Application of Decision Sciences to Solve Business Problems in the Consumer Packaged Goods (CPG)...

7/29/2019 Application of Decision Sciences to Solve Business Problems in the Consumer Packaged Goods (CPG) Industry

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Application of Decision Sciences

to Solve Business Problems

CPG Industry
http://www.marketelligent.com/home/


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Analytics

for CPG


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New Product

Launches &Innovation

Need Gap Analysis

t is an approach to identify the unmet needs of consumers, in which respondents are asked to envisage

deal brand or product, and then to rate various existing brands or products on key attributes. If there ar

existing brands measuring up to the ideal, there exists a need gap which could be a potential for a

product.

t provides answers to critical business questions like:

What is the consumersperception of the brand/product?

What are the consumer needs yet to be catered to and are there competitors providing alternatives?

Identify new consumer segments and market potential for a new product.

What is the brand image in the consumersmind? If needed, how is it to be re-branded and re-position

Needs

Satisfaction

High

Low

HighLow

Hygiene needs

Unmet needs

Satisfied needs

Underdeveloped needs

Has enjoyable flavour

Cleans thoroughly

Provides fresh breath

Whitens teeth

Has anti-cavity action

Has anti-

bacterial actionSoothes gum

irritation,

inflammation andbleedingRelieves

teeth

sensitivity

Controls tartar

Strengthens

enamel


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oduct & Concept Testing

PI Believability Uniqueness Value

Disclose technical

formula

DEL DEL MNB MB

Sensory ingredients IND DEL IND DEL

Natural ingredients IND DEL IND DEL

Easy to apply IND HYG

DEL = Delight

IND = Indifferent

TRNF = Turnoff

MNB = Must not be

MB = Must beHYG = Hygiene

New Product

Launches &Innovation

Product & Concept Testing

Estimate the market potential of an idea or a concept, before actually developing the product base

consumer response on multiple metrics like: uniqueness, believability, feasibility, price, desirab

advantages, disadvantages, etc.

Only successful concepts pass to the next phase, thereby minimizing R&D and marketing costs.

Apart from estimating the market potential, it also helps:

Identify critical success factors for a new product/service

Estimate price sensitivity and purchase likelihood

Bundle product/service features

Identify potential consumer segments and assess competition

Understand the purchase process and decision making

Optimize advertising messages and improve promotional offers

Statistical techniques (like Conjoint analysis, Discrete choice modeling, KANO analysis) are applied on

consumer responses collected.


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Supply Chain

SKU rationalization exercise is usually

supplemented with an impact study to

answer questions like: What is the revenue impact associated

and how can it be minimized?

What is the inventory carrying impact

and overall savings?

Will it result in consumer dissatisfaction?

What is the consumer reactivation rate

on rationalized SKUs?

Is the product seasonal? What is the time

frame to rationalize the category?

What are the substitute products thatthe consumer can be offered?

Cumulativ

eRevenue

85%

Top Selling

CumulativeRevenue

SKU in order of

decreasing Reve

Contribution

100%

98%

80%

Top Mid Bottom

Recommended for Rationalizatio

80%

Mid Selling

Cumulativ

eRevenue

SKU Rationalization

The objective of SKU rationalization is to reduce the business complexities arising from a burgeoning pro

portfolio, from managing too many items, product life cycles, consumer preferences, etc., while ensu

consumer satisfaction. It is the process of re-looking at the product portfolio and optimizing it.

t starts with the parameters that form the basisidentifying and retaining high margin SKUs, high vo

SKUs, SKUs that have a higher shelf life and those which are in tune with consumer preferences.

After analyzing the cost drivers for each SKU, the portfolio can be assorted and rejected products can b

evaluated for further action (merge, sell, milk or kill).


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Pricing: Competitive pricing

(comparable to other vendors),

stability (low variance), accuracy,advance notice of price changes.

Quality: Compliance with purchase

order, conformity to specifications,

reliability (rate of product failures),

durability, support, warranty.

Delivery: Time, quantity, lead time,

packaging, emergency delivery and

technical support.

