Supply chain and logistics operations can be a company's biggest source of financial risk or competitive advantage. The key is reconciling external supplier data like tariff and shipping information with internal data to deliver insights across teams and geographies.

As a modern data leader, you know that real-time access to data-driven insights is key to driving higher levels of business growth and innovation, and better customer experiences. You also know that when frontline employees have easier access to data they’re able to make better decisions that ultimately boost your bottom line. But what happens when employees don’t trust the data in front of them?

In 2020, the pandemic tested supply chains in a manner few have seen in our lifetimes, with businesses like Apple struggling to predict demand and keep factory lines moving. The weaknesses exposed by this crisis are not brand new, but they should be a wake-up call that current strategies are not sustainable. The limitations of modern supply chains were becoming apparent last year when companies struggled to react to new tariffs and restrictions caused by Brexit and the U.S.-China trade war.

Ask any analyst how they spend the majority of their work day and they’ll tell you: Performing remedial tasks that provide no analytics value. 92% of data workers report that their time is being siphoned away performing operational tasks outside of their roles. Data teams waste an inordinate amount of time maintaining the delicate data-to-dashboards pipelines they’ve created, leaving only 50% of their time to actually analyze data.