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How Will The RMS Evolve to Move Revenue Management Forward

Revenue Hub
Revenue Hub
Episode • Jul 9, 2020 • 1h 4m
Today we are joined by 3 Guests






Michael McCartan - founder of mccartan tech consulting






Neville Isaac - Chief Customer Officer at BeOnPrice

https://beonprice.com/en_US/






Marko Lukicic - Co-Founder and Director at Acquaint

https://acquaint.hr/ 





This discussion continues our series looking at the evolving role of the revenue manager





Today we explore how the RMS is evolving and what additional data sets are being integrated to enhance the pricing element - looking at optimal pricing and fair pricing.





We then talk about potential, non traditional, indicative data sets and consider some constraints around this in terms of cost and privacy legislation



If you would like to watch the interview you can see it on our YouTube channel by clicking this link: https://youtu.be/9ijlPw-tg7Y





Here is the timelinechapter breakdown of topics discussed:





0:00        General welcome

1:00        Welcome guests

2:00        Guest introductions

7:15        Current RMS solutions - Is it providing sufficiently accurate predictions

9:17        Does the current RMS only really automate what we did manually

11:13      From a data science perspective reliance on historical data Is very limiting

14:50     RMS 2.0: How is the RMS evolving

16:20     Market Intelligence and the influence on a hotel - marrying internal and external data to improve price recommendation

20:50     Fair pricing

23:15     Revenue professionals restricted to location because of market knowledge

25:05     Willingness to pay and how individual property features could play a greater part

33:02     How are those without an RMS doing revenue management. Do they really understand the concept

36:04     Is most revenue pricing forecast still just adding a multiplier to last years rate

40:15     Where do we go next above and beyond historical in-hotel data

41:14     How the Finance sector moved beyond traditional historical data

45:50     RMS 3.0: What untraditional data sets could we be exploring to enrich forecasting

49:35     Macro data and micro data

52:50     How trust can be an issue as more data sets get added

58:00     Can the current one size fits all RMS become more bespoke

1:01:41  Wrap up summary




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