Partner Strategic Fit Brand Equity Financial HealthAbility to

operationalizeFinal Score Status

Vendor 1 9 8 10 7.4 8.75 Pass

Vendor 3 10 9 8 7.4 9.00 Pass

Vendor 3 10 7 6 7.4 7.50 Pass

Vendor 4 10 10 8 10.0 9.50 Underleverag

Vendor 5 9 7 8 7.4 7.75 Pass

Vendor 6 2 7 6 8.2 5.50 Risky

Partner Filtration Methodology & Process Flow

Supply Chain

Vendor Management

t enables organizations to control costs, strive towards service excellence and mitigate risks to gain incre

value from their vendor by:

Minimizing potential business disruption

Avoiding deal and delivery failure

Improving operational efficiencies, controlling costs and planning of workforce and labor

t includes vendor identification, recruitment, monitoring, tracking and evaluating vendors on certain KPI


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INSOURCEHigh

Demand Flexibility?

Low

High

OUTSOURCE

Low

Competitive advantage?

Capability of

supplier

Process ma turity of

supplier

Strategic risk with

supplier

IMPLEMENT

OUTSOURCE

High High Low

Low

Establish norms for product

quality, process for transferring

knowledge & monitor quality

tracking measures

Establish process monitoring

measures, plans to

continuously improve process

and knowledge sharing across

teams

Actions Actions

Low

High

Ensure flexibility and penalty

clauses are established for

product delivery, establish

alternate source of activity and

divulge as little proprietary

information as possible.

Actions

Establish control need based on

three secondary factors,

develop appropriate

contracting relationship type

and negotiate contract

Supply Chain

Sourcing Strategy & Production Planning

Strategic sourcing continuously improves and re-evaluates the purchasing activities of a company. Sou

optimization helps evaluate different procurement inputs by considering supply market, specific supply c

conditions, individual supplier conditions and offers alternatives to address the buyerssourcing goals.

t helps in:

Assessing the supply market, the companysspending and identifying suitable suppliers

Optimizing production related sourcing decisions, concerning where to produce or source prod

based on a total supply chain cost analysis

Selecting a suitable manufacturing site, optimal capacity utilization of plants and product alloca

among the different plants and distribution centers

Strategic planning for manufacturing and inventory optimization

Increasing manufacturing and distribution asset utilization


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Project Area Identified Savings (to date)

Transportation 16%

Warehouse 12%

Supply Chain 3%

Total 15%

Supply Chain

Network Optimization

Network optimization helps in designing the optimal supply chain network with the lowest total

structure, given operational constraints. It uses statistical modeling to describe the transport network t

followed. It helps senior management in making the most efficient use of resources while identifying

most economical routes.

t aids in:

Reducing transportation overheads and ensuring that the right product reaches the right locatio

time

Improving transportation mode selection, load consolidation and resource utilization

Quantifying operational, financial costs of alternative networks and identifying scopes of improveme

Ensuring reduced freight costs and increased operating efficiency

Streamlining warehouse activities, thereby reducing time to dispatch and optimizing productivity leve


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Lead time : It is the time lag between

when the order is placed and the point at

which the stocks are available; A lead

time of 4 days implies that there should

always be stock for 4 days supply to avoid

stock-out scenario

Safety stockis the buffer quantity to

cover any unplanned excess requirement

taking into account delivery delays

Reorder pointis the minimum level of

stock at which procurement should be

triggered and quantity of warehouse

stock should never go below this point

If the quantity of warehouse stock is less

than re-order point, there is shortfall

Stock

TimeRelease date

Safety

Stock

Reorder

point

Availability date

Lot size

Replenishment

lead time

Supply Chain

nventory Management

Optimal inventory management is an indispensable function to ensure un-interrupted product supp

meet the changing demand. Stock out analysis helps in:

Optimizing inventory and service levels by streamlining ordering processes

Minimizing stock outstock out can lead to loss of sales

Handling overstockoverstock leads to increased inventory costs and costs to liquidate excess inven

Maximizing warehouse space utilization

Lead time is the time lag between when the order is placed, and the point at which stocks are available.

buffer quantity to cover any unplanned excess requirement, taking into account delivery delays, is referre

as safety stock. Providing for safety stock on top of lead time demand, will give the re-order point, whi

the minimal level of stock at which procurement should be triggered. Warehouse stock should neve

below the re-order point. Re-order point will assist in deciding what would be the best optimal o

quantity and when to place an order.


