use the results of analytics for S&OP and how to
present the analysis in order to have the greatest impact
Randy Wilp
Leader of Global Commercial Forecasting
Dave Pappentick
Sr. Project Manager, Global Commercial Forecasting
Merck & Co., Inc.
3
The Quadrant Analysis: A Strategic
Approach to ABC Finished Goods
Product Segmentation
In this session, you will learn an empirical way to code ABC that
ensures that key constituent needs are being met. It is a two-axis
mode that satisfies CEOs and shareholders by ranking product
3
SKUs on revenue or gross margins. It also will satisfy customers
by segmenting SKUs by sales unit volume. We will talk about why
the quadrant analysis takes the guesswork out of segmentation
and is different from the traditional 80/20 Pareto analysis. We will
show you how the quadrant analysis benchmarks against itself
and how to use ABC segmentation in finished goods inventory
planning, sales forecasting, and service level reporting. In this
session, you will learn how to combine ABC quadrant analysis
results with specific product knowledge (such as new product
launches and gone-when-gone scenarios). We will also discuss
how to use a simple analytical models that other functional areas
can understand. You will receive an MS-Excel file that will help you
segment your data.
You will learn:
• How to satisfy CEOs and shareholders with an empirical way
to code ABC by ranking product SKUs on gross margins or
revenue
• How to use ABC segmentation in sales forecasting, inventory
planning, and service level reporting
• How to use MS Excel to segment (attendees will receive an
MS-Excel file)
Greg Klaus
Supply Chain Project Manager
Medtronic
4
How to Optimize Statistical Forecast
Models within your System for
Demand Planning
Development of an accurate statistical forecast for demand
planning requires the evaluation of a range of different forecast
model types (Holt Winters, Double Exponential Smoothing,
Seasonal Linear Regression, etc.) as well as settings for adjustable
parameters, such as smoothing coefficients and trend dampening.
An automated optimization process, which has been developed
for the statistical models available in the SAP APO and SCM7
planning systems, will identify the best model and settings to be
programmed as forecast profiles. A systematic process has also
been developed to identify the best models and parameter settings
and produce a smaller set of forecast profiles to be maintained in
the system with minimal loss of forecast accuracy (generally <1%).
Finally, a process for including market/product knowledge into the
model selection process has been developed to aid the demand
planner or analyst in the selection of alternative models when the
lowest error model does not reflect changes in market conditions,
such as level shifts. In this presentation, we will demonstrate these
methods and illustrate their application with real world business
examples.
You Will Learn:
• How to optimize statistical forecast models based on the
minimization of forecast error using models available in SAP
APO and SCM7
• How to incorporate market/product knowledge in the
Predictive Business, Analytics, Forecasting & Planning Conference | To Register, please call: +1 516 504 7576 or visit: https://ibf.org/events/atlanta2016
selection of forecast models
• How to develop a core set of forecast profiles (20 to 30) for
use with the system
• The models and methods application with real-world business
case studies
Dean W. Face, Ph. D.
Business Process Manager
DuPont
5
Data Analysis: A Double-Edged Sword
The rise of big data has led an increasing number of
organizations to place more emphasis on analysis and planning
functions. As these groups lend greater credence to forecasting,
planning, and analysis departments, those of us in these areas find
ourselves with an ever increasing influence and responsibility. We in
analytical roles – especially roles relating to forecasting, planning,
and predictive analytics – must ensure that the conclusions drawn,
plans made, and most importantly, plans executed are based on
the surest foundation possible. If the analytical foundation that
business plans are built upon is not solid, then organizations are far
more likely to encounter unexpected and unfavorable situations.
As examples, failures can stem from inaccurate raw data, incorrect
calculation steps, choosing the wrong variables to name a
few. Although, it is true that great data analysis cannot predict
everything that could possibly happen, we can make sure that it
gives us a close picture of reality and what will likely happen in
the future. Join us in this session to learn how Reddy Ice maintains
a strong analytics foundation for better business planning and
organizational performance.
You will learn:
• How to mitigate the risk of miscommunicating data analysis to
management
• • How to better present data that is easy to interpret for
anyone
• • The differences and characteristics of good & great analytical
approaches
Grant Daniel
Senior Manager of Forecasting
ReddyIce Corp.
real-world company initiative to utilize these methods will illustrate
this potential in greater detail and offer insight into how your
organization can also benefit from machine learning.
You Will Learn:
• How machine-learning works for data science practitioners
and business leaders
• A real-world application of machine learning methods, based
on an example in the food-service logistics industry
• How to develop, optimize, and deploy neural networks in your
company
• About the power of R and how it can be a free solution to
your company’s analytics needs
Arya Eskamani
Senior Predictive Analyst
Restaurant Services Inc.
7
Demand Planning & Forecasting for
Non-Transactional Products—Review &
Best Practices
Demand Planning is primarily driven from the intelligent and
analytical usage of the various datasets available for existing
products and sales. In this session, we will focus on the best practices
in analytics and usage of data for use in Non-Transactional (Deal
Oriented) and Large-Value items (Enterprise Products). We will
discuss practical tools and techniques to enable better forecasting
and planning for these category of products. We will also focus on
the various insights that are useful for arriving at a best outcome.
This includes how our customers are gathering intelligence from
their customers behaviors via marketing analytics platforms.
You Will Learn:
• What are the practical problems planners face in forecasting
large-value items in a multinational setup, e.g., Enterprise
Products.
• How to use various sets of data efficiently to help with this
type of forecasting.
• The various analytics tools, platforms, techniques, and vendors
that can help analyze and arrange the above datasets for use
in forecasting and the overall decision making process.
Azeem Ahmad
Enterprise Demand Planning
6
Machine Learning: Forecasting with
Artificial Neural Networks
Machine learning algorithms are one of the most powerful tools
in predictive analytics. Also, as a key component in data science,
they have many advantages over standard forecasting or datamining techniques. Yet there is still much ambiguity over what
machine learning is and how organizations can leverage it for
accurate predictions. This presentation will showcase Artificial
Neural Networks, a popular type of machine learning model, and
their capabilities to analyze large amounts of data and create
accurate predictive and Forecasting models. A dive into an active
4
Dell Inc.
