Analytics. The Oxford Dictionary definition may seem dull, BUT, when viewed from the right perspective - is powerful.
“The systematic computational analysis of data or statistics”
Foundational Pillars of Analytics
Data
A business has many components. Whether it be hundreds of stores across a country or millions of ads across the internet - if collected (written down) to reference in the future, this is data. Analytics includes collecting and storing data.
Systematic Computation
Systematic computation in my words means having a process (computer) do things so they are easy. For instance, while you can count out the number 89367550 and repeat it ninety two times (89367550x92) … it will take a while. A calculator finds the answer instantly.
Analysis
Analysis is making something complex simple in order to understand it. The Data is complex, Systematic Computation makes it simple and then we can understand it.
The Function of Analytics
To inform decisions through actionable insights.
Example: One million people around the globe make purchases on an ecommerce website weekly. Analytics allows a single individual to see return on ad spend to determine if marketing efforts are profitable.
Advanced Example: Forecasting demand (predictive analytics), informing a business how much inventory to acquire for a large future promotion to optimize efficiency.
Decisions
Without analytics results can often be unclear. Additionally, the interpretation of results is often subject to bias. The best way to avoid bias is with strong analytics. Strong analytics entails data driven conclusions with predetermined statistical significance.
Biases
Confirmation Bias - The tendency to interpret new evidence as confirmation of one’s existing beliefs or theories.
Anchoring Bias - Being overly influenced by the first piece of information we receive.
Availability Heuristic - Placing more value on the first idea that comes into your head.
Progress Bias - Overstating positive actions while downplaying negative ones.
Survivorship Bias - Paying too much attention to successes, while glossing over failures.
The IKEA Effect - Placing too much value on the things we’ve done ourselves, often while discounting other people’s smart ideas or good work.
Overconfidence Bias - Thinking your contribution is more important than it is.