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States

States

States

States

Zones

YTD

MOM

Salience

Brand share

YOY

States

Zones

States

Zone

Increase in brand share

Decrease in brand share

No change in brand share

25.6, 61.3

6.5, 56.54.4, 78.1

16.8, 79.7

12.3, 73.3

8.3, 76.0

1.0, 66.7

10.9, 84.8

0.3, 82.7

3.0, 50.5

2.5, 60.0

0.2, 65.2

1.0, 33.9

1.0, 61.9

0.2, 68.7

% Salience, %Brand Share

Sales & Channe

Planning

Sales Tracker

Constant monitoring and tracking provides the sales team with accurate information related to ma

dynamics, so that they can have an action plan before the next sales cycle starts. Also, it serves as the

for formulating sales strategies. It:

Identifies which products and SKUs are selling the most

Analyses market trends and geographic buying patterns

Evaluates growth potential for product portfolio (products, regions, markets)

Identifies the epicenter for market share lossRoot-cause analysis

nteractive visual dashboards on market performance across geographies provide further assistance

analyzing large volumes of data.


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0.0

1.0

2.0

3.0

4.0

5.0 Actual Sales Forecasted Sales Base Line Sales

Millionc

asessold

Sales & Channe

Planning

Sales Forecasting

A good demand forecast helps improve sales volume, cash flow and hence the profitability, by optim

nventory and by minimizing out-of-stock. Besides considering historicaldata, external factors like promo

seasonality, price changes, macro-economic conditions are also considered for more accurate forecas

helps create better solutions for:

Inventory Control: Optimizing inventory & service levels by streamlining ordering processes

Minimizing Out of Stock: Out of stocks equal lost sales which can have a negative impact on sales

Improving product freshness & warehouse efficiency: Too much inventory can result in excess exp

inventorythat must be liquidated at or below cost, which is a cash flow drain

Maximizing warehouse space utilization: As SKU proliferation continues, forecasting can help maxi

the use of warehouse space

Capitalizing on peak sales weeks: Accurate forecasting ensures the right product mix to take

advantage of operational capacity and peak market demands

Statistical techniques (like Moving Average, Holt Winters, Regression, ARIMA) are applied on historical da


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53.2

44.0

30.4

20.4 19.1 18.3

0

10

20

30

40

50

60

70

0

5

10

15

20

25

30

35

$0.90

to

$0.98

$0.99 $1.00

to

$1.08

$ 1.0 9 $ 1.1 0

to

$1.18

$1.19 $1.20

to

$1.28

$ 1.2 9 $ 1.3 0

to

$1.38

$ 1.39 $ 1.4 0

to

$1.48

$1.49

% ACV Brand A sales rate

Identify price threshold

0

10

20

30

40

50

60

70

80

90

100

110

120

Wk-1('09)

Wk-4('09)

Wk-7('09)

Wk-10('09)

Wk-13('09)

Wk-16('09)

Wk-19('09)

Wk-22('09)

Wk-25('09)

Wk-28('09)

Wk-31('09)

Wk-34('09)

Wk-37('09)

Wk-40('09)

Wk-43('09)

Wk-46('09)

Wk-49('09)

Wk-52('09)

Wk-3('10)

Wk-6('10)

Wk-9('10)

Wk-12('10)

Wk-15('10)

Wk-18('10)

Wk-21('10)

Wk-24('10)

Wk-27('10)

Wk-30('10)

Wk-33('10)

Wk-36('10)

Wk-39('10)

Wk-42('10)

Wk-45('10)

Wk-48('10)

Wk-51('10)

Wk-2('11)

Wk-5('11)

Wk-8('11)

Wk-11('11)

Wk-14('11)

Wk-17('11)

Wk-20('11)

Wk-23('11)

Wk-26('11)

Wk-29('11)

Wk-32('11)

Wk-35('11)

Wk-38('11)

Wk-41('11)

Wk-44('11)

Wk-47('11)

Wk-50('11)

Price index vs. competition Volume share

Optimum price corridor

Identify optimum price corridor

Sales & Channe

Planning

Pricing Analysis

Pricing strategies are crafted to meet two key objectives: profit and revenue maximization. It help

dentifying the best pricing strategy in a dynamic market, in response to the competitive scenario, by:

Evaluating the brandsown price elasticity and competitor brandscross price elasticity

Identifying price gaps/thresholds which can result in significant share changes for the brand

Identifying the right price gap/threshold with respect to the key competitors


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Simulator for effective allocation of trade spends

Sales & Channe

Planning

Promotional Effectiveness

Promotions provide great value for brand through both incremental sales and increased brand awarene

s a technique of evaluating the extent of success of an activity using past data, by correlating the sales

and marketing efforts. Main objective is to assess the impact and effectiveness of promotions.

Trade promotion optimization (TPO) utilizes advanced econometric modeling techniques to help br

refine their promotion strategies, identify the right price and discount point that maximized sales lift and

and eventually help manufacturers enlarge their consumer basket and have a sustained impact on base

sales.

TPO helps companies:

Allocate more for promotion sensitive brands and SKUs

Collaborate with retailers and restructure their trade programs

Design unique programs specific to a retailer/channel instead of following a one-size fits allapproa


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Streaming Sales Data

fed weekly or

monthly as is

available

Promotion Calendar fed

into the system

periodically

Marketelligent

PRISM

Display

Feature

Consumer

TPR

Decomposed Lift ()

Sales & Channe

Planning

Real-time evaluation of promotions

Marketelligent has developed an in-house proprietary tool called PRISM, for continuous monitoring

evaluation of trade and marketing promotions on a real time basis, using the test-control approach.

dentifying the control samples for each of the test group takes most of the time/effort. PRISM minim

the time required for the same and identifies the control samples on a real time basis, based on histo

sales trends and outlet demographics.

PRISM uses sales in test and control outlets, to calculate the lift factor for each or combinations of t

marketing programs. Based on the lift factor, incremental sales and ROI are calculated for each activity

effectiveness of promotions can be compared at different levelschannels, categories, brands and mark


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Market

Performance

Jan09

Feb09

Mar09

Apr09

May09

Jun09

Jul09

Aug09

Sep09

Oct09

Nov09

Dec09

Jan10

Feb10

Mar10

Apr10

May10

Jun10

Jul10

Aug10

Sep10

Oct10

Nov10

Dec10

Volume,

000units

Mediaspend,000USD

2%

4%

6%

8%

10%

12%

14%

Total Spends Magazine TV Daily

Evaluate Efficiency/ROI from each media vehicle

Efficiency

0

100

200

300

400

500

600

700

800

900

0

2

4

6

8

10

12

14

16

18

20

Baseline sales Online incr. sales TV incr. sales Daily incr. sales

Online spend TV spend Dailies spend

Decomposed sales into base line and incremental

Market Mix Modeling

Marketing budgets as a percentage of sales typically vary between 4-10% for a CPG company. Given the

nvestment, marketers would like to evaluate the returns from each media vehicle and optimize

nvestments.

Market Mix Modeling (MMM) helps brand managers identify the right mix of advertising media, ma

channels and allocate marketing spend in a manner that not only provides the required sales lift but

maximizes the returns on investment by media vehicles.

The model captures the following:

Cannibalization, if any, amongst the portfolio of brands

Impact of competition media activity

Saturation spends for each media vehicle based on diminishing returns

Decay impact, if any for each of the media vehicles - also called ad-stock


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Knowledgeable

2%

Quality Conscious

4%

Soft Shiny Hair

4%

Better Color

Experience 1%

Natural

Ingredients 2%Pleasant

Fragrance 1%

Gray coverage

1%

Value for Money

0.4%

Feel young In

charge 15%

Sensuous &

Sophisticated14%

Perfect color

13%

Recommended

brand 11%

Brand that keeps

its promises 9%

Range of Shades

8%

Makes me feel

confident 9%

Intense, long

lasting colors 5%

Purchase Intent

Colour pathwayNon-damaging pathwayExperiential

Emotional response

Rational response

Brand image

Brand attributes

Market

Performance

Driver Analysis

Every organization needs to understand which product/service attributes have the greatest influence on

consumerspurchase decision. For instance, consumers might rate a personal care product based on its c

scent, functionality, price, discount offer and so on. Driver analysis is a technique widely used to identify

key consumer needs which translates to purchase behavior. It provides answers to critical questions like:

What accounts for consumersproclivity to purchase the product?

What causes consumers to switch to competitor brands?

What is the core consumer segment that should be focused on?

Statistical techniques (Correlation, Multivariate Regression, and Structural Equation Modeling) are utilize

dentify the critical success factors of a brand which drives sales or revenue.


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Identify growth opportunities for niche

consumer segments

Define the portfolio strategy for theircategory by ensuring minimal consumer

segment overlap across brands

Based on the above, the marketing team

modifies their product/service offering and

deploys the desired positioning and

marketing communication to reach their

consumer base.

