# What is Long Term Variation in Six Sigma?

You will need to understand long term variation to launch a successful Six Sigma initiative. When underlying disturbances are added to the natural short-term variation, the overall combination is called the *long-term variation *of the process. In many cases, it’s written with a simple *LT* notation.

If you look at an extended process behavior graph, you’ll notice something besides pure random variation is going on. Notice that the range of short-term variation doesn’t stay locked at a single level. Instead, it shifts and drifts up and down over time. These bumps and currents — called *disturbances to the process* — are emphasized with overlaid lines.

## Long-term variation’s non-random behavior

As opposed to random, short-term variation, these underlying disturbances are *non-random* over the long term. You can approximate them with a line, a step, a curve, or a repeated pattern.

With the proper detection techniques and tools, you can see what part of your process is affected by non-random forces. If the process is to assemble a proposal, and if the critical output of that process is how long it takes to create the proposal, you want to look at the variation patterns in the output of the process.

You can see the *output variation,* or changes in the number of incoming calls at a call center per hour. If the output metric varies in a non-random way, you can safely say that some combination of special cause factors has affected the volume of incoming calls.

When you hear “special cause,” that means that the output has varied to an extent that is inconsistent with what you would expect from purely normal, short-term, natural — or random — influences. You know that something non-random has occurred, and, therefore, you know that you can find the cause and solve the problem.

A good way of depicting the difference between short-term and long-term variation in a process is by using two probability distributions. Notice that, over time, the long-term variation is wider than the inherent, short-term variation.

Non-random variation is caused by special forces whose effects on the process are readily observed and understood. Consequently, this non-random variation is also called *special cause variation* or *assignable cause variation.*

## How to compute long-term variation

Calculating the long-term variation of a characteristic is identical to calculating its overall variation. Therefore, the overall standard deviation is the formula you use to quantify the level of long-term variation in a characteristic.

The calculated long-term variation should always be greater than or equal to the calculated short-term variation.

For any long-term variation you find, you can immediately create solutions to solve the problem, whether that’s conducting routine preventive maintenance on your drills, making the maintenance procedure so easy that anyone can understand and adhere to it, creating redundant systems in case equipment breaks down or a contingency plan in the event of losing a principal leader, or whatever.