Microsoft Office Tutorials and References
In Depth Information
Other Trending Techniques
to actual data values. For instance, instead of charting each month’s sales for a single year, you could
chart the average sales for Q1, Q2, Q3, and Q4. With such a chart, you get a directional idea of
monthly sales, without the need to look into detailed data.
Take a look at Figure 8-30, which shows two charts. The bottom chart trends each year’s monthly
data in a single trending component. You can see how difficult it is to discern much from this chart. It
looks like monthly sales are dropping in all three years. The top chart shows the same data in a
directional trend, showing average sales for key time periods. The trend really jumps at you, showing that
sales have flattened out after healthy growth in 2011 and 2012.
Figure 8-30: Directional trending (bottom) can help you reveal trends that may be hidden
in more complex charts.
Certain lines of business lend themselves to wide fluctuations in data from month to month. For instance,
a consulting practice may go months without a steady revenue stream before a big contract comes along
and spikes the sales figures for a few months. Some call these ups and downs seasonality or business
Whatever you call them, wild fluctuations in data can prevent you from effectively analyzing and
presenting trends. Figure 8-31 demonstrates how highly volatile data can conceal underlying trends.
This is where the concept of smoothing comes in. Smoothing does just what it sounds like — it forces
the range between the highest and lowest values in a dataset to smooth to a predictable range
without disturbing the proportions of the dataset.