ShareBy Paul van Meerendonk, Director of Advisory Services, IDeaS Revenue Solutions
I had the honor of speaking at HSMAI’s Brand CRO Roundtable recently in New Orleans about the power of today’s sophisticated analytics. With many unique challenges facing the industry today – notably around an increasingly competitive distribution landscape – hotels are looking for the best ways to account and solve for the complexity in the market.
There are four main players in the distribution scene:
- Expedia/Booking.com; With recent mergers in the industry, these two organizations are really dominating today’s OTA market
- Airbnb; This new distribution channel presents a challenge and opportunity for hotels but will it steal away business from other channels and hotel market share or increase the travel population?
- Google; Jumping into the distribution game, Google is now providing the ability for hotel bookings
- TripAdvisor; Once solely a guest review site, TripAdvisor now offers guests ways to directly book reservations on a variety of different sites
With these new entrants and growing powerhouses posing a potential problem for hotel direct business, discussions have been revolving around how revenue teams can tackle these mounting revenue management and distribution challenges. We’ve seen an emergence of important concepts like big data, machine learning and business intelligence landing at the forefront of many industry conversations, but they can all mean different things to different people. However, what they all have in common is they are all components of today’s sophisticated analytics.
The analytics tsunami is here and it’s been engulfing revenue management with no signs of stopping – nor should it. Analytics uses data mining, machine learning and statistics to churn out optimal pricing and inventory decisions for hotels. And with the sophistication and adoption of analytics growing tremendously, there’s a massive opportunity to evaluate your own analytical capabilities – both as part of an organization or as an individual – and map out how analytics can move you from being reactive to proactive and predictive in revenue management.
Analytics helps you move even further beyond the normal revenue management processes into harnessing your data and forecasting capabilities to explore, predict and optimize your revenue results. Today’s analytics help you explore why patterns and trends are happening so you can predict whether you can anticipate similar or different results moving forward – and this is where analytics becomes exciting. By determining why specific results are emerging – and if you can expect them to continue – you can then start to optimize them by taking action to get the best effects and deliver revenue performance.
There are many aspects of analytics that play a role in delivering optimal results: High performance forecasting capabilities provide a dynamic selection of hundreds of forecasting algorithms and models to give you the best possible results; granular data and decisions can be provided for multiple hotels by departments, segments, room types, day parts and rate codes; predictive analytical tools allow you to understand the impacts of changing your strategy; advanced pricing and inventory controls maximize revenue opportunities; and expanded data sources such as reputation, competitive performance, rate shopping and value of demand can be integrated into your decision outputs.
In order to take advantage of these approaches and ride the analytics wave, I believe there are three key components that need to be taken into consideration.
- Technology: Do you have a best-in-class infrastructure and the right tools available? The benefits of sophisticated analytical technology provide a solid foundation from which to build your performance strategy.
- Processes: Optimal processes should not only look at taking advantage of the analytics outputs, but almost as importantly the inputs. To make analytics work effectively for your organization, the company culture needs to be geared towards a common goal of data integrity and effective implementation of analytical decisions.
- People: Who is going to apply sophisticated analytics in your organization? Increasingly, the role of a data scientist is becoming an essential component of an effective revenue management strategy. In-house resources are becoming more common-place in the larger organizations. As was shared by some of the participants during the roundtable, cross-departmental data scientist can apply their skills where needed at the right times, while balancing the overhead costs of maintain this new role. External resources and third parties that can provide analytics as a service are also available. Dedicated support services for your analytical technology and processes will ensure you can perform at your maximum potential.
Taking these components into account will ensure you can deliver the most optimal revenue results – helping you master the analytics tide and avoid drowning in today’s sea of big data and distribution.