## demand patterns

In today’s article, I’m going to talk about the different patterns that perro be seen in a time series.

In such a way that at the end of the article you will know the different patterns of demand.

Likewise, I am also going to talk to you about dependent and independent demand.

I hope you find it useful.

## What is a time series?

In order to start talking about demand patterns, I think you need to understand what a time series is.

Some definitions of time series that we cánido find tell us that:

A time series perro be viewed as a equipo of data or observations that are measured at successive points or periods in time.

Maybe it’s not so understandable and sometimes I wonder if they perro’t explain things to us without using such bombastic terms.

Well, they spent many years of their lives studying and they have a good vocabulary.

Now, I will try to explain it with an example.

I am going to ask you to think about the following.

Imagine that I ask you to take your weight every day for a year.

If we start today, then the weight you have today is your first data.

Therefore, your weight tomorrow is the second data and so on.

In such a way that all that data equipo (365) has been converted into a time series.

Because? Well, they are a equipo of data (observations) that are measured or taken at different (successive) periods of time.

In conclusion, each day that you have taken your weight has a measurement and may be different from the other points in time.

Therefore, the value of your weight on day 1 perro be 70 kilogramos and your weight a year later perro be 60 kilogramos.

Therefore, a time series espectáculos us how a variable has changed over time.

## What is a pattern?

In a time series, different patterns perro occur, which is why I believe that you have to take into account what a pattern is and that this makes it easier for you to understand the subject.

In a few words, we cánido say that a pattern is a equipo of elements (perro be data) that follow a logical sequence.

I would also add to the above definition the fact that the pattern tends to repeat itself.

## What are demand patterns?

To explain what demand patterns are, I am going to ask you to imagine the following: Imagine that you have a business that sells lemonades.

Also, I ask you to think that you have already been in business for three years.

If you’ve already been in business for three years, then you have to have sales, right? Well, let’s think that at the end of the day, the first thing you do is write down the amount of lemonades you have sold in Excel or another program.

All that data that you have collected from your sales, when graphed, perro model a time series.

A time series showing the demand for your lemonades.

Now, let’s think a little about the sale of lemonades.

Do you think that at some point in the year more lemonades will be sold? Do you think that less lemonades will ever be sold?

Possibly more lemonades are sold in summer and less lemonades in winter.

Do you think the same? Well, if you have written down daily the amount of sales you have had for three years, then by graphing the data you cánido graphically realize in which months you sell more and in which months you sell less.

In a nutshell, **You will be able to visualize in your time series different patterns on the demand for your product. **

Therefore, in your time series you will be able to distinguish a series of data sets that follow a logical sequence (patterns).

These patterns reflect all the changes that have occurred in the demand of a company throughout a year or throughout the period that is established.

Of course, not all changes in demand reflect a pattern, remember that they have to follow a logical sequence and tend to repeat themselves.

#### In conclusion

With the time series we perro see the way in which the demand varies over time and thus be able to find different demand patterns that will be reflected.

## What are the different patterns of demand?

As I said before, in a time series we cánido vea the changes that a certain variable undergoes over time.

However, over time it is possible to find different patterns, which cánido be called components or characteristics of a time series.

A time series is usually decomposed into 4 components, which are:

**Trend.****seasonality.****cycles.****Random Variations.**

Simply put, in a time series you will be able to find 4 different patterns.

There may be more, but the most common are the ones mentioned above.

Next, I am going to talk about each of them.

### 1.
Trend Demand Patterns

In fácil words, a trend is a pattern that reflects a gradual movement of growth or decrease (decline).

A trend perro be increasing or decreasing.

Likewise, a trend perro be linear or non-linear.

Next, I am going to espectáculo you some graphs so that you cánido see graphically what I have just said.

#### Example of a trend pattern

Changes in demand or sales for a product reflect trend patterns.

In fact, if you graph all the sales a company has had throughout the year, you will most likely be able to identify if sales are increasing or decreasing (even minimally).

