In the fast-paced world of brewing, keeping up with consumer demands can be as intricate as the brewing process itself. Breweries have long since realized the importance of understanding demand patterns to optimize production, distribution, and marketing strategies. However, the trick isn't just in recognizing the average demand but in pinpointing and understanding the outliers. Here's why.

Why Should Breweries Care About Demand Outliers?
Outliers in demand patterns are those unexpected spikes or drops that deviate from the usual order volume. They're essential for two main reasons:

Opportunities for Growth: An unexpected spike in demand for a particular brew might indicate an emerging trend or a newfound preference among consumers. Recognizing this can allow breweries to capitalize on the opportunity, adapt their production schedules, or launch targeted marketing campaigns.

Mitigating Losses: On the flip side, a sudden drop in demand might signal an issue – perhaps a competitor's campaign is impacting sales, or there's a broader market shift. Identifying such drops early can help breweries adjust their strategies accordingly.

Standard Deviation: Understanding the Spread
So, how do we recognize what's 'usual' and what's not? Enter Standard Deviation.

Imagine every brew has an average monthly sales figure. Standard deviation, in this context, measures how sales numbers spread around this average. A small standard deviation indicates that sales are generally close to the average, while a large one shows more variability. If sales figures for a particular month fall way outside this spread, they might be considered outliers.

As an example, review the below chart that shows most of the results falling within an expected range, but four outliers are also present; two on either side of the expected range (that are highlighted for review through color and size). 

Control Charts: Visualizing the Demand
A control chart offers a graphical representation of demand over time. With the average demand at its center, the chart will have bounds indicating where 95% (often set at 2 standard deviations) or 99.7% (often set at 3 standard deviations) of all data points  should fall.

Data points that lie outside these bounds are potential outliers, signaling unexpected highs or lows in demand. Such a visual aid can be invaluable for breweries, enabling them to respond promptly to changes in the market

In the below example, we can see that the most recent Monday and Tuesday have been above the normal range; and that although Wednesday and Thursday have bounced around a bit, total demand has been falling in the expected range.