8
How to Use Size Forecasting,
Optimized Allocation, and Visual
Analytics from Levi’s Strauss & Company
To better serve your customers and capture lost sales in a SKU
intensive environment, ask three questions. 1) Can they find
what they are looking for in brick/mortar stores and by using
e-commerce? 2) How are product size curves calculated today and
how should they be calculated tomorrow? 3) What can we do to
Predictive Business, Analytics, Forecasting & Planning Conference | To Register, please call: +1 516 504 7576 or visit: https://ibf.org/events/atlanta2016
ensure that we are allocating the “Right Sizes” across all stores
and channels? Given the fickle nature of the fashion business, it
is critical to get your demand plans and supply plans aligned so
that you have enough product in your distribution value chain.
However, that is only part of the story. It is even more important
to get a critical product attribute—Size—correct and distributed
to locations and channels with the highest probability of making
a sale. In this session, we will discuss ways to collaborate with
partners across the value chain and unlock benefits of CPFR and
build a “Win-Win” relationship while leveraging visual analytics to
better inform assortment, product placement, pricing and demand
forecasting.
You Will Learn:
• What factors drive on-shelf availability (OSA) and what
prevents customers from finding product
• How to leverage POS data at the SKU level to inform your
sizing forecasts and supply plans
• Which algorithms to use to quantify lost sales and ensure
products are distributed to the location where they have
highest probability of making a sale
Rene Saroukhanoff, CPF
Senior Director of Merchandise
Planning Reporting & Analytics
Levi’s
Manik Aryapadi
Senior Manager, Retail & Technology Practices
A. T. Kearney
9
Improved Profitability from DataDriven Decision Making
At General Motors we believe in data-driven decisions as a
cornerstone of our DNA culture. Before 2015, the Mexican
subsidiary did not have a comprehensive vehicle inventory
control practice to better support S&OP in very dynamic market
and supply conditions. Given the radical changes in the Mexican
automotive industry, the company evolved by implementing a
consistent statistical methodology for buffer stock calculations.
In this session, attendees will learn how statistical modeling and
analytics, especially for forecasting purposes, mitigates inventory
and operational risks if appropriately used. You will hear several
practical examples about how a new framework for inventory
management affected the daily activities of other areas such as
Sales Operations, Marketing, and Production Control.
You will learn:
• How a company can improve its profitability through fostering
a data-driven culture
• Mastering forecasting to enable highly accurate inventory
levels with little or no waste
• The impact of safety stocks in simplifying daily S&OP activities
Edgar Núñez
Senior Economist / SME of Forecast & Market Analysis
General Motors
5
10
Prediction Success & Preventing
Business Failure: Using Your Own
People to Crowdsource Strategic Decisions
From the multi-year delays in the launch of Boeing’s 787
Dreamliner to the sales flops of the Amazon smartphone to the
failed healthcare.gov launch, there are countless examples of
failed business strategies. Large organizations spend tens of
millions of dollars on data initiatives, management consultants,
and their own subject matter experts to make predictions ahead
of important strategic decisions. Yet when these predictions are
wrong or overly optimistic, the companies end up with a poor
market fit for a product, slow reaction to industry changes, or
investment in the wrong areas. If external crowdsourcing can
be used to alert drivers to traffic delays as soon as they happen
and predict the outcome of elections better than polls, consider
the power of crowdsourcing internally for the strategic benefit
of large organizations. In this session you will learn how we
use crowdsourcing to give decision makers ongoing and realtime predictions from their own people to help inform the most
important strategic and investment decisions.
You will learn:
• Why predictions are often so wrong
• How organizations must evolve beyond their current
techniques and use the collective wisdom of their own people
for predictions
• Best practices from organizations who have already initiated
the crowdsourcing process, key learnings, and the benefits
they’ve experienced
Adam Siegel
CEO and Founder
Cultivate Labs
11
Application of Predictive Business
Analytics in E-Commerce,
Marketing, and Influencing Product
Demand
This session will provide some empirical evidence for the economic
relationship between FedEx Ground’s average daily volume and
U. S. e-commerce and retail sales using an econometric model.
The main finding in the research is that there exists a stable longrun relationship between the growth rate of FedEx’s average
daily volume and the growth rate of U. S. e-commerce. This
stable quantitative relationship is beneficial to forecast residential
delivery volume for FedEx Ground and we could use the analytics
company’s e-commerce forecast data to quickly estimate
approximate residential average daily volume growth rate per
month and, thus, manage our capacity efficiently. Join us in this
session to learn tips and methods that could be used to manage
your business through better analytics.
Predictive Business, Analytics, Forecasting & Planning Conference | To Register, please call: +1 516 504 7576 or visit: https://ibf.org/events/atlanta2016
You Will Learn:
• About related tests, such as unit root test, weak exogeneity
test, cointegration test, and granger causality test for
predictive analytics
• How to use these methods for impulse responses functions
and better manage your capacity.
• About the econometric methodology, e.g., Vector Error
Correction Forecasting Model.
• How to correlate external factors with internal results to create
business forecasts with unprecedented accuracy.
• Tips for generating better forecasts to optimize decisions in
staffing, supply chain, capital investment and even Wall Street
guidance.
Yidan Xia
Rich Wagner
Revenue Science Analyst
Fedex
12
Director—Investor Relations & Business Strategy
Advanced Drainage Systems (ADS)
Founder and CEO
Prevedere
Using Decision Trees for Market
Segmentation in Forecasting
Demand planning analysis is often enhanced through the use of
decision trees for market segmentation designed to help planners
determine customer attrition risks or determining profitable from
unprofitable customers? In market segmentation, decision trees can
provide this data by finding key combinations of drivers that make
a difference. Tree methods sift through hundreds or thousands
of potential predictors. Predictors include both quantitative and
qualitative measures such as past sales or geographic region. In
this session, the use of decision trees as a “customer road map”
in demand planning will be outlined showing how key predictors
can be used effectively to explain attrition or profitability, and how
they can benefit forecasting plans.
