If you have “AI,” “data,” or “analytics” in your job title, then your role in the enterprise transformation story is just starting to get interesting.
Did you know that number one driver for ERP modernization is to gain improved reporting and visibility? That’s right. A FinancesOnline Reviews for Business market survey found that 67% of tech leaders were looking for that benefit — above operational efficiency, improved business processes, and increased competitiveness.
At the highest level, the data folks interpret and analyze data from multiple sources to create reports, but also to conceive of imaginative solutions to problems.
Data stewards are responsible for carrying out data usage and security policies and acting as a liaison between the IT department and the business side of an organization. Data managers develop data-oriented systems, procedures, and policies to meet an organization’s or research team’s needs. And data scientists turn raw data into valuable insights that an organization needs to grow and compete.
So, what are you looking to achieve as part of an ERP transformation project? With real-time, data-derived intelligence; reliable data connectivity throughout your organization; and AI-driven automation, you have the power to diagnose inefficiencies, predict outcomes, prescribe corrective actions, articulate operational insights, reduce churn, and improve ROI.
But to do that, you’ve got some barriers to break through.
First, data collection. It’s critical for you to ensure real-time and comprehensive data collection and normalization. And whatever data you collect has to be reliable and easy for analysts and data scientists to access and use.
Second, access to best-of-breed analytics. You must have the freedom and flexibility to integrate with and make use of current and top AI and analytics technology, regardless of vendor. And, you need access to the right data for different types of predictive and prescriptive analytics to gain insights and offer intelligent corrective action.
Third, real-time operations. While you’re heading to the cloud, you can’t leave behind on-premises systems and data. Especially in complex environments with a high number of data sources to draw from. You need to be able to provide integrated, real-time access to non-cloud applications and data too.
And fourth, speed. In addition to all the data challenges we’ve covered already, you’re also being asked to do everything quickly — your data integration must be fast, your application integration seamless, and your business operations uninterrupted.
Not too much to ask, is it?
Successful AI analytics-based competitive advantage can be achieved quickly by making use of connectivity and automation to ensure successful discovery, capture, cataloging, and normalization of data while ensuring intelligent integration of key processes that consume this data.
To find out more about how an ERP upgrade can help you speed time to AI-informed decisions, read our ERP Modernization executive brief.