Value of Variance

All data analysts will keep a keen eye open for variance from the norm of any process or product measure. The main objective is to keep the performance of the measure stable and capable - within the acceptable norm.
Lets quickly look at a situation where there is no variance:

• Great quality
• Great performance
• Great predictability
• Very stable and capable process

But to achieve this, we would require 'machine' like people who can execute the process and these people will cost the company a lot of money to hire, sustain and retain as these people typically come with perfection all around them and taking decisions in a perfect world is almost impossible.

The downside of zero variance is:

• No mistakes - so no learning from mistakes
• No improvement possibility (in terms of knowledge)
• No growth path beyond what has been achieved

Variance gives the intent and the opportunity to dream beyond and the hope to achieve it. It promotes mistakes, lessons learnt, knowledge sharing etc - all provided, it is within an acceptable range. Variance promotes the business of an organization to grow and facilitates the true value of the organization (it's people) to be truly valuable - thus increasing the maturity of the organization.
This will in-turn create more visions for the organization, based on which the organization can go on a mission with the enhanced value.

Variance control should not be an overdrive as it would kill a lot of necessary aspects of the DNA of an organization.
This big picture on the value of variance is a must have view for all professionals. This is the basic intent of ensuring that variance must exist.
Yes, it cannot be beyond a certain limit and that is what the data analysts should be able to determine - keeping the intent of variance very much alive.