You will learn:
• How to find market segments underlying a yes/no question
within your operational forecasting plan
• How to outline the use of decision trees, and their benefits to
an organization to upper management
• How to use decision trees as predictive models in order to plan
for ‘success’ within your forecast
Sara Brumbaugh
Managing Principal
Ceres Analytics
13
The Proactive Enterprise: How to
Generate Actionable Insights with
Predictive Analytics
By leveraging today’s advanced analytics and real-time global data
on consumer behavior and market conditions, it is now possible
to identify causal factors that impact business performance. When
combined with a company’s historical data, these factors can be
quantified to give business leaders an accurate and complete
picture of future outcomes. By empowering decision makers
to proactively address constantly changing market conditions,
companies can vastly improve their predictive accuracy, resulting
in smarter spending and reduced risks.
You Will Learn:
• Ways to anticipate the impact of consumer behaviors by
weighing external factors such as unemployment, wages,
housing starts, weather, etc.
6
Mike Higgins
14
Using Predictive Analytics to
Accurately Forecast Sales from
Electronic Marketing & Traditional
Promotional Activities
Many retailers, e-commerce merchants, and consumer goods
companies spend more on promotions than they earn in profits,
yet this spend is often managed with little more than educated
guesswork. This talk will demonstrate how analytics can be used
to forecast the behavior of promotions, and to optimize the design
of both individual promotions and a firm’s overall promotion
portfolio. We will cover key insights such as determining the true
base volume, measuring cannibalization between competitor
SKUs, evaluating incremental profit for both manufacturer and
retailer, and determining how to re-allocate spend to improve ROI.
These will be illustrated with case studies drawn from both online
and bricks-and-mortar settings.
You will learn:
• How to forecast incremental volume driven by promotions
• Design better promotions and optimize your promotion
portfolio for eCommerce and brick & mortar retailers
• How to accurately measure cannibalization from promotional
activities
• How to calculate potential profits for retailers, manufactures,
as well as online stores.
Russell Halper
Sr. Consultant
Allan Gray
Co-Founder
End-to-End Analytics
15
Getting C Suite Engagement (&
Support) for Predictive Analytics,
Forecasting and Planning Initiatives
This session will be a facilitated discussion to help you unlock
funding and support from peers and upper management across
projects anywhere in the predictive business analytics, forecasting,
and/ or planning process, including building your initial analytics
capability. Learn insider secrets, which led to over 40 financing,
M&A, and non-monetary transactions aggregating to more than
$390 million. The takeaway’s that will be shared in this session is
Predictive Business, Analytics, Forecasting & Planning Conference | To Register, please call: +1 516 504 7576 or visit: https://ibf.org/events/atlanta2016
based on over 30 years helping over 200 companies, including
two international INC 500 companies spread across every industry
sector, while serving as C Suite head of every functional area. In
addition, there are three key points we will discuss. 1) You will
learn how to dramatically increase your success rate on getting
projects approved with C Suite engagement when you understand
the impact of what “they” want. 2) All the C Suite problems have
four core issues, which will be shared. 3) You must keep KEY
stakeholders in the loop, and we’ll share how best to do this. This
session will help ensure project success and perhaps your next
opportunity or promotion.
You will learn:
• How to build your initial predictive analytics and forecasting
capability with less resistance
• The secret decoder and handshake of getting C Suite approval
and buy in
• The five tactical steps that will help your ability to execute
resolution of the key issues you identify
• How to evaluate when you are better off NOT getting project
approval
Gary W. Patterson
CEO
FiscalDoctor, Inc.
16
Using Downstream Data to Improve
Forecast Accuracy and Determining
the Quantitative Impact of our Sales and
Marketing Programs
Downstream data has been electronically available with minimal
latency (1-2 week lag) to companies for over two decades. Sales
transaction data are being captured at increasingly granular levels
across markets, channels, brands, and product configurations.
Faster in-memory processing is making it possible to run
simulations in minutes; previously, it had to be run overnight. In
fact, companies receive daily and weekly retailer POS data down
to the SKU/UPC level electronically, which can be supplemented
with Syndicated Scanner data across multiple channels (retail
grocery, mass merchandiser, drug, wholesale club, liquor, and
others) by demographic market area, channel, key account (retail
chain), brand, product group, product, and SKU/UPC. As a result,
a new process has emerged called “Multi-Tiered Causal Analysis”
(MTCA), which ties downstream data (POS/Syndicated Scanner
data) and the performance of a market, channel, brand, product,
and/or SKU at retail to internal upstream replenishment shipments
(or sales orders) across time (two to three years). Now sales and
marketing programs that influence demand can be simulated and
evaluated to determine the full impact on supply (shipments).
You Will Learn:
• How to use Multi-Tiered Causal Analysis (MTCA) to capture
the impact on the supply chain by using predictive analytics to
sense sales and marketing strategies.
• How to use “what-if” scenario analysis to shape future
demand.
7
• Ways to arrive at the most realistic supply response (shipment
forecast) by linking future shaped demand to supply
(shipments).
Charles W. Chase, Jr., CPF
Advisory Industry Consultant
SAS Institute, Inc.
17
The Playbook for Defensive
Business Forecasting
Forecasting efforts can be characterized as either offensive or
defensive. When we build fancier models, or a more elaborate
process, we are practicing offensive forecasting – trying to extract
every last bit of accuracy from our forecasts. But defensive
forecasting, instead, focuses on avoiding the things that fail to
improve the forecast – or just make it worse. This presentation
outlines the playbook for defensive business forecasting. We will
begin by sharing recent research exposing the extent of harm
organizations can do to their forecasts. We will provide examples
of common practices – worst practices – that may lead to poor
forecasts. We will show how simple methods of Forecast Value
Added (FVA) analysis can be used to identify the bad practices
that plague our forecasting processes. The good news is that as
worst practices are identified and eliminated, the organization
can approach its ultimate forecasting goal: To generate forecasts
efficiently that are as accurate and unbiased as possible.
