Only 27 percent of shippers and 42 percent of service providers have an in-house data science team, which can limit the effectiveness of analytics initiatives, according to the latest Supply Chain Analytics Benchmark Study from American Shipper.
Fewer than one in 10 shippers and logistics services provider have highly accurate data underlying their analytics initiatives, according to new research from American Shipper on supply chain analytics and business intelligence.
American Shipper’s second annual Supply Chain Analytics Benchmark Study: Analyze This, found that only 5 percent of shipper respondents say they have extremely accurate data, a major problem since analytics is heavily dependent on reliable and accurate data.
The report also found that only 27 percent of shippers, and 42 percent of LSPs, have an in-house data science team. This can present a limitation on the effectiveness of analytics unless those shippers and LSPs are leveraging outside help to make sense of their data and data initiatives.
Other findings in the report include:
• About a third of respondents are using a mix of descriptive, predictive, and prescriptive analytics;
• Shippers use an average of 2.2 business intelligence tools across their supply chain;
• And shippers most commonly cited ocean freight as the mode where analytics initiatives are most effective.
“You’re no longer competing against company down the street,” Richard Sherman, a senior fellow with Tata Consultancy Services, said at the North American Logistics CIO Conference in Austin Tuesday. “You’re competing against time. It takes a history of analytic behavior to improve performance. You can’t create history – it takes time. And you may find yourself facing a competitor with machine learning based on two to three years of historical data that you just can’t make up in time. Analytics may be an extinction event.”
AS Report: Less than 10% of shippers confident in analytics data accuracy
