In past blogs, we discussed how small businesses could utilize big data from a big-picture view. Let’s take a more nitty-gritty view today. We’ll dive into predictive and prescriptive analysis.
Predictive analysis has been around forever. Your company analyzes current data to predict future business. No longer done by hand, the newest predictive software uses not only statistics and modeling but machine learning and AI.
Patterns emerge from historical data and transactions that identify future risks and opportunities. How are these applied?
The patterns help detect fraud. With ongoing fraud and network security issues, time is of the essence to spot vulnerabilities. Analytics can spot anomalies in real-time.
Analytics advance your marketing by identifying the best customers and promotions. Your business can design more ways to appeal to those customers with targeted advertisements.
One of the most valuable uses of this analysis is allocating inventory and handling resources. Airlines use it to set ticket prices and hotels to determine the likely number of rooms booked per night. A manufacturer uses it to adjust orders to avoid too much-unsold inventory.
A prescriptive analysis takes predictive a step further by producing recommendations and specific courses of action. Wow, hard to envision. But, here goes.
In retail, prescriptive analysis suggests ideal product mixes, best product promotions, and forecasts demand more accurately. It reduces risk, as analysis produces several outcomes, not just an average.
We’ve all seen the news when towns on a flood plain rely only on averages. The prescriptive analysis shows you mother nature’s best and worst cases along with their probability.
Author: Kris Keppeler, a writer who finds technology fascinating and loves humor. She writes for Crossing Genres on Medium.com and Does This Happen to You? on Channillo. Award-winning podcast producer who enjoys telling stories. Follow her @KrisKKAria on Twitter or on LinkedIn.
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