You can’t determine your success without measuring what you do

Blog Author: Aaron Smith | May 21st, 2015

We live in a largely data driven world these days. However, most businesses believe that data analysis is limited to the big end of town. Nothing could in fact be further from the truth, and the analysis power that is available at your fingertips these days is probably far more than you appreciate.

The first step in any data analysis is the process of gathering the data. Many systems provide a wealth of data generation but it can take a bit of digging to determine how to unlock this and export it in a format that is useful. A good step may be to talk to the vendor to see what is available and how to access it.

Once you know that you can obtain the data, the next question is which tool are you going to use to actually perform the analysis. For most people the tool of choice will be Excel. Importing and working with data from external sources can mean requiring a higher level of understanding and experience with a product like Excel than average. This may mean becoming familiar with things such as Pivot Tables, Power Query, etc.

After getting the data into your tool of choice, you then need to perform the desired analysis. The best place to start such analysis is generally not in the tool you have just imported the data into. Here you need to take a step back and actually document what you are trying to achieve and break it down into manageable chunks. The other reason you should take this step is that there may come a day when the analysis needs to be handed off to someone else and you generally want to make it as easy as you can for them.

Now it is time to turn to your tool and convert the analysis you desire into actual formulas and calculations. Again, good practice is to build these up gradually from sub components. Having one massive formula in a cell can make debugging problems quite difficult. Using other areas to provide foundation calculations means you check your logic as you build your model.

Once you have completed your model you need to output it in a readable format. In many cases, this means simplifying the results and incorporating graphs and interactive elements. Here you really need to consider the audience for your analysis.

In many cases you want to compare your current results with those obtained historically. You also generally want to able repeat the whole exporting, importing and data analysis quickly and easily. This typically means you need to automate the process to reduce time but also reduce chances of error.

As mentioned, the easiest tool to achieve most analysis is Excel, and its support of powerful components like Pivot Tables, Automation and importation from various data sources. If you need help with the more advanced features of Excel then Correct is able to provide training to suit your needs. Contact us on (02) 8831 8200 to discuss your requirements.

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