{"id":6848,"date":"2017-05-30T08:30:00","date_gmt":"2017-05-30T08:30:00","guid":{"rendered":"https:\/\/arliemediadesign.com\/?p=6848"},"modified":"2025-03-29T08:22:31","modified_gmt":"2025-03-29T08:22:31","slug":"assumptions-guesses-and-pivot-tables-from-data-to-discovery","status":"publish","type":"post","link":"https:\/\/www.happy.co.uk\/blogs\/assumptions-guesses-and-pivot-tables-from-data-to-discovery\/","title":{"rendered":"Assumptions, Guesses and Pivot Tables: From Data to Discovery"},"content":{"rendered":"\n

Most of us will say \u201cYES\u201d to most or all of those questions, if for no other reason than we\u2019d be embarrassed to admit otherwise. We also have lots of data which should have informed our claimed understanding, but how many of our assumptions and beliefs about our performance have been challenged, dismissed or reinforced by looking at our data?<\/p>\n\n\n\n

Probably, and here I\u2019m making an assumption, very few.<\/p>\n\n\n\n

This could be for many reasons. Data is boring and, at first glance, impenetrable. We often have no idea at all why we have the data we have, often data is amassed as some sort of corporate comfort blanket, collected with the utmost diligence and never used.<\/p>\n\n\n\n

We know that all this data could help us understand our business better \u2013 but data is just, well, data really.<\/p>\n\n\n\n

This is where Microsoft Excel comes in. After a bit of sorting there, an auto filter here, we start seeing little glimpses into the potential our data promises.<\/p>\n\n\n\n

These odd little nuggets of information may well be useful but they\u2019re not pretty or easy to share. So, we may start playing with some formulas \u2013 SUMIF(S), COUNTIF(S), and AVERAGE. All very fine formulas that have served us all well, but once again, can be a little labour intensive.<\/p>\n\n\n\n

What we really need is some way of turning our Data into Information. I remember vividly the moment I understood the difference \u2013 Data is just data, it tells you very little if anything at all. It only becomes information when it\u2019s distilled into small chunks that tell you something you didn\u2019t know (or confirms something you only guessed).<\/p>\n\n\n\n

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And here is where I finally introduce the Pivot Table.<\/p>\n\n\n\n

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A basic Pivot Table.<\/em><\/p>\n\n\n\n

The Pivot Table is an amazingly sophisticated feature of Excel, which, once mastered, can transform massive amounts of data into meaningful information. This doesn\u2019t mean your assumptions and guesses are worthless; they are the starting point. We often start using Pivot Tables and Pivot Charts to test these assumptions and it\u2019s often pleasing to find how our close our instincts can be to reality.<\/p>\n\n\n\n

Pivot Tables and Pivot Charts gives us the facility to quiz our data in many different ways, and to place those summaries right next to each other. It allows you to transform that data with a few simple clicks \u2013 and it can become quite intoxicating to realise what control you can finally take of all this data!<\/p>\n\n\n\n

But rather than be proved right, how much more exciting is it to be proved wrong? The biggest thrill I\u2019ve had discovering Pivot Tables was when a simple Pivot Table proved that something I believed to be a \u201cfact\u201d about a course we ran was completely wrong. That was fantastic! This data, honed down to useful information, had told me something that completely changed my understanding of a part of our business that I was meant to be the expert in!<\/p>\n\n\n\n

So why is being wrong so right? Often, you might be delving into this data because your organisation wants to make more, spend less, be quicker, be bigger \u2013 so finding out where you\u2019re wrong is a great place to start. Challenge those assumptions, find the hidden stories and then share them with the rest of your organisation with some wonderfully informative Pivot Tables, Pivot Charts, and Dashboards.<\/p>\n\n\n\n

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Related blogs<\/h3>\n\n\n\n