You will learn:
• How the naïve “no change” model serves as a baseline for
worst case forecasting performance
• How organizations often forecast worse than the naïve
benchmark based on research
• How many common forecasting practices can make the
forecast worse
• How to do FVA analysis, and use it to identify the worst
practices that are harming your forecasting performance
Ryan Rickard
Senior Consultant
SCMO2
Michael Gilliland
Marketing Manager
SAS
18
Augmenting the S&OP Process
Through Collaboration and
Predictive Data Science at Unilever
The S&OP Process can be significantly improved by combining
both quantitative know-how and business expertise (found within
the company) when all done in a collaborative and synchronized
fashion. With increasing data availability through technology and
the development of A. I. applications (such as Machine Learning),
the terrain is well set to receive more advanced methodologies.
For example, Neural Forecasting is an adaptive algorithm that
enables the use of multiple variables (e. g., sell-out, prices, stock in
Predictive Business, Analytics, Forecasting & Planning Conference | To Register, please call: +1 516 504 7576 or visit: https://ibf.org/events/atlanta2016
trade, promotions, and so forth) and identifies complex patterns/
relationships in order to generate more accurate forecasts. In this
session, there will be a discussion about the benefits, dangers,
and ways these techniques can be applied to your business.
Furthermore, examples from Unilever will be shared on how
successful collaboration with predictive data science can actually
be achieved, including steps to take and pitfalls to avoid.
You will learn:
• Optimal strategies to combine business know-how with
predictive data science
• How to apply Neural Forecasting to your business as its not
just for NASA
• When it makes sense to apply Machine Learning methods and
how
• How Unilever gained from this approach including benefits
and obstacles to avoid
Gustavo Rodríguez, Planning HPC Director
Unilever
Pablo Rodriguez, CEO
Forecastia
19
Step-by-Step: How to Maximize
Best Practices on Utilizing
e-Commerce and Social Media Data for
Better Forecasting & Planning
We have all heard about “Best Practices” in business. But little is
understood about how to achieve best practices in forecasting. In
this session there will be a discussion about the use and impact
of e-Commerce and website data for planning and forecasting.
We will talk about the unrealized influence of social media, global
supply, health, and other environmental or causal factors. It’s
important for each company to identify its uniqueness and how
it impacts business acumen. Forecast accuracy is a driver to most
businesses in terms of reduced inventory and cash flow. Therefore,
every company should strive to improve its forecast accuracy,
especially when risks are high. Of course, there are many methods
and suggestions available to improve performance. In this
presentation, we will help you recognize what are best practices
that can work for you and if there are “one-size fits all” methods.
You will learn:
• How to use e-Commerce and website data for better planning
& forecasting
• Best practices that will suit your unique business
• How to leverage external or environmental factors / data
like social media, health, global supply, and more for better
planning
Shower Zhang, Planning Manager
Novus International
20
Use of Social Media to
Predict Unit Sales
After a brief introduction about general business analytics, supply
chain, and forecasting, there will be a discussion about knowing
and understanding the importance of social media when it comes
to forecasting sales. Social media is a huge reservoir that can
provide a large quantity of data for making marketing, sales,
and risks predictions for the coming year; in addition, it has the
possibility of an entire decade of trend prediction. Various specific
ways on how to collect details and information that will be useful
for forecasting through social media will be discussed. A video
presentation will be shown for the trends with social media as a
operational decision making tool. Gathering such big data is an
enormous undertaking; thus, a discussion about how to manage
and properly analyze it will be highlighted in the session as well.
You Will Learn:
• The importance of social media in forecasting and operations
planning
• What are the ways to provide forecasts using social media.
• How to leverage and manage the enormous amounts of data
being collected
Hazem Shrayef, NOC Engineer
Emirates Telecommunications
Corporation Etisalat
FORECASTING & PREDICTIVE BUSINESS ANALYTICS ROUND ROBIN,
ROUND-TABLE DISCUSSIONS
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Includ ur
Yo
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it
W
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Confe ation
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Increase your networking opportunities at IBF’s Conference by joining us at our very popular 1-hour
Round Robin, Round-Table Discussion session. Take this opportunity to bring up the most challenging questions facing your team,
share your own war stories from the field and hear and share best practices. There will be up to 5 timely and practical topics
provided for your professional enhancement. These sessions will add new dimensions to the services you provide your customers,
and increase your contact base in the analytics and forecasting community. All experience levels are invited and welcome.
T OPICS:
• Technology for Analytics, Forecasting, and Planning
• Talent Management in Analytics, Forecasting, and Planning
• Analytics, Data Management, & Improving Forecast Accuracy
• New Products: Successfully Forecasting & Planning the Success of Innovation
8
Predictive Business, Analytics, Forecasting & Planning Conference | To Register, please call: +1 516 504 7576 or visit: https://ibf.org/events/atlanta2016
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BECOME A CERTIFIED PROFESSIONAL FORECASTER (CPF)
Master Demand Planning, Forecasting, and S&OP with IBF Certification
Benefits of IBF Certification
FOR EMPLOYEES:
• Accelerate your career growth, leadership opportunities,
marketability, and job security
• Validate your professional experience, knowledge, and
skill-sets in the field
• Build confidence knowing that you’re prepared for today’s
rapidly changing marketplace
• Complement your supply chain education & certifications with IBF
• Become more recognized at your company, as well as in the field
• Master demand planning, forecasting and S&OP
FOR EMPLOYERS:
• Save time and resources as IBF certified individuals are
pre-qualified, allowing you to quickly identify the right person
for a forecasting/demand planning job • Gain assurance that an IBF Certified individual has the background
to help improve forecasting performance and hit the ground running
• Increase the value of your forecasting and demand planning staff,
department, and company
• Save time and resources in training —
CPF or ACPF professionals already have a
verified body of knowledge
GET CERTIFIED AFTER THE CONFERENCE!
Please visit www.ibf.org for additional exam dates and locations.
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Supply Chain Forecasting & Planning Conference | Europe | To Register, please call: +1 516 504 7576 or visit: https://ibf.org/events/atlanta2016
P R E S E N T E R S
KEYNOTE SPEAKER | Rick Davis, Vice President, Business Intelligence | Kellogg’s
Rick has led multiple efforts for continuous improvement in demand planning, demand sensing, and technology solutions
for Kellogg USA. He also leads the Sales Technology Council for Kellogg Sales Company. Rick joined Kellogg Company in
1990 as a sales representative and has held numerous positions in field sales and HQ, in both account management and sales
management positions.
