This is part two of the “Flex Your Data Muscles” analytics challenge. If you are not familiar with this challenge, click here for the first article in the series. In summary, each month throughout this calendar year, you will be presented with one analytics-related challenge to tackle. The challenges, each with 2 levels (basic and advanced), will be presented and discussed via this newsletter and the Hospitality Upgrade magazine.

A review of last month’s challenge: Where is my data?

The first task of the series challenged you to identify all your internal and external sources of data. The purpose of the task was not to gather data, but rather help you identify your sources of data which could include software systems, data repositories, scheduled reports, and reports/data from external sources. Most of us are overwhelmed by the number of reports and the amount of data we have access to, such that, we tend to ignore a significant portion of them. However, for your analytics to be more meaningful there might be the need to include data from various sources, including some that you may have previously ignored.  As you went through the process of identifying the data sources I hope you discovered new sources of data or generated an interest in previously ignored data sources.

For the advanced challenge, the task was taken a step further by asking you to also review data-related issues such as access controls, the usability of the data, and how the data is currently being used. From a strategic perspective, emphasis should not only be placed on making data available for analytics (such as; ensuring data quality, building a data warehouse or granting appropriate access to data sources), but also on the relevance, privacy and security of the data being made available. If you’ve not already done so, I hope this exercise prompted you to review your data governance or consider creating one for your organization.

Challenge 2 (February): What’s in my data source?

Know where to get data relevant to your analytics
More often than not, there is a strong urge to gather all available data before deciding on what analytics needed to be done. However, prudence should caution you to resist this urge and rather place your initial focus on identifying your sources of data and knowing what data they contain. This knowledge provides guidance on where to look for data relevant to the analytics you need to do. Simply put... it’s not enough to know that a data source exists. You should also know what information/data resides in that source.

Meaningful analytics is all about relevance. Thus, it would be unwise and unproductive to include irrelevant data in your analytics or conduct analytics that may be insightful but have no relevance to you. This is why it is beneficial to have a general idea of what information/data resides in your data sources. Without this knowledge, you might end up spending countless hours and resources combing through a data source that does not contain the relevant data you need.

During this task, I hope that you come across new data and/or information that you previously did not know existed in your sources of data (especially within your software systems). Don’t be surprised if you find ready-to-use analytics, preformatted analytics that can be easily modified to meet your needs, or data points that can add clarity to other pieces of data you already use.

Challenge 2:




  • For each data source you identified in Part 1 of the series, create a list of the type(s) of information/data that can be obtained from that source.
  • For each data source you identified in Part 1 of the series, create a list of the type(s) of information/data that can be obtained from that source.
  • Next, assign the types of information/data to your lines of business & departments, ensuring that you consider the relevance of the data to the assigned entity. Do they really need to see this data? Are there any gaps in their information needs?
  • For information/data types that might seem ambiguous, create standard definitions that can provide clarity at the end user level.


Comments and hints:

Basic Level:  You may wish to use more generalized groupings of the information types such as: revenue, labor cost, food cost, guest information, and employee information. Use any layout you prefer.  Examples:

  • Layout 1
    • Data Source A: revenue, reservations, detailed guest information
    • Data Source B: labor cost, departments, employee information
    • Data Source C: revenue, departments, marketing expense, guest information
  • Layout 2
    o Revenue: Source A, Source C
    o Guest Information: Source A, Source C
    o Labor Cost: Source B

Remember to focus on the data sources and information that you assume will be most relevant to you, and don’t forget to seek the input of your colleagues as some of them might be more familiar with certain data sources.

Advanced Level:  While tackling this challenge, it would be a good idea to discuss your data needs with your vendors and other external parties to see what additional relevant data they might be able to provide.

Collaboration Forum:
I encourage you to participate by making comments on this newsletter or via our forum, 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.