Innovation combined with key pricing and revenue management disciplines will be crucial for turning ideas and technologies into actionable intelligence in 2013 and beyond. In this presentation, Suresh Acharya, VP of Product Management, JDA Software, provides an overview of revenue management and how media companies can apply innovative technologies and practices to turn upfront and scatter opportunities into profits.

1. Theory to Practice:
Translating Pricing Theory into Reality
Suresh Acharya, VP of Product Management

2. Agenda
• Overview of RM
• Media Industry
• Ratecard Optimization
• Dynamic Placement
• Questions
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3. Overview of RM Systems:
Perishable Inventory
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4. Overview of RM Systems:
Demand Shaping
RM systems work by
RM systems work by predicting
predicting future demand,
future demand, based on booking
history and current history and
based on booking booking trends
current booking trends
Excess
Demand
Capacity
Units Sold
By understanding the inventory
constraints, an RM algorithm decides
which subject of the remaining bookings
should yield out or displace
Days Left Service Date
Legend: Observed Demand Unconstrained Demand Capacity
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5. Overview of RM Systems:
Customer Segmentation
DILUTED UNACCOMMODATED
DEMAND $100
$100 DEMAND
$80
$60
PRICE
PRICE
$50
$40
$20
$1 $1
1 50 100 1 20 40 60 80 100
DEMAND DEMAND
• 1 Price • 4 Prices
• Maximum achievable revenue of • Broader market segments can be
$2,500 addressed
• Produces $4,000 in revenue
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6. Price & Inventory Optimization
Inventory Willingness
to pay
Price
Competitive
Sensitive
Data
Forecasts
Optimization
Optimal Price Recommendations
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7. Similarities:
Media and Other Industries
 Perishable inventory
 Segmentation for efficient inventory usage
 Fixed or inflexible inventory
 Purchase date vs. service date
 Competition affects rates
 Integration with transactional systems
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8. Distinctions:
Special Considerations in the Media Industry
 What is being directly
purchased is not what the
buyer is buying
 Stochastic nature of yield
 Small number of buyers
 Different delivery vehicles can
be used to satisfy shortages
 Splitting of inventory for Sales
and Promotions
 Pre-emptibility
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9. Challenges in Media:
 Constant changes in the
selling vehicles
 Rotational buyers vs.
“cherry-picking” buyers
 Changing delivery platforms
 Imbalance of revenues
between delivery platforms
 Ever increasing number of
selling items
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10. Ratecard Building
 The basis of selling is to determine at what price
can something be sold to make the most revenue.
 There are many groups that have a vested interest:
o Finance: Here are our budget targets
o Programming: Here is what we have to sell
o Research: Here is the data behind the inventory
o Sales: Here is how we should sell it
o Revenue Planning / Management: Here are the statistical
trends
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11. Ratecard Modification
 Once rates are set, the next set of questions begins:
o Should I change the rates?
o Which rate(s) should I change?
o For all time periods and by how much?
o What relationships should be maintained between different
selling vehicles?
o What is the overall revenue impact?
o What are different scenarios that need to be considered?
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12. Ratecard Optimization
Inventory Stewardship
/ ADU Req
Demand Business
Forecasts Rules
Optimization
JDA Media Rate Optimizer generates optimal ratecards based on a
holistic evaluation of forecasts, remaining inventory and business rules
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13. Media RM Problem
Matching Demand and Supply
Demand Supply
In addition to the optimal assignment of requests of spots, there are many
complicating rules in media that make the problem very difficult
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14. Media RM Placement Problem
Matching demand and supply
Demand Supply
 Advertisers buy eyeballs;  Network sells advertising
i.e., the attention of time
audience  The value of advertising
 The size of audience time depends on program
depends on program, week, and week
and target demographics  Network is limited by
 Demand is price-sensitive capacity and level of sale
 Demand comes with objectives
complex and many times  Opportunity to transfer
conflicting restrictions inventory between Sales
and On-Air Promotions
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15. Dynamic Placement:
Optimal Utilization of Inventory
Many problems include those in transportation involve the assignment of
space against available capacity to maximize overall value
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16. Dynamic Placement:
Under the Hood
Minimize opportunity cost of Lost Impressions
Manual
placement subject to …
Placement
– Audience requirements
– Daypart Mix
– Flighting
– Program quality constraints
– Program inclusions/exclusions
– Program/time block availability
More Units &
– Demand Impressions Optimal
– Frequency Remaining Placement
– Category conflicts
– Spot length mix Improved
– “Sellability” Efficiency
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17. Dynamic Placement:
Different Realities
In certain media
industries, it is possible to
reassign spots on a
periodic basis.
In other industries, each
proposal must be
assigned with little to no
opportunity to re-assign.
JDA Commercial Proposal Optimization solution enables the optimal
assignment of ad requests to spots to maximize overall profitability
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18. Dynamic Placement:
Heuristic vs. Optimization
Rule of Thumb-based
solve methodologies are
known to produce inferior
recommendations –
costing companies
millions of dollars.
Media RM problems are often categorized as difficult combinatorial problems.
These types of problems require sophisticated optimization technology.
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19. How can you go WRONG with
Revenue Management?
Selling the right product
to the right customer
at the right time
for the right price
through the right channel
RM is a process of maximizing revenue from a
“perishable” product through a combination of
pricing and inventory control.
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20. Theory to Practice:
Translating Pricing Theory into Reality
More Info: www.jda.com/revenuemanagement