Why flex your data muscles?
A significant number of organizations across all industries are flexing their data muscles by using data analytics to guide decisions made to tackle challenges and to improve performance. Even though analytics alone may not answer all your business questions, it provides a solid foundation upon which you can develop answers to your toughest business questions and tackle the challenges you face with confidence. As you strive to improve the overall guest experience while remaining profitable, do not ignore the key role that analytics can play. I should mention here that quite a number of hospitality organizations are using data analytics extensively to improve their performance. However, a larger proportion of hospitality businesses still remain behind the curve. Remember that you shouldn’t flex your data muscles just because everyone else is doing it. Do it because infusing the relevant insights obtained from your analytics into your day-to-day business decisions can significantly improve the overall performance of your business.

A Review of Last Month’s Challenge: What’s in my data source?
February’s challenge was aimed at helping you review and identify the various types of information that can be found in your data sources. When outlining the challenge, I mentioned that it’s not enough to know that a data source exists.  You should also know what information/data resides in each source. This knowledge will save you a significant amount of time when it comes to looking for data relevant to your analytics. Various studies have shown that most people who want to analyze data spend about two-thirds of their time looking for and gathering data, leaving them with very little time and energy to understand and analyze the data. Therefore, any proactive measure that helps you spend less time looking for data can add value to your analytics journey.

During this stage of the challenge, you were expected to familiarize yourself with the types of information within each of your data sources, and create a list of this information either grouped by data source or by the type of information. For example; you should be able to create a list of all the data sources/systems in which you can find revenue data, or for each data source/system create a list of the type of information that can be found in it (e.g., revenue data, guest information, employee information etc.).  A typical challenge you might have encountered would be that in some cases the same data (e.g., revenue) resides in multiple sources. You therefore needed to review these pieces of data to determine any instances of duplication or the need to combine data sources. Another point you should have considered was that even though there might be duplication of data, some data sources provide more granular details of data found in other systems. For example; total labor cost resides in one system and the same labor cost broken down by department resides in other system.

Challenge No. 3
What questions do I have?
Start each analytics challenge by asking questions, not gathering data

Every analytics journey, no matter its significance or length, should start with a definition of the business questions facing you and an establishment of what the desired outcomes should be. The question could be as simple as: what’s the year-to-date labor-cost-ratio by department/property? Once this has been done, you can now start identifying the pieces of data needed for the required analytics that might help answer the questions posed. More often than not, there is the temptation to gather all the available data before deciding what analytics needs to be done. Defining the questions first, enables you to not only narrow your focus to specific subject areas, but it also prompts you to explore and use readily available analytics or datasets that may already exist within your systems. If any information gaps are identified, you can then go out and get the required data to fill the gaps. This is where the knowledge gained from the previous two challenges helps you realize value quickly. You should by now be familiar with your data sources and the type of information each one contains. Note that the previous challenges did not ask you to gather data, rather the focus was on knowing where to go for your data needs.

Challenge
Basic Level:  Even though you may have numerous questions that need answers, I would suggest that you focus on the top five high priority issues that frequently need answers. These could include the metrics and performance indicators over which you have significant decision-making influence.  There’s no need to rack your brain on this. Think about your daily tasks and decisions and list your top five information needs. It doesn’t matter whether you currently get this information or it’s on your wish list.

Advanced Level: Your problematic subject areas could include revenue management, labor cost, employee productivity, etc. Then under each subject area think about the relevant questions that always go unanswered. If you do not have formalized KPIs in place, now will be a good time to create them. Your KPIs do not need to be complicated or contain fancy terminology. Just something simple enough for you and others within your organization to understand and monitor.  If you already have formalized KPIs in place, take time to review their relevance to your strategic vision. A lot might have changed since the KPIs were developed. The same kind of review can be done for internal and external benchmarks.

Collaboration Forum
I encourage you to participate by commenting on the newsletter posts or via our forum (http://bigdataworkout.freeforums.net), to enable you to ask questions of each other, discuss how challenges were tackled, and also raise issues/problems that you encounter. Comments are meant to be interactive as well as educative, thus I’ll urge users to be respectful of each other.

Samuel Ayisi is the head of analytics with Leumas Solutions. He can be reached at sayisi@leumassolutions.com.

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