Analytics must have a purpose a goal, If you think about it data can’t drive anything at all. In one sense decisions depend to a greater or lesser extent the questions asked. Why, How and What as proposed by Simon Sinek or alternatively the observe, orient, decide, and act (OODA loop) First conceived by US colonel John Boyd.
“Purpose-driven” means standing for something. How can it be socially useful? Is finance just for profit, investors and shareholders, or does it have a wider role in society, government and the economy?
Purpose driven analytics gives you a series of principles archive your goals and get benefit from yout analytics.
Guiding Principles of Purpose-driven Analytics
Ask Clear and Correct Questions
Ask precise questions based on the company’s best-informed priorities. Here, clarity is essential. This is exemplified by the questions “how can we reduce costs?”; “how can we increase revenues?”; “How can we improve the productivity of each member of our team?”. Analytics does noy pay off for vaguer questions such as “what patterns do the data points show?”
Identify Small Changes for Big Impact
Focuses on generating gains even on small improvements. There is a need to identify small points of difference to amplify and exploit because the smallest edge can make the biggest difference. For the fashion industry your looking at cutting cost by using less material. simpler and hence faster sewing techniques.
The impact of “big data” analytics is often manifested by thousands—or more—of incrementally small improvements.This is essentially Kaizen with data.
Leverage Soft Data or Embrace taboos
Get quality insights and generating sharper conclusions. It is at this point wherein the use of softer inputs such as industry forecasts, predictions from product experts, and social media commentary are given more emphasis. Soft data is essential when trying to connect the dots between more exact inputs.
Don’t be hasty to disregard imperfect information because the sample period is to short i.e days or weeks not months. For retail situations you ask question about the weather, sporting events, placement of goods no shelves. traffic through tills.
Connect Separate Data Sets
Capture the untapped value in data sets. This principle emphasizes the need to combine sources of information to make sharper insights. When different data sets are examined, the greater is the probability that problems can easily be fixed. This is helpful in scenarios such maintenance and maintenance failures. Here you can connect schedules maintenance essential HR data to operational reports on failure.
Run loops
The most successful companies to day often use OODA loops to collect data make decisions and take actions on continuous basis.