Effectively analyzing historical data: Agile history archive

What good is the data you’re collecting throughout your supply chain if you can’t utilize it effectively? It’s a question that continues to plague companies from every industry – and it’s why organizations turn to experts for help with analyzing their historical data.

A successful product development teams uses data from across the enterprise to inform decision-making and improve response times to challenges. However, it’s not enough to simply collect the information and store it on company servers; organizations need to drill down into this data to identify trends and make effective decisions.

Predictive analytics is the name of the game in supply chain data.Predictive analytics is the name of the game in supply chain data.

 

How do companies use supply chain data?

There are several important uses for the steadily increasing amount of information that companies collect on a daily basis. Here are only some of the ways organizations are utilizing data to improve their operations:

  • Enhance transparency: When you can see all of the data throughout the organization, you have greater transparency into your operations – which means that outside actors (like the government or other regulatory bodies) will be able to gauge your level of¬†compliance. This is especially important for organizations within the high tech and medical device industries.
  • Reduce risk: Effective risk management is possible through data analysis, as well, according to Computerworld. By analyzing historical information, organizations can assess the likelihood of a problem and its potential impact. Historical analysis, risk mapping and scenario planning are all made possible by data analytics.
  • Increase visibility:¬†Supply Chain Dive contributor Edwin Lopez noted that logistics visibility is one of the main use cases for utilizing supply chain data to derive value within operations. Being able to pinpoint problems and to address issues immediately, before they become full-fledged crises, is integral.

Predict to stay ahead

The name of the game is predictive analytics – by using existing information about customer preferences, logistics challenges and supplier pitfalls, organizations can effectively predict what the business landscape looks like at any given moment.

“[Another use of data] is getting some better form of demand and supply synchronization,” supply chain data expert Adam Mussomeli told Lopez. “There is a pretty long history of people building things in the hopes that it’s what the market wants, but it turns out the market does not.”

To this end, product data can help executives know when to adjust product design to meet demand. This is a better alternative than the build-it-and-hope method that Mussomeli alluded to.

When it comes to analyzing your operation’s data and making sure you’re pulling out all the right insights so you can make the best design decisions, it starts with storing the data properly so when you retrieve it for analysis, you have access to the proper channels.

Inspirage can help your company maintain an historical archive so you can manage this access and facilitate better decision-making. Get in touch with the supply chain data experts at Inspirage today for more information about how we can help you make the most of your enterprise information.


 

Kim Galeazzi

Kim Galeazzi | Key Contributor

Kim Galeazzi has has over 15+ years of experience working with Agile PLM. At Inspirage he plays a technical lead role on projects ranging from Agile Product Lifecycle Management (PLM) implementations to upgrades, data migration, Engineering Collaboration (MCAD and ECAD CAD - PLM connectors) and PLM - ERP integration.