Office Organization & Efficiency

Easy Tricks to Help You Track Down and Analyze Research Data (Part 2)

  • Share This:
  • Digg!
  • submit to reddit

In the first part of this article we looked at how to get yourself organized, how to find sources for the information you need and simple tips for conducting an online Google search. In the second half of this article we are going to discuss what to do once you have identified sources for data and how to analyze what you find.

Using Database Analysis or Spreadsheets

In order to analyze the data you have gathered it is important to develop some type of comparison tool. Depending on the amount and type of information, as well as your ability to utilize database or spreadsheet tools, you can determine what method works best for you.

In the case of the new piece of $1MM equipment that the company may want to purchase, you will want to look at a variety of competitors to determine if they offer a similar piece of equipment and for what price. You may include a review of the similarities and differences that each piece of equipment has to offer. This way you can analyze just exactly what the company would be getting for its money. Here is an example:

Equipment

Company

Cost

(in millions)

Upgrades

(in thousands)

Annual Contract

Delivery Date (Months)

Alpha

$1

$50

1

6

Beta

$1.2

$15

1

3

Delta

$0.8

$25

.5

2

Sigma

$0.75

$40

0

1

Of course, this is purely fictional and doesn't contain the type of data that you might obtain; however, it does help you to visualize how you might go about setting up an analysis sheet.

If you use a database and download all the available information, then you will be able to create reports to help you organize the information in a variety of ways and enable you to do comparative analysis depending on your focus. These tools can provide statistics such as the mean, median, mode, and average, just to name a few.

Reading Statistical Data

Once you have gathered all the information you can to help answer your questions and have downloaded the numerical data into a database or spreadsheet, you will then need to review what you have found and come to some conclusions.

Be careful about drawing conclusions too early in your analysis though, as you might be swayed to believe one thing or another without giving full weight to the information you actually discover.

As you interpret your data, you should see how the information answers each of your questions and determine what kind of an argument you can make for or against moving in a specific direction. For example, if your boss wants to buy that $1MM piece of equipment, what arguments can you provide for this as an option versus what arguments can you provide against this as the option?

More than likely your boss is expecting you to provide her with all the relevant data about why she should or shouldn't move forward with a specific decision. This can be nerve-wracking as the responsibility is now on your shoulders to clarify your findings; however, if you have thoroughly gathered and reviewed the data available, your input could be vital to her.

Tracking Your Reference Material

When you gather information for your analysis, you may want to track the source of the data, especially if you are preparing a report for your supervisor's review. This means using citations in your work.

If you are putting together a written report that contains quoted material or ideas obtained from another source, enclose the author's name and the date of publication in parentheses following the material quoted or the ideas referred to (FranklinCovey 1999). In addition, you can use a bibliography (author name, source title, edition, publisher or press, city of publication, date of publication) at the end of your report or even footnotes throughout it depending upon your business needs.

Even if your work is contained in a less formal format, you should at least track where you have gathered the data you have used so you can refer to it at a future time should the need arise.

Tracking down and analyzing research data can take a lot of time; however, if you enjoy challenges you may find it fun to dig and compare.


Talk about it