Making Sense of New Data in the Supply Chain [Guest Commentary]

Right now we are seeing a tremendous increase in the amount of data available throughout the supply chain. The problem is, that there is so much data that no one really knows what to do with it. Harnessing the power of data is vital to ensuring your supply chain is meeting customer expectations.

To get started making sense of all this data, supply chain managers should adhere to the following steps: 

1. Understand where all the data is coming from 

Before you can begin making sense of new data, you must first understand where it’s coming from. Today, we not only have structured data, including orders and forecasts, but also unstructured data including POS, weather forecasts, and sentiment analysis. 

2. Be able to access data from anywhere 

It’s predicted that by 2020, we will have over 6.1 billion smartphone users globally and over 50 billion smart connected devices, all of which are opportunities to collect, analyze and share data. In light of this growing number of smart connected devices, it's important that supply chain managers can access information from anywhere, at any time, on any device to be able to make real-time supply and demand decisions. 

3. Turn big data into actionable information in business context 

It’s reported that only 42% of companies know how to extract meaningful insight from the data available to them. To help make sense of it all, data should always be put into the appropriate international business context for whomever it’s intended for. For example, a 20-page detailed data analysis report might resonate well with a production manager, but a C-Level executive would respond much better if the same data were presented in a high-level dashboard. Putting demand and supply data, both structured and unstructured, into the right business context will allow you to best monetize innovative business models.

4. Leverage the power of data scientists 

Harnessing all this data and turning it into actionable information, requires a specific skill set and expertise that have not been required in supply chains, until now. That’s why the most successful businesses have hired data scientists to fill this void and take on these new responsibilities. This person is critical for not only collecting, managing, and analyzing supply chain data but also for garnering advanced predictive analytics to help executives make more intuitive, accurate, and reliable, allowing them to deliver goods and customer service ahead of the competition. 

Big data enables us to capture and analyze massive volumes of information from all corners of the supply chain and ecosystem. If harnessed and leveraged it can deliver increased visibility and deeper insights into the business processes across your extended supply chain. You can improve your responsiveness to changes in demand and supply and minimize or even mitigate supply chain risk.

 About the Contributor:
Richard Howells is a VP for Extended Supply Chain at SAP
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All contents are written by Ben Benjabutr unless marked as [Guest Commentary]

About the Author and Editor:
Ben Benjabutr is the author and editor of Supply Chain Opz. He holds an M.Sc. in Logistics Management with 10+ years of experience. You can contact him via e-mail or Twitter.