Azeem Ahmad, Enterprise Demand Planning | Dell Inc.
Azeem is a Business Planning & Operations leader with extensive cross-functional experience in strategic planning, financial
modeling, competitive analysis coupled with extensive knowledge of systems & business intelligence technologies.
He has been with Dell Inc. in various leadership roles spanning from Analytics Manager/Finance Controller/Demand Planning
Manager (Commercial Business). Currently Azeem hold the responsibility for demand planning function in the Consumer and
Small Business space. He is also leading various business transformation initiatives within Dell on streamlining and optimizing
the supply chain planning and operations. Azeem holds an MBA and an MS in Information Systems.
Manik Aryapadi, Senior Manager, Retail & Technology Practices | A. T. Kearney
Manik Aryapadi is a Senior Manager in A.T. Kearney’s Retail & Operations practices. He has led and delivered multiple
engagements in the Apparel and Footwear industries at the intersection of Planning/Forecasting, Systems Enablement,
Organization and Big Data Analytics. Manik holds a graduate degree in engineering management from Northwestern University
and a degree in electrical engineering from Texas A&M University. He is a certified Supply Chain professional.
Sara Brumbaugh, Managing Principal | Ceres Analytics
Sara Brumbaugh is Managing Principal of Ceres Analytics, where she works with companies to expand their analytic capabilities.
Sara’s roots are in business forecasting: she’s worked with the IBF for over 15 years, and is a former member of the IBF Board
of Advisors. She is also co-inventor of two patent-pending methods in predictive analytics: one in financial fraud detection, and
the other to select cancer treatments by identifying important genes in tumors.
Charles W. Chase, Jr., CPF, Advisory Industry Consultant | SAS Institute, Inc.
Charles Chase is the Advisory Industry Consultant and Subject Matter Expert for the manufacturing and supply chain global
practice at SAS. He is the primary architect and strategist for delivering demand planning and forecasting solutions to improve
supply chain efficiencies for SAS customers. He has more than 26 years of experience in the consumer packaged goods industry
and is an expert in sales forecasting, market response modeling, econometrics, and supply chain management. Chase has also
worked at the Mennen Company, Johnson & Johnson - Consumer Products Inc., Reckitt & Benckiser, the Polaroid Corporation,
Coca-Cola, Wyeth-Ayerst Pharmaceuticals, and Heineken USA. Chase is a columnist in the IBF’s Journal of Business Forecasting
and has authored several articles on sales forecasting and market response modeling. He was named “2004 Pro to Know”
in the February/March 2004 issue of Supply and Demand Chain Executive Magazine. He is also the author of Demand-Driven
Forecasting: A Structured Approach to Forecasting (2009) and coauthor of Bricks Matter: The Role of Supply Chains in Building
Market-Driven Differentiation (2012). Plus, he is a 2013 recipient of the IBF’s Lifetime Achievement in Business Forecasting &
Planning Award.
Grant Daniel, Senior Manager of Forecasting | ReddyIce Corp.
Grant is currently the Senior Manager of Forecasting at ReddyIce Corp. He has demand planning, forecasting, and supply
chain management experience on both the manufacturing and distribution sides of multiple CPG & Direct Sales companies.
He currently oversees a forecasting process that generates daily store & SKU level forecasts for over 60,000 customer locations.
In addition to his forecasting responsibilities, he is also responsible for analyzing and tracking the results several integrated
business planning initiatives. Grant holds a Bachelor of Science degree in Economics from Brigham Young University – Idaho.
Arya Eskamani, Senior Predictive Analyst | Restaurant Services Inc.
Arya Eskamani currently holds the role of Senior Predictive Analytics Analyst for Restaurant Services, Inc. where he is responsible
for all complex analytical and forecasting projects. He has over five years of experience applying predictive analytics in a variety
of professional fields including technology, healthcare, and manufacturing. Arya received his Bachelors in Business Economics
from the University of Central Florida and a M.S. in Economics from Florida Atlantic University.
Dean W. Face, Ph.D., Business Process Manager | DuPont
Dr. Face is currently a Business Process Manager and Six Sigma Master Black Belt at DuPont in the Corporate Integrated Business
Effectiveness (CIBE) organization. His current work is focused on the development and optimization of statistical forecasting
methods for demand planning in a range of DuPont businesses on a global basis. Work also includes the development of
business specific Composite Leading Indicator (CLI) models based on a wide range of global economic leading indicators to aid
in the demand planning process. Previous experience includes R&D and program management in the areas of superconductivity,
electronic materials, thin films, and electronic devices. Dean was a postdoctoral fellow at MIT and has a Ph.D. in Applied Physics
from Yale University and a B.S. in Electrical Engineering from Caltech.
Allan Gray, Co-Founder, | End-to-End Analytics
Allan Gray is Partner and Co-Founder at End-to-End Analytics, where he leads the Consumer Goods and Retail practice. He is
currently helping several of the world’s leading consumer goods manufacturers and retailers to deploy cutting-edge analytics to
improve forecasting, optimize pricing and promotions, and streamline their supply chains. Allan holds an MEng with First Class
Honors from Oxford University, an MBA from Stanford University, and was a Kennedy Scholar at MIT.
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Michael Gilliland, Product Marketing Manager | SAS Institute Inc.
Predictive Business, Analytics, Forecasting & Planning Conference | To Register, please call: +1 516 504 7576 or visit: https://ibf.org/events/atlanta2016
Michael Gilliland is Marketing Manager for SAS forecasting software, author of The Business Forecasting Deal, and co-editor
of Business Forecasting: Practical Problems and Solutions. He has published articles in Journal of Business Forecasting, Supply
Chain Management Review, Analytics, Supply Chain Forecasting Digest,APICS Magazine, Swiss Analytics Magazine, and in
Foresight: The International Journal of Applied Forecastingwhere he is also editor of the Forecasting Practice section. Mike
holds a BA in Philosophy from Michigan State University, and Master’s degrees in Philosophy and Mathematical Sciences from
Johns Hopkins University.
