Application of Ai/ML in Business for Sustainable Profitable Growth
Transforming partners through upskilling, retooling, and data-driven business commercial steering


The Three Pillars of The Value I Bring


AI Opportunity Detection

AI Strategy & Implementation

Organization Design & AI




The value I bring is in helping companies and departments assess which business processes are most affected by changes in consumer behavior as well as market, competitive, and technology trends. I then typically work on (1) AI opportunity detection, (2) data and AI strategy for insights/automation prioritization, and (3) organizing the department or companies around modern data-driven product offering, sales, and commercial steering processes. In many cases (1) is also first about automating manual repetitive tasks in pricing, quoting, and analyses that slow down but underpin day-to-day decision-making. Addressing this first helps freeing up up to 60% of time to work on more strategic matters. 


1) AI Opportunity Detection

Identify what AI and AI-powered solutions can bring to your company, in automating smart human-intelligence type processes, insights to improve sales, customer experiences and automate smart processes like dynamic personalized offerings.

Recent Use Cases (2020-2022)

  • Retailing on marketplace with dynamic pricing while ingesting 3rd party content (airline start-up)
  • Deep micro segmentation for new value driver identification & calculation of monetary value for improved insights-based pricing (in pax and B2B, and cargo)
  • Digitizing cargo spot quoting process
  • Automating responses to RFQs with real-time pricing guidance to increase win rates with better margins
  • Moving to dynamic ancillary pricing
  • Implementing dynamic pricing in air cargo
  • Infusing circular-route logic, analytics-based demand forecast and capacity control optimization using ML.
  • Preparing freighter route/market optimization process for automation with supervisor-guided rules using AI.


2) AI Strategy & Implementation

Improve your commercial model and competitive position by prioritizing the right AI strategies and technology partners. 

Recent Use Cases (2019-2022):

  • For airline: Completed airline start-up commercial planning and design using Deep Learning and AI at Enterprise level (Q1-2022)
  • For travel marketplace: Developed and implement a holistic and hybrid dynamic bundling/offering management process and automated tool for air fare, ancillaries, loyalty, and onboard sales
  • For cargo operator: Using deep analytics and layered ML (Deep Learning) to carve out new markets, segments, product offerings (pax / cargo)
  • For cargo sales: Identified and implement new market/customer/product/commodity combinations with shipper-FF-carrier transparency, creating new business models with specific price points based on value-based pricing (attributes)
  • For vendor: "Frequent freighter" (loyalty) program design and implementation around strategic accounts using AI
  • For freighter carrier: Used ML and AI to create deep insights and automate the preparation of strategic sales initiatives and programs with Freight Forwarders.


3) Learning Organization with AI

 Organize your company and talent in the right places and processes to become a continuous learning organization around smart processes that deliver toward your company goals.

Recent Use Cases (2021-2022):

  • For airline: Created an airline start-up organization design along an Enterprise AI workflow
  • For Big 4 and their customers: Created a learning organization  that facilitates the learning of 'multi-disciplinary specialists' continuously transforms itself around new AI experimentation
  • For Chief HR Officer: Used data scientists and their workflows to help redesign the organization structure based on value-creation
  • For airline CCO: Used data-driven approaches (ML/AI) to redesign divisional/departmental structures and work streams to create a frictionless customer-based business execution.
  • For airline CEO: Embedded human performance-based metrics (KPI) into machine-based continuous improvement: i.e. define how ML will help upskill managers to become more strategic in their managerial leadership to using ML/AI in a competitive setting. 


Overview and Specialties

I specialize in all aspects around driving more and better quality revenues through the application of Machine Learning (ML) and the automation of smart processes through Artificial Intelligence (AI) in B2B and B2C verticals, particularly passenger airlines, air cargo, and air cargo forwarding.  My approach is not through traditional consulting, but more through updating, upskilling and educating colleagues and partners, working together as a facilitator and resources at arm's length.

I help individuals and companies accelerate the modernization of commercial processes and workflows by preparing them for the adoption of Artificial Intelligence and Machine Learning in business. I do this through education, training, and by sharing research of best practices, particularly with regard to the modernization of pricing, RM, ancillaries, sales and retailing and the evolution beyond Business Intelligence (BI). With my 28 years in aviation split between pax and cargo (even today), I am current in both verticals.

The know-how you gain assists you and your company to get ready to become data-driven and take advantage of insight-driven automated decision-making (AI), helping your company to become competitive and agile. The solutions you will learn to design and implement result in better planning, better segmentation, better pricing, smarter customer propositions, higher conversion, and a truly customer-centric experience that will boost market share, customer retention, and profitability.

Ricardo Pilon, Ph.D., FRAeS

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