HOW DATA ANALYTICS POWERING THE MODERN SUPPLY CHAIN OPERATIONS:

“The goal is to turn data into information, and information into insight.” - Carly Fiorina, Former CEO of HP

Optimize supply chains with advanced analytics:

"Without data, you're just another person?with an opinion."?But that's not enough.?

In order to have an impact,?we need to transform that data into insights.?In this article, I'll look at five types of data analytics?in practical supply chain perspectives that we can use to analyze, optimize,?and automate our supply chains.?

Analytics is a journey that always starts?with collecting and cleaning and organizing our data.?Once that's done, we can choose?one of the five different approaches to analytics.?

1.????Descriptive Analytics:

The most basic approach is descriptive analytics.?Descriptive analytics involves sorting and filtering data?so that we can see patterns?and describe what has happened in our supply chain.?

When we perform descriptive analytics,?we often use statistics.?We could be looking at past sales records,?production volumes, or inventory levels.?And we might be talking about average inventory levels?or average lead times.?

2.????Diagnostic Analytics:

Next is diagnostic analytics.?Diagnostic analytics compares what actually happened?to what we expected to happen.?

For example, we could use diagnostic analytics?to compare a sales forecast to our actual sales results.?Diagnostic analytics is useful for doing root cause analysis?and implementing statistical process control.?So it's often combined?with continuous process improvement approaches,?such as Lean and Six Sigma.?

3.????Predictive Analytics:

Then there's predictive analytics.?With predictive analytics,?we use the past to predict the future?or in more technical terms,?we use historical statistics?to estimate future probabilities.?We can use predictive analytics?to think about how we should prepare for managing risks.?

Let's say our warehouse is located in a region?that floods once every five years.?An example of predictive analytics would be?to project that there's a 20% chance of flooding next year.?

4.????Prescriptive Analytics:

Many supply chains are now going a step further?and using artificial intelligence?to implement prescriptive analytics.?Prescriptive analytics combine historical data?with real-time inputs to recommend actions.?

Have You heard About "Application of Recommendation Engine - ARE"?

You may hear this called a recommendation engine,?because the system is actually giving suggestions?to a human about what actions they should take.?A common challenge with prescriptive analytics?is that humans may not understand?why the recommendation was made.?

The recommendation engine?can seem like a mysterious black box?that just churns out instructions.?

5.????Advanced Analytics:

At the highest level, we have advanced analytics,?where computers are able to make decisions autonomously.?That is the long-term goal?for many digital transformation efforts.?

All five levels of supply chain analytics?play a role in digital transformation.?By understanding the differences,?you can choose the right approach?for the challenges you're facing today?and for the supply chain you're building for the future.