Skip to content

Good OM Reading: Supply Chains and Data Analytics

April 7, 2017

The OM field will soon face a major change in the way we make decisions. Big data, data analytics, and business intelligence are all skill sets our OM students will need. The Gartner Group has just issued an interesting report on these concepts. Gartner identifies 4 core skill sets to support the successful adoption of analytics: Data engineers who make the appropriate data accessible and available for data scientists. Supply chain expert analysts who understand supply chain requirements and priorities to ensure the right tools are used. Data scientists who create predictive and prescriptive models. Citizen data scientists who are lighter versions of a data scientist who can build or choose models, but within a platform.

There is, of course, a shortage of data scientists. This is compounded for supply chain, which might not be viewed as attractive as finance, sales and marketing. But analytical platforms can alleviate this shortage. This is because within the platform environment, “citizen data scientists” can build new apps and solutions.

As the line between the physical and digital world blurs in business, the algorithmic supply chain affords companies the ability to leverage massive data from increasing connections among people, businesses and things. This allows them to respond quickly and profitably to changes in market demandIn an algorithmic supply chain, decision-making relies on the company’s intellectual property (IP) that captures data and encapsulates it into reusable, unique and optimized information assets. Embedding this IP in supply chain processes, the company can solve large-scale, dynamic problems and create competitive advantage.

UPS provides a powerful example of using analytical platforms to build On the Road Integrated Optimization and Navigation (ORION) to support its core business processes. ORION generates daily routing manifests to 55,000 UPS drivers. The platform incorporates optimization, heuristics, predictive analytics and custom mapping. It generates $300-$400 million in annual benefits, based on reducing fuel consumption by 10 million gallons, carbon emissions by 100,000 metric tons and driven miles by 100 million, annually.

No comments yet

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.

%d bloggers like this: