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BIA650
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US Senior Citizen Diabetes Prevention ProposalBIA-650 Process Optimization and AnalyticsDec 2014
Alek LiskovBing Lang
Dmitry RassakhatskyNing Li
Yilin Wei
Agenda1. Introduction to Diabetes2. Target Population3. Prevention Programs4. Optimization Models5. Sensitivity Analysis6. Conclusion
1. Introduction to diabetes• Type II diabetes takes the largest part
Source: Global diabetes plan 2011-2021, International diabetes federation
Type I: 3% - 5%Gestational diabetes: 2% - 10%
Type II: 90% - 95%
2. Target populationPatients highly concentrate at Louisiana, Mississippi, Georgia, Tennessee, South Carolina and Arizona.
2. Target populationThe economically challenged areas overlap with the areas of high percent of diabetes.
US diabetes map US poverty mapSource: CDC's Behavioral Risk Factor Surveillance
2. Target population
Utilize PRIZM to investigate psychographic segmentation based on geographic and demographic segmentation
Age:55+65+
Income:Lower midMidscale
DownscaleLow income
Urbanicity:SuburbanTown/rural
TownRural
2. Target population
Use TV program and shopping place to advertise program
Type Midscale Mature w/o Kids
Lower Mid Mature w/o Kids
Midscale Mature w/o Kids
Shop Lord & Taylor JCPenney Lands' End(online)Watch Frontline Wheel of Fortune Hallmark Channel
Type Midscale Older Mostly w/o Kids
Downscale Mature w/o Kids
Downscale Mature w/o Kids
Shop QVC(online) Kmart L.L.Bean(online)
Watch New Yankee Workshop
Crimetime Saturday The 700 Club
Type Downscale Mature w/o Kids
Downscale Older w/o Kids
Downscale Mature Mostly w/o Kids
Shop In-Home Vitamins Purchase JCPenney(online) Tractor Supply
CompanyWatch Price is Right Judge Joe Brown Bold & Beautiful
2. Target population
People aged 60+ hope to save more money
Source: The 2014 edition of the United States of Aging Survey
2. Target population
People aged 60+ hope to maintain closer relationships.
Source: The 2014 edition of the United States of Aging Survey
27%
3.1 Prevention programs
Two steps model to educate participants
Based on Dr. Peter Sandman’s environmental communications model
3.1 Target Population DataSource Data Description Time Period
Centers for Disease Control and Prevention (CDC)
Distribution of diabetes patients and occurrences, including data about socio-economic factors and population characteristics.
2004-2014
Last 10 Years of data
CDC and National Center for Health Statistics
Data about new and existing diabetes cases broken down by age group and condition stages
2004-2014
Last 10 Years of data
3.1 Мedia campaign - DataSource Data Description Time
PeriodGoogle Analytics* Google AdWords audience reach
and measurement data2014
Traffic Audit Bureau The improved metric system will measure audiences 'likely to see' an outdoor ad, with rich demographic and ethnographic data.
2013
Nielsen TV and Radio Audience Measurement and statistics
2014
Facebook* Facebook audience reach and measurement data
2014
3.2 My Health Task Program
Gamification: ● Allow user to win appealing awards by completing
tasks
By participating the program,users will be ● repeatedly exposed to health related instructions and
tips● encouraged to adopt healthy eating habit and exercise● encouraged to share progress on social media to
influence their network
3.2 My Health Task Program
Complete one
health quiz
everyday
Workout 3 hours/week
Test and record blood sugar/
pressure
Read a healthy
recipe/tip everyday
Through web/app
Post healthy meal
/workout on social media
Measured by apps such as MapMyRun,
Nike+, JawBone
Task 1 Task 2 Task 3 Task 4 Task 5
Every user will be a
social media info center
Complete one
health quiz
everyday
Workout 3 hours/week
Test and record blood sugar/
pressure
Read the healthy
recipe/tip everyday
Post healthy meal/
workout on social media
Task 1 Task 2 Task 3 Task 4 Task 5
3.3 Media Efficiency Matrix
CostHigh Low Medium Low Low Medium
Participation High Low Medium Medium Medium Medium
Effectiveness Medium Low Medium Medium Low Medium
4. Optimization Models - Objectives● Maximize effectiveness
○ Maximize participation■ Effectiveness of prevention program■ Optimal ROI for each media channel
○ Maximize awareness■ Optimal allocation of advertising budget
4. Optimization Models - Constraints● Budget
○ stay within the designated budget in terms of program spending
● The minimum acceptable level of participation
● Minimum effectiveness level >=○ difficulty tracking exact viewership and campaign
ROI;○ availability of social media data;○ understanding the accuracy of the campaign;
4. Optimization Models - Optimization techniques● Classification● Analytic hierarchy process (AHP)● Goal programming● Linear programing
4.1 Optimization Model MHT
• To Maximize the participation and effectiveness of My Health Task
• Score each task by Analytic Hierarchy Process (AHP)
• Prioritize participation as first goal and effectiveness as second goal by goal programing
• Allocate budget by linear programing
Task 1 Task 2 Task 3 Task 4 Task 5
Cost(R&D+ad)
Low Low High high low
Participation(Predicted)
0.8 0.7 0.2 0.3 0.1
EffectivenessQuotient
20 30 50 90 10
Task 1 Task 2 Task 3 Task 4 Task 5
4.2 Optimization Model - Мedia campaign● Utilize clustering techniques to identify the
subpopulations based on geographical location and socioeconomic factors
● Determine the optimal combination of media channels using AHP
● Allocate budget by linear programming
4.2 Optimization Model - Мedia campaign
● Variables and estimated weights
Types Number of People Reacher / $1
SEO 2.6
SEM 1.2
Facebook 3.0
TV Ads 2.5
Magazine Ads 0.8
5. Sensitivity Analysis - MHT● Change of budget● Change of participation response rate● Change of minimum required effectiveness
5. Sensitivity Analysis - Media● Allocation of advertising funds
○ Examining the change in allocation based on campaign effectiveness
● Determining the best portfolio for each channel○ TV: deciding between programs and time○ Radio: station and optimal time○ Print: publication selection○ Web/Mobile: best platform and coding○ Street: Location and message○ Social: Best audience
6. Conclusion
The practice:
Functioning program + advertising methods
The measurement:
cognitive quantitative
Restrictions:
○ Accuracy of the data ■ Survey results do not 100% reflect realty■ Privacy Concerns