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5 Powerful Excel Functions That Make Work Easier

5 Powerful Excel Functions That Make Work Easier

If you’ve just started learning how to use Microsoft Excel, you’ll probably have a lot of questions to ask about the functions of the program. Because let’s face it, despite being exceptionally useful, Excel can be a very complicated application. It’s like a hammer when your most frustrating reporting tasks at work resemble nails.

Aside from great Excel features such as flash fill, pivot tables, and conditional formatting, Excel also has a lot of powerful functions that will help save time when creating spreadsheets. Invest some time in learning to use Excel so you can prepare and manage complex reports, as well as perform what-if analysis on data like a pro!

To help you get started, here are 5 important Excel functions you should learn today.

1. The SUM Function

The sum function is the most used function when it comes to computing data on Excel. This function works to sum a group of numbers in a specific set of cells. This means you don’t need to type a long cumbrous formula just to calculate the sum of all the data you need. Because of its popularity, newer versions of Microsoft Excel have a button specifically for this function.

This function is performed by typing the formula on the function bar and highlighting the cells you want summed before clicking “Enter”. You also need to be careful in highlighting cells, as Excel will sum everything you include. If this happens, you can easily click the “Undo” button to reset the values back to its original state.

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SUM function

    The syntax formula for sum function is “=SUM” (number1, number2, etc.).

    In this image, the sum function for the cells C2 through C7 is obtained through the formula “=SUM(C2:C7)”, giving you the result of 33161.

    2. The TEXT Function

    Text function is a useful tool that helps convert a date (or number) into a text string in a particular format. It falls in the category of string formulas that converts numerical values to a string. It is handy when users need to view numeric data in a readable format. Take note that the “TEXT” formula only works to convert numeric values to text. Therefore, its results cannot be calculated.

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    TEXT FUNCTION

      The syntax formula for text function is “=TEXT” (value, format_text).

      • “Value” refers to the particular number you wish to convert to text.
      • “Format_text” defines the format of the conversion.

      In this example, the user uses a text formula to find the abbreviated day for the date “=TEXT (B2, “ddd”)”.

      3. The VLOOKUP Function

      VLookup is powerful Excel function that is often overlooked. Users will find it useful when they need to find specific data on a large table. You can also use VLookup to search for names, phone number, or specific data on your sheet. Instead of manually looking for the names and wasting time scrolling through hundreds of data, the VLookup function makes this process faster and more efficient.

      vlookup

        Image: spreadsheeto.com

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        The VLookup formula is “=VLOOKUP” (lookup_value, table_array, col_index_num, *range_lookup*).

        • “lookup_value” is the data you want to find.
        • “table_array” is the data column where you want to limit your search.
        • “col_index_num” is the column number within the table that you want to return a value from.
        • “range_lookup” is an optional argument that allows you to search for the exact match of your lookup value without sorting the table.

        4. The AVERAGE Function

        The average function is an extremely useful tool for getting the average value in a range of cells. Like the sum function, it is frequently used in computing and analyzing data on spreadsheet. Basically, the average function works to find the “arithmetic mean” for a group of cells. Aside from the average function, Excel also has the median and mode function.

        Average Function

          The syntax formula for the average function is “AVERAGE” (number1, number2, etc.).

          • “Number 1” refers to the first number in the range where you want the average.
          • “Number 2” is the additional reference of the average range. You can get an average of up to a maximum of 255 cells.

          Additional ­­Examples:

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          “=AVERAGE (A2:A10)” – computes the average of numbers in cells A2 through A10.

          “=AVERAGE (B2: B10, 7)” – computes the average of the numbers in cells B2 through B10 and the number 7.

          5. The CONCATENATE Function

          This function is a good time saver when you need to combine data from 2 or more cells. Unlike the merge tool which physically merges two or more cells into a single cell, the concatenate function only combines the contents of the combined cells. In the latest version of Excel ( 2016), the concatenate function has been replaced with concat function and will be incorporated in more future versions of Excel.

          Average Function

            The syntax formula for the concatenate function is “CONCATENATE” (text1, [text2…text_n]),

            • “Text1, Text2…text_n” are the data you want to combine.

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            The Productivity Paradox: What Is It And How Can We Move Beyond It?

            The Productivity Paradox: What Is It And How Can We Move Beyond It?

            It’s a depressing adage we’ve all heard time and time again: An increase in technology does not necessarily translate to an increase in productivity.

            Put another way by Robert Solow, a Nobel laureate in economics,

            “You can see the computer age everywhere but in the productivity statistics.”

            In other words, just because our computers are getting faster, that doesn’t mean that that we will have an equivalent leap in productivity. In fact, the opposite may be true!