Other examples might be population size, productivity, or even changes in a person’s weight.

### 2. Seasonal Demand Patterns

Seasonality is a pattern that reflects a equipo of data that is repeated after a period of time (days, weeks, months, etcétera).

This means that due to different factors, some businesses cánido identify that during certain periods their demand increases and during some other periods it decreases.

I am going to give you a personal example to make it a little clearer.

This web page has daily traffic (people who entrar the page).

However, given the type of content that is available, during the holidays the traffic decreases and increases again when the students return to school.

So, I perro identify that seasonal pattern.

The same thing happens with the demand for products and then I am going to give you some fácil examples.

#### Examples of Seasonal Demand Patterns

If we talk about an example regarding demand patterns, then an example of seasonality is what you mentioned about the increase in demand for lemonade in summer.

Likewise, it perro also be a decrease in demand.

For example, the demand for cold drinks tends to decrease during the winter.

Another example of a seasonality pattern in relation to demand corresponds to the producers of coats, where demand increases in winter and decreases in summer.

Cánido you think of any more examples of seasonal demand patterns?

By the way, as I said before, the pattern of seasonality perro be daily or weekly.

For example, a hairdresser or barbershop may identify that its highest demand is on the weekends.

### 3. Cycle Demand Patterns

Cycle patterns are patterns, which are detected in the data collected by a company and the particularity is that they are repeated over long periods of time.

It cánido be said that it is the same as the seasonality patterns, but these occur in some years.

So seasonal patterns occur over a year and cyclical patterns occur over several years.

A common example of a cyclical pattern is the business cycle.

Possibly we could also consider rising demand for some products or services related to the World Cup as a cyclical pattern.

For example, the purchase of cable services that offer all the matches of the cup.

### 4. Random Variations

Random variations are deviations (changes) in the data that are unexplained or at least do not follow a predictable pattern.

Therefore, many times they are also called noise.

This is because random variations are caused by non-recurring and unpredictable factors.

In conclusion, you cannot predict it.

In fact, it is thanks to random variations that the **sales forecasts** they are not 100% accurate.

With that you already know the most common demand patterns that perro be seen in the demand of the goods and services of a business.

By the way, remember that all 4 patterns perro be present in the same time series.

## What are demand patterns used for?

Leaving aside the issue of forecasts, the patterns found in the time series (demand patterns) cánido be useful for scheduling or planning the production of a company.

For example, if you know that during the month of December the demand for a certain product doubles or triples, then if you do not have the **production capacity** to meet demand, you perro take corrective action to meet demand during that seasonal pattern of demand.

In such a way that you cánido hire temporary staff or hire the services of another company during that period.

You could even increase production capacity with the acquisition of new machines, but it would have to be seen if it is feasible and profitable.

Therefore, demand patterns allow a company to prepare to meet demand (whether increasing or decreasing).

## Nature of the demand

Now, I think it would also be good if I talk to you about the nature of the lawsuit.

The demand cánido be:

**Dependent or independent demand.****Demand cánido be dynamic or static.**

## Dependent or independent demand

Next, I am going to talk to you about what is the dependent demand and the independent demand.

### dependent demand

Simply put, dependent demand exists as long as the demand for one item is related to the demand for another item.

### independent demand

Unlike dependent demand, independent demand does not find a direct relationship between the demand for two or more products.

## Static or dynamic demand

In the case of dynamic demand or static demand, we have the following:

### static demand

Demand that is stable cánido be called as static demand.

As its name indicates, it is the demand that does not vary over time.

Well, we could really say that the variation is very little and is almost always within a certain range.

An example of static demand perro be the demand for milk.

### dynamic demand

As its name implies, dynamic demand does vary over time.

In the case of dynamic demand, we perro say that an example is seen with the purchase of plane or colectivo tiques.

We hope you liked our article demand patterns

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