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I continue with the third part in my series on enterprise system pitfalls and now discuss the problem of what I call the infrastructure imbalance. I have two previous posts that introduce the topic of pitfalls of enterprise systems and discuss the pitfall of over abstraction.

Today I continue my series on enterprise system pitfalls and discuss the problem of over abstraction. Be sure to read my previous post which lays the foundation for this series.

Are we getting the economic return we should be with new technology innovation? In this article, I’m starting a series reflecting on common weaknesses in enterprise systems development, and am going to try to unpack as concisely as I can these pitfalls we fall into.  We’ll analyze why we stumble into these problems, our struggle recognizing the root causes, and the results.

HU talks with Bob Diachenko, the cybersecurity expert who discovered the breach, about steps hotels can take to prevent data incidents

A groundbreaking new report by the Urban Land Institute in Washington, D.C. explores sustainability in the hospitality industry and examines ways in which hotels are incorporating eco-friendly best practices into both operations and construction. The study includes insights from leading hotel owners, developers and investors.



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Part 7: Flex Your Data Muscles: A 12-Month Challenge to Get Analytics Working For You

08/10/2015
by Samuel Ayisi

We are now past the halfway mark in our 12-month “Flex Your Data Muscles” analytics challenge, and we’ve made significant progress towards achieving our goal. If you’ve undertaken all the challenges posed so far, we hope that you have been inspired to improve your existing analytics efforts. If you’re just getting to know about the challenge, refer to the Hospitality Upgrade newsletter issued in January 2015 by clicking here.

Analytics tools are just what they are… tools.

A successful analytics initiative is much more than the utilization of the latest fancy and/or complicated analytics tool. Your primary focus should be on the ability to analyze your data, extract relevant insights, and transform the resulting insights into smarter decisions and valuable transformative actions. The analytics tool(s) used to achieve this objective is not as relevant as being able to do the aforementioned and doing it well.

More often than not, people and organizations place too much emphasis on analytics tools, with very little consideration as to whether these tools are a “best fit” for them. It is true that there are great analytics tools on the market, and some do a better job at certain things than others. However, don’t get misled by the desire to acquire the latest shiny new toy. The analytics tool you select should not necessarily be the leading product on the market. Rather, one that best meets your needs in terms of cost, your available IT resources, skill/knowledge levels within your organization, compatibility with the way you do business, and your analytics goals. In some case you might not even need a new analytics tool, especially if you’re just getting started. Your existing software applications and office productivity tools may suffice.

The aforementioned doesn’t diminish the fact that certain tools may make analytics much more convenient and less complicated, especially for the end users. Nor does it ignore the role that intuitive analytics tools play in enticing the previously deterred within your organization to increasingly adopt analytics.

Just avoid being caught in the frenzy over a particular analytics tool. After all, tools are just what they are… tools. It is how you use these tools to achieve your analytics goals that really matters.

A Review of Last Month’s Challenge: Let’s Gather Some Data

Last month we set out to challenge ourselves to see if we could actually get our hands on the data we need for our analytics. No data… no analytics, right? The goal was to make sure that you were not only promised access to the data, but you could actually get and see the data. Hopefully, there weren’t too many obstacles in the data acquisition process. I’m sure that you were also mindful of the need to strike a balance between the cost and consequences of acquiring the data and the benefits of the value the acquired data adds to your analytics.

  • Were you able to get all the data you needed? If not, why?
  • Was the data given to you in the requested format?
  • Was it timely?
  • Was it relevant or what you requested? Or were you just given a huge data dump and asked to muddle through it?
  • At first glance, did it seem to be of high quality?

For those doing the advanced challenge, I hope that you took time to review your data security and access controls and how these controls helped in achieving your organization’s analytics goals. 

Series Recap: What We’ve Done So Far
 

Month

What we did

January

Challenge #1 - Where is my data?

Identify and create a list of your various data sources (both internal and external).

February

Challenge #2 - What’s in my data source?

Figure out exactly what's in your data sources.

For example:

Source A has revenue, reservations, and guest information

Source B has revenue, expenses, and departments

OR

Revenue is located in Source A, Source D

Guest Information is located in Source A (summary), Source C (detailed)

March

Challenge #3 - What questions do I have?

Identify and list the top five business questions that you frequently need answered. It didn't matter whether you currently get all the required answers or it's on your wish list.

April

Challenge #4 - What data can help answer my questions?

Map your information needs to your data sources. The emphasis was to utilize the information gathered during the first two challenges, and identify any data gaps.

May

Challenge #5 – Time for pit-stop

Review & refine results achieved so far.

June

Challenge #6 – Let’s get some data.

Get the data needed for your analytics.








































 
Challenge 7 (July): Which analytics tool(s) should I use?
 
One Tool May Not Be Sufficient
 
Depending on your role in the analytics environment within your organization there might be the need to use a number of tools in order to achieve your analytics objective. Different tools may be required for:
  • Data cleansing and formatting
  • Processing, calculations and analysis
  • Visualization (i.e. dashboards, reports, charts etc.) and interactivity (i.e. drill-down, further exploration etc.)
  • Distribution and collaboration

Note that in some instances, software packages that provide an “all-in-one” solution may not be the best option for you, because some modules of that solution may not perform as well as desired.

Challenge
 

Basic

Advanced

·         Make a list of all the software applications available to you that you believe can be used for analytics.

·         Identify all available software applications that can be used for analytics.

·         Assess the availability of the identified analytics tools to various departments (depending on their needs).

·         Determine whether your available analytics tools need upgrading.

·         Are there tools you currently do not have, but absolutely need to achieve your analytics goals?
















Comments and Hints

Basic Level:  Don’t forget your office productivity tools such as spreadsheets and locally installed databases. It would be a good idea to discuss this challenge with your colleagues and your IT team, as there might be analytics tools available to you that you are not aware of.

Advanced Level:  As part of this task, determine whether or not your various departments need access to particular analytics tools. Have you considered expanding access to already acquired analytics tools? Have you explored the analytics capabilities of your various systems and software applications? Some of them may have embedded analytics tools that you may find useful. Have you considered open-source analytics tools?

Collaboration Forum

I encourage you to participate by commenting on the newsletter posts or via our online 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.

About The Author
Samuel Ayisi
Head of Analytics
Leumas Solutions


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

 
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