            New York Times writer Matt Richel wrote in an article for the paper back in 2008 that stated, “Statistical and anecdotal evidence mounts that the same technology tools that have led to improvements in productivity can be counterproductive if overused.”

            There’s a strange paradox when it comes to productivity. Rather than an exponential curve, our productivity will eventually reach a plateau, even with advances in technology.

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            So what does that mean for our personal levels of productivity? And what does this mean for our economy as a whole? Here’s what you should know about the productivity paradox, its causes, and what possible solutions we may have to combat it.

            What is the productivity paradox?

            There is a discrepancy between the investment in IT growth and the national level of productivity and productive output. The term “productivity paradox” became popularized after being used in the title of a 1993 paper by MIT’s Erik Brynjolfsson, a Professor of Management at the MIT Sloan School of Management, and the Director of the MIT Center for Digital Business.

            In his paper, Brynjolfsson argued that while there doesn’t seem to be a direct, measurable correlation between improvements in IT and improvements in output, this might be more of a reflection on how productive output is measured and tracked.[1]

            He wrote in his conclusion:

            “Intangibles such as better responsiveness to customers and increased coordination with suppliers do not always increase the amount or even intrinsic quality of output, but they do help make sure it arrives at the right time, at the right place, with the right attributes for each customer.

            Just as managers look beyond “productivity” for some of the benefits of IT, so must researchers be prepared to look beyond conventional productivity measurement techniques.”

            How do we measure productivity anyway?

            And this brings up a good point. How exactly is productivity measured?

            In the case of the US Bureau of Labor Statistics, productivity gain is measured as the percentage change in gross domestic product per hour of labor.

            But other publications such as US Today, argue that this is not the best way to track productivity, and instead use something called Total Factor Productivity (TFP). According to US Today, TFP “examines revenue per employee after subtracting productivity improvements that result from increases in capital assets, under the assumption that an investment in modern plants, equipment and technology automatically improves productivity.”[2]

            In other words, this method weighs productivity changes by how much improvement there is since the last time productivity stats were gathered.

            But if we can’t even agree on the best way to track productivity, then how can we know for certain if we’ve entered the productivity paradox?

            Possible causes of the productivity paradox

            Brynjolfsson argued that there are four probable causes for the paradox:

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            • Mis-measurement – The gains are real but our current measures miss them.
            • Redistribution – There are private gains, but they come at the expense of other firms and individuals, leaving little net gain.
            • Time lags – The gains take a long time to show up.
            • Mismanagement – There are no gains because of the unusual difficulties in managing IT or information itself.

            There seems to be some evidence to support the mis-measurement theory as shown above. Another promising candidate is the time lag, which is supported by the work of Paul David, an economist at Oxford University.

            According to an article in The Economist, his research has shown that productivity growth did not accelerate until 40 years after the introduction of electric power in the early 1880s.[3] This was partly because it took until 1920 for at least half of American industrial machinery to be powered by electricity.”

            Therefore, he argues, we won’t see major leaps in productivity until both the US and major global powers have all reached at least a 50% penetration rate for computer use. The US only hit that mark a decade ago, and many other countries are far behind that level of growth.

            The paradox and the recession

            The productivity paradox has another effect on the recession economy. According to Neil Irwin,[4]

            “Sky-high productivity has meant that business output has barely declined, making it less necessary to hire back laid-off workers…businesses are producing only 3 percent fewer goods and services than they were at the end of 2007, yet Americans are working nearly 10 percent fewer hours because of a mix of layoffs and cutbacks in the workweek.”

            This means that more and more companies are trying to do less with more, and that means squeezing two or three people’s worth of work from a single employee in some cases.

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            According to Irwin, “workers, frightened for their job security, squeezed more productivity out of every hour [in 2010].”

            Looking forward

            A recent article on Slate puts it all into perspective with one succinct observation:

            “Perhaps the Internet is just not as revolutionary as we think it is. Sure, people might derive endless pleasure from it—its tendency to improve people’s quality of life is undeniable. And sure, it might have revolutionized how we find, buy, and sell goods and services. But that still does not necessarily mean it is as transformative of an economy as, say, railroads were.”

            Still, Brynjolfsson argues that mismeasurement of productivity can really skew the results of people studying the paradox, perhaps more than any other factor.

            “Because you and I stopped buying CDs, the music industry has shrunk, according to revenues and GDP. But we’re not listening to less music. There’s more music consumed than before.

            On paper, the way GDP is calculated, the music industry is disappearing, but in reality it’s not disappearing. It is disappearing in revenue. It is not disappearing in terms of what you should care about, which is music.”

            Perhaps the paradox isn’t a death sentence for our productivity after all. Only time (and perhaps improved measuring techniques) will tell.

            Featured photo credit: Pexels via pexels.com

            Reference

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