Revenue Management is the application of disciplined analytics that predict consumer behavior at the micro-market level and optimize product availability and price to maximize revenue growth. The primary aim of Revenue Management is selling the right product to the right customer at the right time for the right price and with the right pack. The essence of this discipline is in understanding customers' perception of product value and accurately aligning product prices, placement and availability with each customer segment
The Fundamental Review of the Trading Book (FRTB) is a major challenge for the banking sector. This new Accenture Finance & Risk Services presentation explores the key implications of the new requirements and highlights key differences with previously published standards. Access this link for more information on FRTB: http://bit.ly/1NnY1RN
Cloud system management software market pptDheerajPawar4
[148 Pages Report] Cloud systems management software market categorizes the global market by solution, by service, by deployment, by organization size, by vertical, & by region.
Revenue Management is the application of disciplined analytics that predict consumer behavior at the micro-market level and optimize product availability and price to maximize revenue growth. The primary aim of Revenue Management is selling the right product to the right customer at the right time for the right price and with the right pack. The essence of this discipline is in understanding customers' perception of product value and accurately aligning product prices, placement and availability with each customer segment
The Fundamental Review of the Trading Book (FRTB) is a major challenge for the banking sector. This new Accenture Finance & Risk Services presentation explores the key implications of the new requirements and highlights key differences with previously published standards. Access this link for more information on FRTB: http://bit.ly/1NnY1RN
Cloud system management software market pptDheerajPawar4
[148 Pages Report] Cloud systems management software market categorizes the global market by solution, by service, by deployment, by organization size, by vertical, & by region.
Deloitte Maverick Campus Champions, Regional Qualifiers presentation based on the case Given on Pocket payment and entry strategy into another country. 2015
RepoRemarketing provides a managed liquidation solution for Credit Unions. Get more $ for you repossessed inventory. Leverage technology for transparency, tracking, and benchmark your results.
Travel Management Company (TMC) Transformation Solutions | WNS TRAVOGUERNayak3
Explore WNS Travogue's solutions for corporate travel management companies across travel risk management, revenue management, shared services, and recovery to drive efficiency across the value chain.
What make airlines gain profits while the others fall in losses !!!
How LCC creates profits in a recession time ….
Is Airline Industry a profitable Industry !!!
What are various strategies in such cases…
And how to survive in this miss !!!!!!!
In recent times, the airline industry is focusing on ways to increase profitability, using appropriate service enhancement techniques, marketing scheduling and revenue management strategies.
By now airlines have done all they can to squeeze efficient use of fuel. That said, let us focus on a trinity of basic components industry experts believe must be employed by airline revenue managers to effectively and efficiently handle revenue streams.
Revenue Management
Revenue Integrity
Revenue Accounting
Deloitte Maverick Campus Champions, Regional Qualifiers presentation based on the case Given on Pocket payment and entry strategy into another country. 2015
RepoRemarketing provides a managed liquidation solution for Credit Unions. Get more $ for you repossessed inventory. Leverage technology for transparency, tracking, and benchmark your results.
Travel Management Company (TMC) Transformation Solutions | WNS TRAVOGUERNayak3
Explore WNS Travogue's solutions for corporate travel management companies across travel risk management, revenue management, shared services, and recovery to drive efficiency across the value chain.
What make airlines gain profits while the others fall in losses !!!
How LCC creates profits in a recession time ….
Is Airline Industry a profitable Industry !!!
What are various strategies in such cases…
And how to survive in this miss !!!!!!!
In recent times, the airline industry is focusing on ways to increase profitability, using appropriate service enhancement techniques, marketing scheduling and revenue management strategies.
By now airlines have done all they can to squeeze efficient use of fuel. That said, let us focus on a trinity of basic components industry experts believe must be employed by airline revenue managers to effectively and efficiently handle revenue streams.
Revenue Management
Revenue Integrity
Revenue Accounting
Divergent modeling with United Airlines: Building driver-based models with sy...Anaplan
United Airlines’ Airport Operations system encompasses 160 global stations and has a multi-billion dollar value. Join Cato Hagen and John Karantonis from United Airlines to hear how their Anaplan deployment optimizes company performance through proper changes in forecasting, and learn how to do driver-based modeling and variance reporting in Anaplan.