Russell Halper, Sr. Consultant | End-to-End Analytics
Russell Halper has devoted his career to developing cutting-edge analytical solutions to problems in supply chain, manufacturing,
and marketing. His background includes work with companies in CPG, retail, silicon chip manufacturing, and consumer
electronics. This includes solving problems in promotions forecasting, capacity planning, production planning, labor planning,
scheduling, network design, inventory analysis, and transportation optimization. Prior to joining End-to-End, Russell was a
member of an internal supply chain consulting group at Nestlé. He holds a Ph.D. in Applied Mathematics from the University of
Maryland and is the author of several academic papers on topics ranging from transportation optimization to sports scheduling.
Mike Higgins, Director—Investor Relations & Business Strategy | Advanced Drainage Systems (ADS)
Greg Klaus, ACPF, Supply Chain Project Manager | Medtronic
Greg has 20 years of supply chain experience in industry and consulting. His employers have included Best Buy, Deloitte
Consulting, and Medtronic, Inc. In addition, he has served as a consultant to Guidiant Vascular and CRM (now Boston Scientific),
U.S. Cellular, Levi Strauss and Company, and Deluxe Checking. The supply chain industries he has served include medical
device, retail, and telecom. Greg has an MBA from the University of Minnesota and a BA from the University of Wisconsin. His
certifications include: IBF – ACPF; APICS - CPIM, CSCP, SCOR-P; and PMI - PMP, PMI-ACP.
Michael Mercedes, Former Program Manager, Global Healthcare | Ecolab
Mike Mercedes has been in Healthcare Supply Chain at Ecolab for nearly nine years. After playing a leadership role in the the
implementation of Lean Six Sigma, Mike was appointed the Program Manager to lead the design and implementation of S&OP
for Ecolab Healthcare’s North American Medical Device Supply Chain. Prior to that, Mike worked for three years at General
Electric’s Global R&D Headquarters before making the switch to Supply Chain. He graduated from the University of Notre Dame
with a degree in Chemical Engineering.
Edgar Núñez, Senior Economist / SME of Forecast & Market Analysis | General Motors
Edgar Nuñez serves as Senior Economist and expert of Forecast & Market Analysis at General Motors in Mexico. He is responsible
for developing industry forecasting assumptions and monitoring the economy. His activities affect the company’s budget and
business plan in the next 10 years. In 2014, Edgar was appointed as Operational Excellence leader. His first initiative, an optimal
vehicle inventory model, increased profit by more than $30 million dollars, helping to mitigate S&OP risks in the short term.
Before joining GM, Edgar served as Junior Economist at Ternium, Research Associate at the Inter-American Development Bank,
and Analyst of the Ministry of Finance of Mexico. He holds a Bachelor degree of science in economics from Tecnologico de
Monterrey (ITESM), a graduate certificate in business and economics from Tilburg University, and is currently pursuing a CFA
designation from the CFA Institute.
Dave Pappentick, Sr. Project Manager, Global Commercial Forecasting | Merck & Co., Inc.
Dave is currently working in the Global Commercial Forecasting group supporting inline demand forecasting and cross divisional
projects at Merck. He has five years of experience in pharmaceuticals and over ten years of project management experience
across the manufacturing and advertising industries. Over the past year and a half, Dave has worked to deliver a new supply
chain management tool, with responsibility for the demand planning work stream within the project. Dave has a B.S. in
Information Systems from Elizabethtown College and an MBA from DeSales University.
Gary W. Patterson, CEO | FiscalDoctor, Inc.
Known as the Fiscal Doctor, Gary has helped over 200 international companies in manufacturing, technology, service,
construction, and distribution. Ranging from start-ups to Inc. 500 (twice) to Fortune 500 firms, several of the companies reached
10-times compounded annual revenue growth. He was the European coordinator for a Global supply chain re-engineering
software application for Robertson CECO, a Fortune 500 company. Gary has successfully negotiated over 25 mergers and
acquisitions with a market value exceeding $390 million. Patterson is the author of several books and speaks on enterprise risk
management, risk analysis, leadership, and strategic budgeting. He holds an MBA in Finance and Operations from Stanford, a
BBA in Accounting from the University of Mississippi, and is a Big 4 CPA, and NSA speaker.
Ryan Rickard, Senior Consultant | SCMO2
Gustavo Rodríguez, Planning HPC Director | Unilever
Gustavo is currently director of Supply & Demand Planning in the Southern Cone for Unilever, one of the biggest FMCG
companies in the world. He has more than 23 years of experience working in Supply Chain (from supervisor to director).
Gustavo has an extensive background in manufacturing, demand & supply management, Sales & Operations Planning, change
management, and process transformation. Since 2011, he has been leading a change management process for planning in the
Southern Cone making a step change in innovation, supply, demand, and S&OP. He is also part of the team that is transforming
planning for Unilever globally.
11
Predictive Business, Analytics, Forecasting & Planning Conference | To Register, please call: +1 516 504 7576 or visit: https://ibf.org/events/atlanta2016
Pablo Rodriguez, CEO | Forecastia
Pablo is the founder and CEO of Forecastia, an Argentine-based company that provides quantitative solutions (both products
and services) to improve the S&OP / IBP processes in medium-to-big companies. He is also the co-founder in Continente Siete,
the Supply Chain data science group that owns Forecastia, founded in 2008. He previously developed quantitative consulting
projects within the ITBA University based on analytical methodologies. Pablo has also been a professor in ITBA University since
2005 and owns a MOOC in multi-paradigm simulation at Acámica. He has also trained more than 150 demand planners and
managers in quantitative demand forecasting.
Rene Saroukhanoff, CPF, Senior Director of Merchandise Planning Reporting & Analytics | Levi’s
Rene Saroukhanoff is the Senior Director of Merchandise Planning Reporting & Analytics at Levi Strauss & Company. He is
currently responsible for building and executing all product-related reporting and analytical needs, including special projects
related to targeted growth initiatives, inventory and sizing optimization, and delivering advanced visualization capabilities. Rene
has over 15 years of experience in the apparel industry in multiple leadership roles and functions. He has a degree in business
from the University of Southern California and is an IBF Certified Professional Forecaster (CPF).
