Next Practices For Intelligent Enterprise IM&C Companies

Judy Cubiss

We’ve been talking about the Fourth Industrial Revolution in the industrial machinery and components (IM&C) industry for a while now. It’s really happening. Digital is providing new ways to deliver value to customers. Products have morphed into end-to-end solution lifecycle services. Manufacturers have enthusiastically embraced and are cashing in on the Internet of Things (IoT). Use cases that tap into data intelligence – from the factory floor to the executive suite – are multiplying.

Data analysts in IM&C companies already know the benefits of analytics: growing revenue, designing products and services, reducing costs, enhancing the customer experience, and so on. But tapping data from across and outside of an enterprise IM&C company for analytics on a grand scale was easier said than done – until very recently.

Next practices

From our global experience working with the leading, most innovative IM&C companies, here are three SAP “next practices” – capabilities and outcomes to help companies utilize data and analytics on a grand scale.

Integrate diverse data sources. Data is scattered. It’s in multiple applications, files, data warehouses, data lakes, and public and private clouds. Each silo walls off the data with proprietary rules and complexity. You need visibility into that data. Without it, you have a disjointed picture of the business. With it, you can do things like blockchain-enabled smart contracts to validate outcomes and automatically execute terms. Or connected manufacturing, optimized energy use, data-driven operations and marketing, demand signal management, forecasting, and much, much more.

Next practice #1: Integrate your data by combining data sets – including Big Data, process data, product data, analytical data, etc. – as needed, into a single data universe for much greater visibility.

Make data more useful. Your data comes to you structured, semi-structured, and unstructured. It may be spatial, chart, numeric, geographic, time-series, relational, JavaScript Object Notation (JSON), etc. Integrating all of these different types of data is extremely complex. But without it, your company is at a competitive disadvantage, squandering available resources.

Next practice #2: Integrate your data sources using orchestration and governance solutions. Go from raw feed to intelligence with real-time analysis of vast data sets. How? With solutions to understand, integrate, cleanse, manage, associate, and archive data to optimize business processes and analytical insights.

Simplify your data landscape. Centralized. Easy-to-use. Automated. That’s what you want from your data analytics platform. And those features have been a challenge because of all the different databases, apps, and clouds in your IT and business environment. But now a centralized data management solution is available that manages all facets of an enterprise technology company’s data universe. Represented visually, the architecture is easy to share and understand. Stakeholders assigned to an architecture team within your company can collaborate through a user-friendly Web application in the planning, design, and governance of the architecture.

Next practice #3: Create and maintain a complete landscape architecture that is easy to share and understand. Open up this landscape to an array of company employees and managers to jointly manage your data environment as an agile, strategic tool.

A growing number of data analytics use cases for IM&C companies

Data analytics is being recognized as a vital tool for IM&C companies that need to innovate faster than the competition, create new markets and products quickly, automate processes, and attract and retain customers. The need for speed has grown – along with the diverse types and quantity of data. Becoming a truly intelligent enterprise requires a reliable, easy-to-use platform to capture, ingest, process, orchestrate, compute, and consume data at tremendous scale.

SAP customers in the IM&C industry that are intelligent enterprises are using data analytics fed by an increasing array of data sets for use cases that include:

  • Demand signal management and forecasting to have the right product, at the right volume, at the right location to meet demand
  • Forecasting raw-material pricing impact to simulate material costs and margin impacts
  • Spare and service parts inventory optimization to provide stock-level management across the supply chain, provide simulations, and optimize inventory policies
  • Predictive maintenance to ensure asset health, lower service and maintenance costs, and reduce spare parts inventories
  • Optimizing inventory to lower costs across the supply chain

These are just some of the many quickly evolving, creative ways that larger and diverse data sets are being put to work by intelligent enterprises in IM&C today. Some use cases are relevant to every type of organization in the industry. Others are more suited to different types of businesses, geographies, markets, and other characteristics.

For more on how technology companies around the world are transforming into intelligent enterprises, read the new SAP white paper “The Data-Driven Industrial Machinery and Component Company–Data Management for the Intelligent Enterprise.”

And please listen to the replay of our “Pathways to the Intelligent Enterprise” Webinar, featuring Phil Carter, chief analyst at IDC, and SAP’s Dan Kearnan and Ginger Gatling.


Judy Cubiss

About Judy Cubiss

Judy Cubiss is Global Marketing Lead for Industrial Machinery and Components and Automotive at SAP. She has worked in the software industry for over 20 years in a variety of roles, including consulting, product management, solution management, and content marketing in both Europe and the United States.