Why Revenue Management

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On a personal note, there were questions on of all the possibilities associated with AI, why am I focused on Revenue Management (RM)? There are quite a few contributing reasons.

  • It’s a natural extension of my knowledge as a team lead. I’ve been involved with NRM, RGM, RM, and other versions of Revenue Management since around 2010 when my first projects started. Naturally, many of my friends and colleagues with whom we are working now are also deeply engaged in RM. We’ve all run into many of the same challenges. So, RM is what we know, it’s what we do best.
  • With different teams, we’ve executed it with multiple industries from Life Sciences, CPG (FMCG), Insurance, Travel & Hospitality to Retail.
  • The process of becoming a fully capable RM organization is a long, arduous road requiring a large upfront investment. In almost all cases, organizations engaged with RM initiatives are relying upon obsolete tools (often MS Excel) and methods. Aligning Sales and Marketing on the same brand objectives remains a challenge. Knowledge silos remain intact while extensive training is required to onboard new team members.
  • The new era of Big Data and AI enables interactive Intelligent Assistants and Augmented Teams to provide data analysis on demand and to make decisions in a dynamic, real-time environment. This provides a radical increase in actionability and timeliness to confront one of the biggest challenges of Revenue Analytics – Capability building. The net effect enables people to make data-driven driven decisions and execute them in real-time, on a per-retailer basis. The democratization of data for all stakeholders keeps all teams informed and focused on the same objectives.
  • Then also there is the next-gen appeal of the topic. As a data person throughout my whole career a challenge like this is super-exciting:
    • Intelligent Assistants disrupt this “on-demand” capability applying to all phases and components associated with Revenue Management across the complete execution cycle. In Revenue AI, this is reflected in four modules: Portfolio Architecture, Precision Pricing, Tailored Promotions, and Capable Organizations.
    • A sales or marketing director simply asks a question and our Digital Assistant provides answers in plain English with visuals all stakeholders can easily understand. That’s a huge time-saver!
  • And of course, not to forget revenue growth – There are also huge opportunities for RM, a lot of white space and untapped demand. The Revenue Management market is projected to reach $40+ billion by the end of 2025. The majority (95%) of organizations haven’t started or are just beginning their journey into RM. We like to say the last 5% fall into two camps – those that know RM is a tough nut to crack and those that haven’t cracked it, yet.

Author

  • 15 years of leading analytics disruption in different fields and enabling Business transformations globally. Revenue Management Technology Leadership in different industrials like CPG, Retail, Life Science, Hospitality, Travel and more.