Greg Schlegel, Adjunct Professor, Supply Chain Risk Management | Lehigh University
Greg has over 25 years of experience with several Fortune 100 companies across multiple industries. He has held executive
positions in the systems, staff and plant operations environments and has been Supply Chain Director, Materials Director, Logistics
Manager, Plant Operations Manager, CIO and Systems Director with companies such as Hercules Chemical, Sandvik Specialty
Steel, International Harvester, Schlumberger, Loral Aerospace & Defense Electronics, GAF/ISP Specialty Chemicals and IBM
Supply Chain Solutions. Greg has also been an Executive Consultant for IBF and is presently VP Business Development/Principal
for SherTrack LLC, an “SES”, Software-enabled-Services organization providing Demand-Driven Predictive Manufacturing
solutions. He has also implemented CPFR, collaborative planning, forecasting and replenishment systems, S&OP Processes,
and more. Greg was APICS’ 1997 International Society President. He is a frequent speaker at IBF conferences and seminars,
globally. He has published articles in Supply Chain Management Review, IBF’s The Journal of Business Forecasting, Logistics
Magazine Distribution & Transportation Report, APICS Performance Advantage, Hospital Materiel Management Quarterly,
IOMA Newsletters, AIIE, ISSSP the Six Sigma Organization, WCBF Six Sigma, Asia Auto Focus magazine and ORSA/TIMS, now
INFORMS. He is presently teaching MBA supply chain risk management at Lehigh University in the Graduate Program. He is a
graduate of Penn State, holding a B.S. in Operations Research and Computer Science, and has attended Lake Forest College
of Graduate Studies.
Hazem Shrayef, NOC Engineer | Emirates Telecommunications Corporation Etisalat
Hazem is currently working as a Telecommunications NOC Engineer at the Emirates Telecommunications Corporation,
commonly referred to as Etisalat. There he works with design, analysis, quote preparation, documentation, and approval for all
projects and services that are related to Etisalat’s network. Earlier, Hazem worked with analyst sales engagement, intelligence
and forecasting mainly as a liaison with the municipality, the economic department, and real estate developers to collect
information on planned building projects and expansions to incorporate in the forecasts. Prior to that he had three years of
experience in telecommunications industry where his duties were to recognize, follow, and analyze trends in the market by
researching historical data to map trends and determine how they will influence the business.
Adam Siegel, CEO and Founder | Cultivate Labs
Adam founded Cultivate Labs, whose prediction markets are used in the public and private sectors to help progressive leaders
leverage the collective wisdom of their own people to make more informed decisions. Prior to that, he co-founded Inkling
Markets, a Y Combinator startup that sought to improve the accuracy of forecasting processes using prediction markets. He
also worked for 10 years as a consultant at Accenture, leading a research initiative around next generation user experiences and
advising a wide array of clients ranging from Intel to the U.S. Department of Agriculture on digital strategy. Adam received his
B.A. in political science from Indiana University.
Rich Wagner, Founder and CEO | Prevedere
With an extensive background in IT strategy and innovation, Rich Wagner has seen first-hand the power that external big
data can bring to a company’s financial performance. Today, as president and Chief Executive Officer at Prevedere, Rich
helps companies to look beyond their own walls for key external drivers of financial performance. Utilizing millions of global
metrics from data powerhouses like Nielsen, NASDAQ and the Federal Reserve, Rich has uniquely positioned Prevedere as a
complementary solution to existing forecasting platforms by correlating external economic factors to corporate performance.
Combining the power of big data, machine learning and predictive analytics, Prevedere drives unprecedented forecast accuracy.
Under Rich’s leadership, Prevedere has been named a “Cool Vendor in Information Innovation” by Gartner and an FP&A
Innovation Awards winner in Forecasting and Planning.
Randy Wilp, Leader of Global Commercial Forecasting | Merck & Co., Inc.
Randy is currently Leader of Global Commercial Forecasting at Merck. Prior to Merck, Randy has held leadership positions in
forecasting and predictive analytics for companies such as Pharmacia and Bristol-Myers Squibb. Randy has also founded his own
international forecast consulting company as well as managed forecast consulting practices within other consulting companies.
Randy has an MBA, MS-IS, and BSBA-Accounting from the University of Missouri.
Yidan Xia, Revenue Science Analyst | Fedex
Yidan has four years of business forecasting experience and two years of work experience in FedEx’s forecasting department.
As an analyst in FedEx’s business forecasting department, Yidan develops FedEx Ground surcharge revenue forecasts for helping
formulate pricing strategies. The forecasts are regularly presented to the management chain as well as senior management.
She is specialized in predictive analytics and proficient in time series models for forecasting aimed at estimating dynamic causal
effects. She is experienced in ARIMA, VAR, ARDL, Exponential Smoothing Models, Unobservable Component Models, and
dealing with nonstationary processes and co-integration in ECM and VECM using SAS, STATA or R.
Shower Zhang, Planning Manager | Novus International
Ms. Zhang is the Senior Manager of Global Demand Planning for Novus International, Inc., a leading global animal nutrition and
health company with headquarters in St. Charles, Missouri. She is currently tasked with creating a global integrated demand
planning solution to improve forecasting while optimizing inventory investment. Ms. Zhang has a diverse background in supply
chain management with extensive experience in plant operations, supply chain planning, and inventory management across
the agriculture and automotive industries. Shower holds a BS degree in Chemical Engineering from Jianghan University and an
MBA with emphasis on Operations Management from Peking University.