Healthy hair

Seekers

Natural

enhancers

Expressive

Age defiers

Young subtle

expressers

Young strong

expressers

Original color

of hair

without hair

colorant

Color of hair

with haircolorant

(Aspired

Color)

Dark Brown

Medium Brown

Light Brown

Medium Brown

Medium Blonde

Dark Blonde

Light Brown

Dark Brown

Medium Brown

Medium Brown

Dark Blonde

Medium Blonde

Light Brown

Medium Brown

Medium Blonde

Dark Brown

Chestnut

Medium Blonde

Auburn

Dark Brown

Auburn

Auburn

Chestnut

Auburn

Chestnut

Market

Performance

Consumer Segmentation

Segmentation identifies homogenous consumer groups based on their needs, preferences, attitu

demographics, lifestyle measures (activities, interests, opinions and values) and behavior.

A mass marketing approach treats the market as a whole, while segmentation enables the business to ta

different consumer groups by adapting its product and marketing mix to suit each targeted segment.

Segmentation results are leveraged to:

Understand how the market is evolving in terms of changing consumer needs/preferences

Identify the benefits sought by each consumer segment

Improve the competitive position by focusing on the most profitable and sizeable segment


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Assessing brand value helps in:

Identifying optimal measures to build

strong brand equity

Demonstrating the effect of strongbrand equityin terms of market share,

consumer acquisition, brand loyalty and

other desirable outcomes

Mapping the brand's equity against that

of key competitors Judgments

Resonance

Feelings

ImageryPerformance

Salience

Stages of brand development

4. Relationships =

What about you and me?

3. Response=

What about you?

2. Meaning=

What are you?

1. Identity=

Who are you?

Branding objective at eac

stage

Intense, Activ

loyalt

Positive, Accessibl

reaction

Points-of-parit

& Differenc

Deep, Broa

brand awarenes

Kellers Brand Resonance Pyramid

Market

Performance

Brand Equity Tracker

Brand equity tracker provides a framework for measuring the brands performance/health. This ca

assessed through consumer perception, which includes both rational and emotional aspects. Main cri

for assessment brand differentiation, brand relevance, the consumersknowledge of the brand and b

mage in the consumersmind.

Brand equity tracker defines the gap between what a brand wants to be and how a brand is act

perceived by consumers, thereby giving a direction for branding strategy. Different components of b

equity are depicted in the image.


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Business Situation:

Clients 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 SKUs 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 t

returns.

The Result:

Forall 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 fMay2011 being 85% and June 2011 being 97%.

Analytics in ActionTowards Better Production Planning by Accurate Forecasting

Client: A Leading Carbonated Beverage Manufacturer

Defining

Modelling

universe

Model

developmentValidation

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 tosmoothen the data and to get a better

model fit.

ARIMA model was built on Centralisedmoving 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 SKUs

-

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

Daily

Returns

Actuals

Forecast


21/24

Business Situation:

The client, a leading hair care manufacturer wanted to identify drivers of brand preference for the category which would aid them in designi

the right marketing strategy & related collateral for strengthening market share for their existing brand.

Analytical Framework:Design a Structural Equation Model (SEM) to identify key equity themes & their hierarchy in terms of importance in driving purchase for the

category, and identify the best pathway to improve the brands equity in consumers mind.

The Result:

The following recommendations were made and implemented by the business: Leverage Brands strength on the health dimension this goes in line with brands equity pyramid

Ingredient is one of the key category drivers on which the brand is performing very well strengthen communication strategy to

capture this

Even though health benefit is key, consumers eventually desire the beauty aspect Redesign communication strategy to convey this

as the end benefit

Currently beauty dimension is weak build credibility on that with consistent communication

Analytics in ActionRe-design Product Communication Strategies in line with Consume

Preferences

Client: Leading Hair Care Manufacturer

Marketing strategy on the core Health benefit & its eventual impact on making oneself attractive is the Key

Overall Brand Equity

Feel Confident

& Energised

15%

Trust

10%

Effective

8%

Expert Brand

3%

Leaves hair

soft ,smooth

and shiny

11%

Hair Health

10%

Color

Protection

1%

Conditioning

3%

Ingredients

11%

Brand for me

6%

Attractiveness

10%

Beautiful and

Empowered

1%

Leading Brand

2%

Fragrance

5%

Experience

1%

For men and

women

0.3%

Dandruff and

Scalp issues

4%

0.60

0.37

0.83

0.21

0.90

0.63

0.30

0.09 0.290.15

0.80

Strong relationship

Moderately strong relationship

Weak relationship

0.78 0.19 0.90 0.90 0.90

0.90

0.90

0.16


22/24

Business Situation:

Leading manufacturer in anti-aging cream category. Brand X occupies a dominant position in market; recently also introduced Brand Y.

Brand X Volumes are down 6.5% vs. last year.

