Industrial organizations are still way behind in their data journey, in most of the cases these organizations are infact not collecting the important data. Even if the data is collected this isn’t being used the way Digital first organizations use their data, which is creating Datagraphs (interrelationships between different entities of the organization).
Uber analyzes data on more than twenty-five billion rides, which the taxi companies don’t. Netflix tracks people’s viewing preferences by the second, which the cable and television companies don’t. And Airbnb tracks where, when, and how long travelers stay and what they do and prefer, which the hotel chains don’t.
The typically analyses approach on the data with Industrial organizations have been descriptive and diagnostic.
Descriptive analyses to understand what happened with a product or service.
Diagnostic analyses by drilling down to the root cause of the outcomes, essentially identifying the why behind the what.
Learning from Digital world organizations this analyses is now moving to Predictive and Prescriptive.
Predictive analyses, based on Datagraphs, to forecast future events with different levels of probability, informed by data.
Prescriptive analyses offers recommended actions.
When these four analyses—descriptive, diagnostic, predictive, and prescriptive—are carried out on Datagraphs that build on data network effects, they offer deep and powerful insights for Industrial organizations.
Thinking Space 