A beverage manufacturer needed to accurately forecast daily empty bottle returns for 10 SKUs to optimize production planning. They developed predictive models using 2 years of returns data and techniques like ARIMA, Holt Winters, and year-on-year growth. The models achieved 75% accuracy on average for May-June 2011 forecasts, and 92% accuracy for the highest-return SKU specifically. This significantly improved upon existing forecasting methods.

1. Business Situation:
Client’s 70% to 80% of daily beverage production depends on empty bottle returns from previous day. As such, a highly accurate forecast
for daily bottle returns across all SKU’s was required for optimal production planning.
The Task:
Design, develop and implement a predictive model that will help in forecasting daily empty bottle returns for 10 different SKUs.
Analytical Framework:
Data preparation for model building. Past sales data or production data didn't have much effect on the returns data and thus past 2 years
return data was used for the model building. Different models like ARIMA, Holt Winters, Year on Year growth model were built to forecast the
returns.
The Result:
• For all the SKUs considered, an accuracy of 75% was achieved for May-June 2011. This was significantly better than existing forecasts.
• For the SKU which contributed to 47% of the total returns, an accuracy of 92% was achieved for May-June 2011. The monthly accuracy for
May2011 being 85% and June 2011 being 97%.
Analytics in Action
Towards Better Production Planning by Accurate Forecasting
Client: A Leading Carbonated Beverage Manufacturer
Defining
Modelling
universe
Model
development
Validation
Past 2 years empty bottle returns data was
considered. The data was too volatile to fit
into the model and thus Centralized
Moving Averages was calculated to
smoothen the data and to get a better
model fit.
ARIMA model was built on Centralised
moving averages , Holt winters and Year on
Year growth rate models was built on
empty bottle returns. Bootstrapping
method was applied to choose best
forecast value.
May and June forecasts were compared
against actuals. Accuracy was calculated at
a daily-level for all SKU’s
-
5,000
10,000
15,000
20,000
25,000
30,000
5/1/2009
5/23/2009
6/14/2009
7/6/2009
7/28/2009
8/19/2009
9/10/2009
10/2/2009
10/24/2009
11/15/2009
12/7/2009
12/29/2009
1/20/2010
2/11/2010
3/5/2010
3/27/2010
4/18/2010
5/10/2010
6/1/2010
6/23/2010
7/15/2010
8/6/2010
8/28/2010
9/19/2010
10/11/2010
11/2/2010
11/24/2010
12/16/2010
1/7/2011
1/29/2011
2/20/2011
3/14/2011
4/5/2011
4/27/2011
5/19/2011
6/10/2011
2009
Dailyreturns
Actuals
Forecasts
Model Build on 2009 and 2010 data Model Application for May-June11
2009 2010 2011
-
5,000
10,000
15,000
20,000
25,000
30,000
35,000
1-May-11
3-May-11
5-May-11
7-May-11
9-May-11
11-May-11
13-May-11
15-May-11
17-May-11
19-May-11
21-May-11
23-May-11
25-May-11
27-May-11
29-May-11
31-May-11
2-Jun-11
4-Jun-11
6-Jun-11
8-Jun-11
10-Jun-11
12-Jun-11
14-Jun-11
16-Jun-11
18-Jun-11
20-Jun-11
22-Jun-11
24-Jun-11
26-Jun-11
28-Jun-11
30-Jun-11
DailyReturns
Actuals
Forecast

2. YOUR PARTNER FOR
DATA ANALYTICS SERVICES
MANAGEMENT TEAM
GLOBAL EXPERIENCE.
PROVEN RESULTS.
Roy K. Cherian
CEO
Roy has over 20 years of rich experience in marketing, advertising and media
in organizations like Nestle India, United Breweries, FCB and Feedback
Ventures. He holds an MBA from IIM Ahmedabad.
Anunay Gupta, PhD
COO & Head of Analytics
Anunay has over 15 years of experience, with a significant portion focused
on Analytics in Consumer Finance. In his last assignment at Citigroup, he was
responsible for all Decision Management functions for the US Cards
portfolio of Citigroup, covering approx $150B in assets. Anunay holds an
MBA in Finance from NYU Stern School of Business.
Greg Ferdinand
EVP, Business Development
Greg has over 20 years of experience in global marketing, strategic planning,
business development and analytics at Dell, Capital One and AT&T. He has
successfully developed and embedded analytic-driven programs into a
variety of go-to-market, customer and operational functions. Greg holds an
MBA from NYU Stern School of Business.
Kakul Paul
Business Head, CPG
Kakul has over 6 years of experience within the CPG industry. She was
previously part of the Analytics practice as WNS, leading analytic initiatives
for top Fortune 50 clients globally. She has extensive experience in what
drives Consumer purchase behavior, market mix modeling, pricing &
promotion analytics, etc. Kakul has an MBA from IIM Ahmedabad.
ADVANCED ANALYTICAL SOLUTIONS
MARKETELLIGENT, INC.
80 Broad Street, 5th Floor, New York, NY 10004
1.212.837.7827 (o) 1.208.439.5551 (fax) info@marketelligent.com
CONTACT www.marketelligent.com
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