Decision Intelligence: Turning Hotel Analytics into Action

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BI (business intelligence) is an organization’s ability to track data flow and in the process identify opportunities, minimize risk, and optimize the way it does business. Most businesses - not just hotels - have yet to reach that optimal level of BI maturity. Many have automated data collection, report generation, and, in some cases, data visualization. But that doesn’t mean that they’re mobilizing data into action. Quite often people use their BI platforms for nothing more than scheduling reports to be emailed to them in their inbox but reports alone do not constitute business intelligence. Thus, they’re still stuck in static spreadsheet mode when it comes to decision support. More advanced users leverage BI tools to increase their pace of discovery within the BI portal but then end up spending hours trying to re-share and explain their findings to others who are not operating in the same environment. Often they end up having long discussions with colleagues to figure out “Why don’t your numbers match my numbers?” (Day of week vs date, corporate profiles vs negotiated rate codes, time of data capture, filter by different dimensions - possibilities abound!). 

Looking at automated scheduled reports is certainly a step in the right direction and even better when hotel teams are exploring data to make informed decisions. However, the shortcomings of how BI is being leveraged today are quite visible. 

 

Enter Decision Intelligence (DI)

Cassie Kozyrkov, Chief Decision Scientist at Google, describes DI as a way to augment data science with social science, decision theory, and managerial science. Thus, making it more effective at helping people actually use BI data to make better decisions. A great analogy she uses to describe the difference between data science and DI is comparing them to those who make microwave ovens and the cooks who use them. Note that by ‘data science’ she is referring to the analytics that are delivered via BI platforms. Simply put, DI is an enabler of BI’s end goal - identify opportunities, minimize risk, and optimize the way you do business.

But How?

Firstly, it’s important to note that BI and DI are not just technologies but rather evolving organizational capabilities. In order to succeed you need data-driven culture, people, and tools. The first two you cannot buy off-the-shelf from any technology provider. They have to be embraced as strategic organizational objectives. Once that commitment is made and you actively start working towards it, here are 4 ways to get you much further with your data than basic self-service BI reports:

 

1. Centralize & Correlate

Hoteliers today are working with a deluge of valuable data from their transaction systems (PMS, POS etc.) as well as market intelligence from a variety of 3rd party sources (STR, Kalibri Labs, Knowland etc.). However, very few can actually correlate their channel mix (and many other business dimensions) to something like their STR Market Penetration Index (MPI). That’s because most of the time these data sit in their own silos and no one is able to see how one is impacting the other. Hence, the obvious first step towards unlocking such insights is to centralize all this information on a BI platform that will then allow users to collect, layer, and correlate different types of data to get a holistic view of the business. In the below example, as users go across the time slicer they can see how their segment, channel, and room mixes were changing and impacting their STR indexes.

 

Source: HotelIQ STR Dashboard

 

2. Visualize & Interact 

One of the worst habits people develop using spreadsheets is conditioning themselves to look at specific cells on a wall of numbers. They look at the same set of reports and glance over the same cells regularly to monitor the health of their business. Hence, when they are presented with a BI tool, their first instinct is to automate their reports. They still want the wall of numbers laid out the same way they’ve conditioned themselves to read and think. However, a huge side-effect of such conditioning is that they miss all the threats and opportunities hiding in plain sight. For example, how likely are you to spot a white tiger hiding in a dazzle of zebras?

 

 

 

Similarly, a miscoded rate code can bury itself in a sea of reservations. By the time you notice a dip in the overall ADR, significant damage may have already been done. However, if instead of glancing over a wall of numbers, what if your rate codes were displayed on a scatter plot? It’d highlight to you which ones are performing worse than expected and who’s performing better. Then imagine clicking on a plot and getting the information you need about it literally at your fingertips!   

 

Source: HotelIQ Agency Trends

 

3. Analytics-powered Collaboration

We’re all familiar with digital workspaces. If we weren’t before, the pandemic has forced us to start collaborating digitally. From Sharepoint to Slack to project management portals - all facilitate collaboration between teams. However, when it comes to sharing data and insights, most of us are still dependent on extracts and spreadsheets. Hence, teams spend an unreasonable amount of time trying to come up with a single version of the truth that everyone can agree on before they can take any decisive action. That’s where you need an analytics-powered digital collaboration platform - a portal or intranet where your strategic teams login to work everyday, access a single version of the truth (through automated data integration), share, comment, plan, and track performance. There are also many other advantages to digital collaboration.

 

4. AI-powered Decision Support

Once you have centralized all your data and your team is able to easily explore, share, and collaborate, the obvious next step is to determine what course of action to take. That’s where AI can elevate your decision making capabilities significantly by processing historical and current data trends to highlight risks and opportunities that lie ahead. However, quite often we get fixated on the accuracy of AI predictions. If the pandemic has taught us anything, it’s that no one has a crystal ball that can accurately predict the future. Instead, we need to focus on the reliability and reasonableness of AI’s input in our decision making process. It may not be able to predict a pandemic but can certainly highlight unusual activity that requires your attention much faster than a normal human can. Let’s put it this way, if you have a junior analyst who is very thorough and meticulous in her work, would the CEO leave all the decision making to her? AI is like that analyst and should be treated the same way - pay attention to what AI tells you and then make informed decisions.

 

Source: HotelIQ Risk to Achievement Dashboard

 

Ultimately, technology and decision science will continue to evolve. There will be even more sophisticated ways to enable consumption of information by businesses and means to let them action it. However, unlike tactical technologies like a phone or a refrigerator, there is no leap-frogging when it comes to analytical capabilities of an organization. The longer you delay building that culture and bringing in those solutions, the harder it will be to stay competitive in the information age.