Organisational Entropy

Entropy is a concept that has a number of applications, but as a statistical measurement  of thermodynamics, it is the state of disorganisation within the components of a larger system. An example of this is a car battery. When a car battery is fully charged, the molecules are all organised and lined up and there is plenty of charge available for output. This is called a Low Entropy state. As the battery releases it's charge, the molecules become more and more disorganised until there is no charge available for use. This called a High Entropy state.

When applying entropy to businesses, a high entropy organisation has multiple data sources in disparate locations and formats. Data is not collected appropriately and not well managed. There is little or no knowledge about how things work, and colleagues simply carry out their tasks without knowing why, relying on tradition. There are multiple versions of the same measurements and none of them balance or agree leading to decision paralysis at all levels. Operations are siloed in disparate departments without knowledge across these departments, making change very difficult to achieve. Teams, sections and departments have rigid hierarchical structures and agendas and goals are not aligned and in many cases pulling in entirely different directions. Customers of high entropy companies are often frustrated, as they are passed from department to department, chasing up problems, often having to repeat themselves over and over again.

A Low Entropy organisation is the exact opposite. Information is gathered appropriately and stored and managed. Colleagues have detailed knowledge of the systems and processes they use and can make changes when required without creating more errors. Measures balance with each other. There is one version of the truth and colleagues all agree on the state of the business and are able to make the decisions to take things forward. There is close cooperation across teams, sections and departments due to alignment of objectives and goals...... and your customers are happy.

In short... Low Entropy is good.... High Entropy... not so good.

In this blog I will be referring to lowering the entropy of organisations from a data perspective.