A Regional Airline interconnecting the Middle EastMohammed Awad
This presentation address the main challenges for airline, Decided the Right Aircraft capacity for point to point airline operating Model, and profit maximization for multi stops operating airline model using the concept of optimization ( U curve Concept )
Profit Maximization is addressing Multi-stop operating model of Airlines, it shows how to max. profit in terms of CASK and RASK analysis, delivering the best seniario to select the aircraft then the best result to operate the right segment
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
2. Profiting from Uncertainty
Financial markets recognize uncertainty and capitalize on expected variances
“Risk” justifies higher expected returns in equities and fixed income securities
Investment counselors encourage diversification to reduce overall portfolio risk
Exotic derivatives (puts, calls, collars, floors) are designed specifically to manage, or exploit, risk
Risk is managed more crudely in “real” markets and daily business decisions
Investment decisions, where the financial markets are best represented, typically have 1 hurdle rate based on the whole firm’s
risk profile (D/E ratio, cost of capital); risk differences among projects are often assessed more subjectively
Marketing, pricing, product, and distribution decisions, typically, do not include a sophisticated risk metric
At airlines, however, risk is incorporated explicitly in many commercial and operational decisions
Optimal aircraft sizes and fleet structures incorporate the expected variance in demand across days-of-week and seasons
Pricing – or more particularly revenue management – is based on both expected demand of each fare level on each flight and
on the uncertainty of the forecast for that specific fare level
There is an opportunity for more industries to take a more disciplined approach to Risk
3. Risk-based Decision Making
Airlines have incorporated risk into key commercial/operational decisions
Sophisticated models using Big Data Analytics and linear programming optimization
Exploiting Risk for increased profits is well developed in:
• Supply / Capacity Planning:
• Aircraft and scheduling decisions factor both average daily demand and projected variance in demand
• Pricing:
• Pricing is dynamic, based on forecast demand by flight by fare level
• Forecast uncertainty for each fare level within each flight is explicitly built into optimization models
• Lost Sales:
• Overbooking recognizes high variance in no-shows across flights and days
• Purchasing:
• Sophisticated fuel hedging is designed around specific goals and operating models
4. Capacity Planning: Fleet Decisions
The optimal size of an aircraft on a route cannot solely be based on “average” demand.
For example, average demand of 100 can come from multiple alternative profiles, ranging from a
constant, predictable 100 passengers to random fluctuations between zero and 200+
The aircraft sizing algorithm assesses the Demand Distribution (passengers & fares) and
compares to the operating cost of different aircraft types
Expected marginal revenue versus marginal cost for each incremental seat
The profit maximizing aircraft rarely accommodates average demand
In fact, due to high volatility in demand, 100 passengers on “average” may justify a 110 seat aircraft but this aircraft may only
capture 80 “observed” passengers (a 72% “observed” load factor) with 20 passengers on average unaccommodated
Every flight has its own unique distribution of demand.
High variance, with higher fares, will justify larger aircraft to meet more peak demand.