Spending across Media has shifted from being TV-centric in 2007 to Dailies-centric in 2008.

Manufacturer would like to understand the effectiveness and efficiency of his Media Spend; and to find optimal ways to reallocate mediaspend across channels so as to maintain Sales

The Task:

Need to develop an optimal media investment strategy based on Media Mix Modeling to improve the brand equity of the client :

Establish key relationships between Sales and Marketing driver inputs.

Quantify impact of each marketing driver on sales.

Optimize allocation spends across various drivers to maximize sales.

The Result:

The model gave clear directions for allocating budgets across various media :

For every $ spend, Magazine gives 6 times the return of TV and dailies.

Magazines seems to be operating above threshold and below saturation levels.

Lower returns on TV could be due to operating levels below threshold in certain bursts, and low SOVs compared to Brand Z.

TV has a bigger role of driving the brand health.

Recommendations used to optimize marketing spends across channels to maximize Sales.

Analytics in ActionIncreasing ROI by Optimizing Media Spends

Client: A Leading Beauty Products Manufacturer

0

100

200

300

400

500

600

700

800

900

0

2

4

6

8

10

12

14

16

18

20

JAN07

FEB07

MAR07

APR07

MAY07

JUN07

JUL07

AUG07

SEP07

OCT07

NOV07

DEC07

JAN08

FEB08

MAR08

APR08

MAY08

JUN08

JUL08

AUG08

SEP08

OCT08

NOV08

DEC08

Baseline Sales Magazine Incr. Sales TV Incr. Sales Daily Incr. Sales

test Magazine Spend TV Spend Dailies Spend

Volume,

000units

MediaSpend

,000SGD

-

0.02

0.04

0.06

0.08

0.10

0.12

0.14

Total Spends Magazine TV Daily

Efficiency

Incremental Sales per 000 SGD media spend


23/24

Business Situation :

Over-the-Counter (OTC) market is a growing industry; consumers today are much more inclined to self-diagnosis and self-medication as th

prefer to have a greater role in their health affairs. And brand shares are impacted because of multiple influencers like FDA regulatio

mergers and acquisitions, patent expiry, Rx to OTC switch, entry of generics, etc.

The Task :

In this dynamically changing OTC market; there is a need to track OTC industry movement by category and evaluate market share changacross key geographies /countries . This will enable a business to focus its marketing efforts on areas with the greatest return on investmen

Analysis :

Collated historic (2005-2010) as well as forecasted sales (2011-2015) information.

Accounted for all industry mergers & acquisitionsat company X brand X country level

Evaluated category and brand performance at each of the levels defined below:

The Result :

Insights from this analysis helped identify the focus markets and brands by each category. Based on this the client drafted their annustrategic plan

Analytics in Action

Tracking Market Development in the OTC industry

Client : A Leading Global Manufacturer of Over-the-counter Drugs

Category

1. Cough & Cold

2. Analgesics

3. Vitamins & Minerals

4. Digestive Healthetc.

Geography

1. APAC

2. LA

3. NA

4. WE & EEetc.

Country

1. USA

2. Canada

3. Brazil

4. Chinaetc.

Company

1. J&J

2. GSK

3. Merck

4. Reckitt Benckiseretc.

Brands

(as an example brands

within Analgesics)

1. Tylenol

2. Aspirin

3. Adviletc.


24/24

MANAGEMENT TEAMGLOBAL 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 focusedon 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.

Kakul PaulBusiness Head, CPG & Retail

Kakul has over 8 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

CONTACT www.marketelligent.c

Industry Business Focus Tools and Techniques

Consumer Finance Investment Optimization SAS, SPSS, R, VBA

Credit Cards Revenue Maximization Cluster analysis

Loans and Mortgages Cost and Process Efficiencies Factor analysis

Retail Banking & Insurance Forecasting Structural Equation Modeling

Wealth Management Predictive Modeling Conjoint analysis

Consumer Goods and Retail Risk Management Perceptual maps

CPG & Retail Pricing Optimization Neural Networks

Consumer Durables Customer Segmentation Chaid / CART

Manufacturing and Supply Chain Drivers Analysis Genetic Algorithms

High Tech OEMs Supply Chain Management Support Vector Machines

Automotive Sentiment Analysis

Logistics & Distribution

YOUR PARTNER FOR

DATA ANALYTI CS SE RVIC ES

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
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Application of Decision Sciences to Solve Business Problems in the Consumer Packaged Goods (CPG)...

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