12
Predictive Business, Analytics, Forecasting & Planning Conference | To Register, please call: +1 516 504 7576 or visit: https://ibf.org/events/atlanta2016
WE DN ESD AY | A PRIL 20, 2 0 1 6
12:30 pm – 1:30 pm
PRE-CONFERENCE WORKSHOP REGISTRATION
1:30 pm – 4:30 pm
PRE-CONFERENCE WORKSHOP: PREDICTIVE BUSINESS ANALYTICS & BIG DATA
WITHIN THE SUPPLY CHAIN AND OPERATIONS (IBF MEMBERS ONLY)
5:00 pm – 7:00 pm
EARLY CONFERENCE REGISTRATION | VISIT WITH EXHIBITORS
T H U RSD AY | A PRIL 21, 20 1 6
7:00 am – 8:00 am
MORNING REFRESHMENTS & REGISTRATION | VISIT WITH EXHIBITORS
8:00 am – 8:15 am
WELCOME & OPENING REMARKS
8:20 am – 9:15 am
1 Nursing Your Inventory and Operations Back to Health:
A Three-Step Process
Michael Mercedes
Former Program Manager, Global Healthcare
Ecolab
9:20 am – 10:15 am
3 The Quadrant Analysis: A Strategic Approach to ABC Finished Goods
Product Segmentation
Greg Klaus
Supply Chain Project Manager
Medtronic
10:15 am – 10:30 am
10:30 am – 11:25 am
5 Data Analysis: A Double-Edged Sword
Grant Daniel
Senior Manager of Forecasting
ReddyIce Corp.
6 Machine Learning: Forecasting with Artificial Neural Networks
Arya Eskamani
Senior Predictive Analyst
Restaurant Services Inc.
7 Demand Planning & Forecasting for Non-Transactional Products—Review
& Best Practices
Azeem Ahmad
Enterprise Demand Planning
Dell Inc.
8 How to Use Size Forecasting, Optimized Allocation, and Visual Analytics from
Levi’s Strauss & Company
Rene Saroukhanoff, CPF, Senior Director of Merchandise Planning Reporting & Analytics
Levi’s
Manik Aryapadi, Senior Manager, Retail & Technology Practices
A. T. Kearney
11:30 am – 12:25 pm
12:30 pm– 1:00 pm
KEYNOTE PRESENTATION | The Promise of Analytics – The Art of the Possible
Rick Davis
Vice President, Business Intelligence
Kellogg’s
1:00 pm– 1:45 pm
1:45 pm – 2:15 pm
3:15 pm – 4:10 pm
MORNING BREAK | VISIT WITH EXHIBITORS
LUNCH
2:15 pm –3:10 pm
VISIT WITH EXHIBITORS
9 Improved Profitability from Data-Driven Decision Making
Edgar Núñez
Senior Economist / SME of Forecast & Market Analysis
General Motors
10 Prediction Success & Preventing Business Failure: Using Your Own People to
Crowdsource Strategic Decisions
Adam Siegel, CEO and Founder
Cultivate Labs
11 Application of Predictive Business Analytics in E-Commerce, Marketing,
and Influencing Product Demand
Yidan Xia, Revenue Science Analyst
Fedex
12 Using Decision Trees for Market Segmentation in Forecasting
Sara Brumbaugh
Managing Principal
Ceres Analytics
4:10 pm – 4:30 pm
AFTERNOON BREAK | VISIT WITH EXHIBITORS
4:30pm – 5:30 pm
ROUND ROBIN ROUNDTABLE DISCUSSIONS
5:30 pm – 6:30 pm
IBF COCKTAIL RECEPTION
FRIDAY |
| A PRIL 22, 20 1 6
7:00 am – 8:00 am
8:00 am – 8:55 am
9:00 am – 9:55 am
MORNING REFRESHMENTS & REGISTRATION | VISIT WITH EXHIBITORS
13 The Proactive Enterprise: How to Generate Actionable Insights with
Predictive Analytics
Mike Higgins, Director—Investor Relations & Business Strategy
Advanced Drainage Systems (ADS)
Rich Wagner, Founder and CEO
Prevedere
15 Getting C Suite Engagement (& Support) for Predictive Analytics,
Forecasting and Planning Initiatives
Gary W. Patterson, CEO
FiscalDoctor, Inc.
9:55 am – 10:10 am
10:10 am – 11:05 am
17 The Playbook for Defensive Business Forecasting
Ryan Rickard, Senior Consultant
SCMO2
Michael Gilliland, Marketing Manager
SAS Institute Inc.
11:10 am – 12:05 pm
19 Step-by-Step: How to Maximize Best Practices on Utilizing e-Commerce
and Social Media Data for Better Forecasting & Planning
Shower Zhang,
Planning Manager
Novus International
12:05 pm – 12:20 pm
2 Creating Understandable Analytics to Inform New Product Forecasts
Randy Wilp, Leader of Global Commercial Forecasting
Merck & Co., Inc.
Dave Pappentick, Sr. Project Manager, Global Commercial Forecasting
Merck & Co., Inc.
4 How to Optimize Statistical Forecast Models within your
System for Demand Planning
Dean W. Face, Ph. D.
Business Process Manager
DuPont
14 Using Predictive Analytics to Accurately Forecast Sales from Electronic
Marketing & Traditional Promotional Activities
Russell Halper, Sr. Consultant
End-to-End Analytics
Allan Gray, Co-Founder
End-to-End Analytics
16 Using Downstream Data to Improve Forecast Accuracy and Determining the
Quantitative Impact of our Sales and Marketing Programs
Charles W. Chase, Jr., CPF, Advisory Industry Consultant
SAS Institute, Inc.
MID-MORNING BREAK | VISIT WITH EXHIBITORS
18 Augmenting the S&OP Process Through Collaboration and Predictive Data
Science at Unilever
Gustavo Rodríguez, Planning HPC Director
Unilever
Pablo Rodriguez, CEO
Forecastia
20 Use of Social Media to Predict Unit Sales
Hazem Shrayef
NOC Engineer
Emirates Telecommunications Corporation Etisalat
CLOSING REMARKS & GIVEAWAYS
CONF EREN CE CON CL UDE S
SATURDAY | APRIL 23, 2016 | EXAM DAY 8:15am – 4:30pm | IBF CERTIFICATION DAY | CPF & ACPF GOOD LUCK!
13
A P R I L 2 2 – 2 4 2 0 1 5 | AT L A N TA , G E O R G I A U S A
PREDICTIVE BUSINESS ANALYTICS
FORECASTING & PLANNING CONFERENCE
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Non-Members: m $375 (USD) per exam IBF Members:
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