Lower variance will allow more “perfect” aircraft sizing and higher observed load factors
Optimization models predict “observed” loads and “spilled” (unmet) demand for each flight
5. Pricing Decisions
A typical flight may have 100+ different fares
Airline objective is for each passenger to pay his Maximum Willingness to Pay
Discrete market segments are defined based on different elasticities and behavioral proxies
Lower fares are only offered when demand for higher fares is forecast to be low
Inventory allocations for each fare incorporate demand variance
High variance combined with high upsell opportunity justifies setting aside more inventory for the higher fare demand
Variance is measured, and applied in linear program optimization techniques, for each fare level on each flight
Forecasts and optimized allocation recommendations are updated each night – over a million
distinct forecasts for a 50 aircraft fleet
Such revenue management adds 5-7% revenue to the airline
More discrete pricing based on distributions of demand at different price points – or
between market segments - can improve revenue results in a multitude of industries
6. Lost Sales: Overbooking Decisions
In addition to the demand forecast, additional uncertainty for airlines occurs with no-shows
Passengers who change their travel plans or discard non-refundable tickets
No-shows can be 10-20% of bookings on certain flights on certain days
Without overbooking, no shows result in empty seats and foregone revenue
However, how many or which passengers will no show on a given flight isn’t known
Airlines measure the average and variance of no-show behavior by flight
The expected revenue from selling an extra seat is compared against the probability and cost of oversales
Efficient management of oversales can drive very high overbooking rates when the variance is high
Statistically-based overbooking can add 2% to total airline revenue
7. Other Risk-related Decisions
Fuel hedging became common beginning in 2008 when Southwest earned more from its
hedges than from operating its fleet
Fuel hedging, like financial options, is highly efficient and offers exotic alternatives including collars,
floors, etc. …for a price
However, fuel hedging needs to be tied into operations to avoid being merely speculative
The consolidated industry is now better positioned to pass on higher fuel prices to customers
American Airlines believes any fuel hedging is speculative
Different fleet strategies drive differences in exposure to fluctuating fuel prices
Allegiant airlines operates older aircraft which it grounds when fuel prices are higher or demand lower
Delta manages a fleet of both old and new aircraft, allowing it, too, to manage capacity in response to market changes
Overall risk (operational and financial) needs to be measured and included to meet overall corporate risk/return objectives
Fuel hedges are designed to reduce volatility; not to “make money”
8. Risk-oriented Culture
A firm that relies on heavy statistical modeling and that includes calculated risk in
commercial and operating decisions must adopt different organizational processes
Big Data-based statistical models require special skills and oversight
The “Wall Street” trader mentality within a commercial organization
Specific features of a successful organization built around “Risk” include:
Recruiting and training of skilled analysts
Model transparency and ease-of-use
Checks and balances on analyst decisions and model interventions
Standard metrics for both model and analyst performance; accountability
Within a commercial organization, the Risk group cannot act as a silo
Cross-functional collaboration insures model inputs & outputs (decisions) are “real world”
Learning between the “quants” and the operators is continuous
9. Risk-oriented Decision Process
Point
Forecast
Plan / Act
Forecast
Average
Plan / Act
Type of
Distribution
Economic Assessment of all Outcomes
Overforecast vs. Underforecast
Optimization
Forecast
Volatility
Identification
of Outliers
Goals
Scenario Planning
Traditional
Forecast Process
Risk-oriented Forecast and Decision Process
Operational
constraints/
flexibility
10. Does your Firm Exploit Risk?
Does your firm incorporate forecast uncertainty into its operational decision making?
Analysis of, and metrics for, demand volatility
Economic assessment of under- vs. over-forecasting
Mathematical optimization across distribution of potential outcomes
Capitalizing on high pay-off outcomes, even when they aren’t the most probable
Do you prepare forecasts, along with associated uncertainty, at a sufficiently granular level?
Discrete segmentation of customer market segments based on differing elasticities
Millions of SKU’s including, for services, date- and time-of-day-specific demand
Updated algorithms, coefficients, and the forecasts themselves with real-time orders
Are Operations and Analytics aligned around risk-taking?
11. Can you further exploit Risk?
Tom Bacon has applied Big Data Analytics and Risk Management to support commercial
decision-making at numerous airlines
Led Capacity Planning, Pricing, and other commercial functions as an executive at 5 carriers
Restructured carriers in changing markets or facing new competition
All sectors: global legacy carriers, LCC’s, regionals, and niche carriers
Global: North America, Asia, Middle East, Europe
Assessed analytical systems & modules; achieved track record of success in exploiting risk
Oversaw delivery and deployment of over 150 regional jets, transforming a turboprop carrier into a >$1 B airline
Developed new processes for Pricing Analytics for a bankrupt airline during world recession
Integrated analytical systems for merger of two major airlines
Launched travel start-up designed to manage customers’ risk of fare increases
Persistent advocate for cross-functional collaboration between Analytics and Operations
Thought leader in Big Data Analytics; regular contributor to travel publication and speaker at
industry events
To implement commercial and operational risk management in your organization please contact
Tom at tom.bacon@yahoo.com