Treating Data and AI as a Product Delivers Accelerated Return on Capital
The outsized benefits of data and AI to the Manufacturing sector have been thoroughly documented. As a recent McKinsey study reported, the Manufacturing segment is projected to deliver $700B-$1,200b value through data and AI in cost savings, productivity gains, and new revenue sources. As an example, data-led manufacturing use cases, powered by data and AI, reduce stock replenishment forecasting error by 20-50%, increasing total factory productivity by 50% or lowering scrap rates by 30%.
It shouldn’t be a surprise that the largest customers using the Databricks Manufacturing Lakehouse outperformed the overall market by over 200% over the last two years. What drove this success? These digitally-mature Lakehouse practitioners had:
- more agile supply chains and profitable operations enabled by prescriptive and advanced analytical solutions that foresaw operational issues caused by COVID-19 disrupted supply chains.
- advanced prescriptive analytics that promote uptime with prescriptive maintenance and supply chain integration.
- new sources of revenue in this uncertain time.
Data + AI Summit 2022 featured several of these industry winners at the Manufacturing Industry Forum. These experts shared their experiences of how data and AI are transforming their businesses and delivering a stronger return on invested capital (ROIC). We’d like to highlight some of their insights shared during the event.
Manufacturing Industry Forum Keynote
Muthu Sabarethinam, Vice President, Enterprise Analytics & IT at Honeywell, kicked off the session with his keynote: The Future of Digital Transformation in Manufacturing. Part of his talk focused on how to approach a digital transformation project; in his own words: “start first with data contextualization in the digital transformation process,” meaning start by leveraging IT and OT data convergence to bring all relevant data in context to the users.
Citing that only 30% of projects are productionalized and escape POC Purgatory, he explored the use of AI to create data of value and provided insight on the concept that AI has the potential to streamline data cleaning, mapping, and deduping. In his own words: