Unlock the value of data to drive business intelligence
By Kevin Dherman, CIO at SYSPRO Data forms the backbone of any manufacturing enterprise. With continuous supply chain disruptions, the allure of data and Business Intelligence (BI) is the ability to look deeper into production, performance, and efficiency. For today’s industries the issue isn’t whether they’re generating enough data, it’s whether they’re getting value from that data. SYSPRO research reveals that only 20 percent of manufacturing and distribution businesses have looked at investing in big data analytics tools to process and analyse data in response to ongoing disruptions, and only five percent of businesses have investigated the use of Artificial Intelligence (AI) and Machine Learning (ML) to draw any long-term benefits from data collection. As industries look to digitally transform to the factory of the future in a data-first world, investment in technologies is irrelevant without data analytics to understand the internal and external factors impacting a business. Without the right data insights businesses are unable to compete with global supply chains as they don’t have the visibility to anticipate shifts and respond to market changes. Here’s how manufacturers can obtain visibility across the entire operation and collect accurate real-time data to not only automate processes but make data-driven decisions that drive the factory of the future: Actionable insights with ERP Ultimately, ERP fuels data-driven decision making and drives business intelligence. It allows information to be centralised and organised into readable reports and dashboards. With a variety of valuable KPIs, metrics and more information at their fingertips, they can act on new opportunities, respond to issues, and make informed decisions quickly. A SYSPRO customer, Ruprecht, was able to tackle supply chain disruptions and remain competitive through leveraging data insights. The business which supplies ready-to-eat food products in the US integrated their ERP system with AI and a predictive model to maintain […]