Turning predictions into profits

The next age of data management will help monetize the data points by making decisions smarter 


We have evolved from capturing data to analyzing data to an era where data management is both the greatest challenge in manufacturing as well as its greatest opportunity. Plant Engineering discussed both of those PLE1404_IMG_NEWS_SAP_data management_securityideas with Pradeep Amladi, Vice President, Global Marketing Head, High Tech & Manufacturing Industries and Supply Chain at SAP:

PLANT ENGINEERING: How do you help manufacturers understand what pieces of data are actionable? How does SAP work with the sensor and controls community to turn data into information, and then action?

Amladi: You’re right; data by itself is of little use unless it’s actionable. In that context, we enable companies to:

  • Connect to thousands of types of equipment and control systems by integrating with vendors who manage device level integration
  • Structure, by reducing complexity and making easy to interact with equipment, sensors and networks with human recognizable descriptions. 
  • Bring context to bits and bytes and understand how it impacts profitability, customers, and environment. For example, real-time production environment with safety, inventory management, energy management, performance monitoring, operational risk management, etc
  • Take action with real-time, embedded, analytics, personalized dashboards, and mobile applications. The majority of our customers use some business logic, portals, enterprise integration, etc. in addition to background connectivity so that action can be taken in the context of a process

Some companies are now starting to monetize these actions externally as additional services by connecting to the equipment that they manufacturer such as heavy equipment in mining and oilfield drilling, pumps in production environments, embedded components in transportation – aircrafts, rail..

SAP works with several standards bodies and communities. For example, we are part of the OPC Foundation and contribute to the community and support these open standards for equipment integration and control. We also belong to the Open Data organization for rendering and display of this data. These are some of the larger and widely adopted communities around standards where we have visible commitments. There are others that we work with as well.

PE: One of the big issues with data mobility is data security. Talk a little about that challenge for SAP and how manufacturers can help better secure data.

Amladi: Yes, data security is an issue. This is not unique to manufacturing. One needs to consider security at the device level, as well as at the content and app level. Additionally, where mobile commerce is done, one needs to ensure secure payments as well. Finally there needs to be service to measure, track and manage telecom expenses correctly, and at several levels:

  • Device level: encrypt entire device, enforce password policies, enable BYOD (bring your own device), remote local/wipe, etc.
  • App level: Enterprise App Store, app wrapping to create secure containers with additional policy control, manage/update app distribution..|
  • Content level: secure sync, controlled distribution (private and public sharing), offline or online access, frontend to other file sharing services..

PE: We're gone from data measurement to data management. Is there another frontier out there? What else can manufacturers do with all this information they're gathering?

Amladi: Yes, the next frontier is exciting for manufacturers; it’s about turning predictions into profits.

For businesses, the opportunities to generate recurring revenues after a product sale are of critical importance. While it is likely that many more value-added services will emerge as smart machine implementation continues, a few strategies for turning predictive analytics into profitable services are health monitoring services, quick-turn issue resolution and consulting. 

Products that transmit data at regular intervals are not valuable in and of themselves.

It takes processing capabilities and product knowledge to appropriately analyze the information for smart decision making. Manufacturers are uniquely suited to monitor data from installed equipment and take proactive maintenance action on behalf of the customer. This service could be offered as a monthly subscription or possibly charged based on results, such as the hours of consecutive flight time achieved through proactive monitoring. 

Another benefit companies could offer customers based on smart machine technology is faster response time and issue resolution. When a part or system fails unexpectedly, companies with access to real-time product analytics can quickly determine the source of the problem, respond immediately and solve the issue in a single visit. This premium service reduces costs and other challenges associated with downtime. 

Finally, a third revenue opportunity enabled by access to insightful product data is consultation services. Offered either on a project basis or as a retainer, manufacturers could make recommendations for process or product utilization improvements. Customers could either implement the recommendations themselves or outsource the actions to the manufacturing partner.  

The idea of telling the future by deciphering a cloudy image in a glass ball is gone. Instead, by constantly collecting and analyzing millions of product data points, companies will be able to understand and anticipate product performance in ways never before possible. The projected benefits are not only transformative for the end product, such as a talking car, but will be incredibly important to sustaining profitable innovation within the business community as well.


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