The Business Intelligence Boom – Where is this Leading & Who Must Come to the Rescue?

Article for HITEC June 2014 Report

As a revenue management specialist I am constantly reevaluating data sources and data sets.  Long gone are the days of relying solely on market share reports, competitive rate shopping tools, and internal metrics to gauge performance and guide decision-making.  Today, strategic oversight of the revenue management effort involves complex data sets from a multitude of sources.  And to make sense of this “big data” end users must take a highly structured and efficient approach to data gathering with the aim of interpreting and presenting this data in a clear and concise manner

To accomplish this, a much higher degree of technology integration is required; only in this manner can hotels ensure they do not miss opportunities to manage demand optimally.  The lack of comprehensive technology integration is a key part of this challenge, a problem that is growing daily as new data sets come into play.  Even today hotels operate without interfaces between property management and sales/catering systems because the interface costs are high.  But the true cost of the inefficiency is never measured and the old adage of “what we don’t measure, we don’t manage” certainly applies in this case.  Until such time as hotels fully identify and acknowledge lost revenue that is a direct result of misinterpreting the signs of shifting market conditions, signs that might have been read with the help of “big data”, the industry is not likely to address these issues.  The problem is there is a high cost to integration, and in a cost-obsessed industry this only exacerbates the situation.

The hospitality industry has long suffered from the negative affects of working in silos, but today the dangers are amplified.  Traditionally, the revenue generation roles have been defined as marketing, sales, and revenue management, but these terms are obsolete.  More precise descriptions are demand creation, demand capture, and demand management; and it’s only when these roles fully converge that a hotel is in a position to optimally manage demand.  The graphic below depicts the convergence of these disciplines.

optimal-results

For each of these disciplines there are a growing number of business intelligence data sets that must be taken into account to interpret the “demand continuum”.  Imagine if you will, several integrated dashboards that gather and organize key performance indicators (KPI’s) in such a manner as to enable Revenue Teams to evaluate demand conditions from a number of converging perspectives. These KPI’s can be divided into six broad categories:

  1. Macro demand influencers – these are broad-based, overriding factors that are largely outside the control of hotel operators, but dramatically influence the rise and fall of demand
  2. Leading demand Indicators – these KPI’s are direct and conclusive indicators of demand
  3. Competitive impact factors – these factors relate directly to the competitive market place and include two perspectives – those from the competitive set and those from consumer reviews
  4. Marketing and public relations performance indicators – these data sets include results from a multitude of marketing and PR initiatives
  5. Social media performance metrics – these metrics represent the newest indicators of consumer sentiment and engagement
  6. Internal performance metrics – these measurements are the most familiar to hoteliers and now reach beyond traditional forms of metrics to include a “total revenue management” perspective, i.e. all revenue streams evaluated to the profit ratio level

You’ll notice that internal metrics are listed last.  This is intentional.  Too often hotels focus attention on the isolated performance of their own property rather than the forces and factors that impact that performance.  This type of myopic attention makes it less likely to see the inevitable shifting of market conditions in time to make informed adjustments to strategies.  However, if hoteliers will broaden the scope of key performance indicators and examine these metrics in tandem, the likelihood of deploying optimal demand strategies and tactics is far greater.  Consider the following examples of key impact factors:

Key Performance Indicators
Demand Influencers Leading Indicators Competitive Environment Marketing & Public Relations Social Media Internal Performance Metrics
Economic climate Call volumes Market share Marketing ROI’s Tripadvisor rating Occupancy, average rate, RevPAR, & total revenue (to budget, to forecast, to last year)
Airlift Web visits (total, unique, etc.) Rate shopping PR ROI’s Value index ratio* Forecast accuracy
Currency exchange Unconstrained demand forecast Comparative offers (packages, promotions, etc.) Web referrals New reviews & ranking Total guest spend per occupied room, per available room
Air fares Regrets & denials Market share index balance Web conversion ratios Google + rating Call conversion ratios
Air passenger arrivals Revenue forecast Peer review scores & rankings Paid search results Facebook likes Forecast accuracy
Weather conditions (example:snowfall for ski resorts) Booking pace by market segment Channel share Web engagement ratios Twitter followers & Twitter re-tweets Total spend by market segment
Tourist authority statistics Revenue per reservation Fair-share forecast Email acquisitions YouTube subscribers & views Up-sell revenue
Production statistics (packages, promotions, events, etc.) Results by email initiative Pinterest followers F&B outlet & catering revenues per occupied room; covers
Call center abandon ratios Customer retention Instagram followers Guest capture ratios for golf, spa activities
Call tracking by 800# App.com metrics (proprietary apps) Length of stay
Digital display media results Upgrade statistics(# & value of room nights consumed in room types for which the guest has not paid)
Data Sources
Government, industry, & tourism reports; central banks, airlines, weather services Automated call distribution, property management, global distribution, central reservations, sales & catering & revenue management systems; Google analytics; guest engagement software Market share reports, rate shopping tools, reputation management software, online travel agency reports Marketing automation tools, Google analytics Tripadvisor dashboard & other social media dashboards; app statistics Property management, golf, spa, point of sale, sales/catering, & central reservation systems; forecasting tools;

* Value index = the value score in Tripadvisor reviews expressed as an index against the competitive set – much like a market share index

If these metrics could be gathered in such a manner as to make decision making smooth, efficient, and effective, imagine the impact.  If a Revenue Team convenes and determines that call volumes and web visits are down year-over-year, and sets about to identify just how many calls are required at current conversion ratios and lengths of stay to produce the desired room nights, then the marketing team has specific targets to reach.  If competitive research indicates that a hotel’s social media effort is losing share, then Marketing & Sales can make informed decisions to improve customer engagement.

In another example, if the revenue manager carefully tracks production statistics for each and every package and promotion, marketing can fully evaluate the return on investment (ROI) of that initiative.  The key, of course, to all these assessments is the ability to make these decisions based on empirical data not anecdotal observations.  However, at present a Revenue Team must awkwardly examine multiple systems and data sources to collect, organize, and eventually interpret trends.

Technology professionals have worked endlessly to provide intelligent, highly efficient hardware and software to meet the needs of the hospitality industry.  Yet hotel operators are often reluctant to invest in new technology.  In the same manner that the traditional marketing, sales, and revenue management disciplines must evolve and converge into a single demand continuum, so must operators evolve and accept the reality that “big data” is here to stay and growing exponentially.  And the larger it grows the more disconnected our systems become.

So there are two distinct areas of responsibility here.  The first is for the technology companies to make integration easy and affordable.  Many have done this already with open API’s and open minds.  But hoteliers must also have open minds.  And the best way for a cost-obsessed industry to measure the value of integration is to start honestly calculating the money being left on the table.  Comprehensive data sets that are fully integrated for use by hotel general managers and revenue teams are the answer to optimizing demand, whatever that demand may be.  There is a saying that “what’s goes up must come down”…and surely up and down demand cycles are inevitable.  But to answer the question…“who must come to the rescue?”…The answer is a fully collaborative effort from hotel operators and technology professionals, with the emphasis on the operators.  If operators have the political and financial will to conduct business in a fully integrated environment, it will happen and they will come to their own rescue.