By 2020, we will be living in a world where it is predicted that over 30 billion devices will have embedded, connected sensors (EMC Digital Universe, April 2014). These wired products will continually track, monitor and transmit data, creating a vast digital universe nearly inconceivable in size. Already, manufacturing industry executives are struggling with how to sift through immense amounts of information to find value. In fact, the process of uncovering actionable data has been likened to mining for gold during the 1800s — manual, time consuming and reliant on a bit of luck.
Extracting the right information for smart decision making has become nearly impossible without the right tools and processes, which is why deliberate use of data is now one of the biggest challenges facing organizations. Yet, companies that can transform data into useable assets will enjoy tremendous, profit-producing benefits critical for sustainable, future success.
Overcoming the Challenge of Finding Value in Company Data
The biggest challenge in using big data to improve manufacturing company performance is to reduce the complexity of the information. With potentially thousands of sensors deployed in possibly hundreds of locations, the amount of information from newly created data streams can quickly become overwhelming. Companies need the right technology and tools to manage the volume, velocity and variety of data, allowing executives to quickly analyze the information in context and maintain a competitive advantage.
To begin with, companies should have a connected network of equipment and control systems. Integrating technology allows communication to happen in real-time between employees and departments; among machines; and with vendors along the entire supply chain. The network also must include a structure that makes it easy for people to access and analyze the resulting information.
Using customizable tools such as personalized dashboards, business portals, or mobile applications, employees have the ability to put real-time data into context. Being able to look at information in terms of how it impacts profitability or the environment, for example, is an important element to making data actionable.
Another challenge of taking action from data is having the ability to look at information in new ways. Often data can actually inhibit businesses, because executives tend to standardize and aggregate data in ways that drove success in the past — but that won’t necessarily drive it in the future. A better approach is to use computing methods that allow users to combine structured and unstructured data in real time without being limited by existing formats and reports.
Using Data for Decision Making
Once the network is integrated and easy access is established, companies must face the new challenge of having too much data. Examining the data with the “right lens” or in the right business context to impact what’s happening now and in the future (not rear view analysis) can be nearly impossible without the right technology solutions. To make data actionable, companies need real-time access to integrated information. For example, a manufacturer would benefit greatly from being able to combine performance of an assembly line data with a business process such a customer delivery commitments or movements of supply parts. Analyzing integrated data can trigger timely actions that lead to greater profits or more efficient operations.
Insights gained from real-time data analytics have already spurred ideas for a variety of new products, new services and even entire new markets. Health care device manufacturing companies, for example, are able to monitor implanted devices, analyze the real-time data, and recommend appropriate preventive maintenance to protect the health of a patient. Automobile manufacturers are collecting product usage data and using them to make proactive design changes or offer preemptive maintenance.
Another way manufacturing companies are using data is in the field. Service technicians can now connect remotely to the integrated network and access the information needed to resolve issues and put products back into production faster. By analyzing real-time data on parts performance and customer usage, a company can be prepared for potential product breakdowns, and service them faster, avoiding costly downtime. This is particularly important when products are being used in remote areas such as mining and construction sites and oilfield operations.
A third way companies can leverage data is to offer insightful consulting services. Manufacturing companies are particularly well positioned to offer after-sale recommendations because they have direct access to the product or service information and have the power to make changes. By analyzing both the product data and the usage information, manufacturers can make recommendations for process or product utilization improvements. Customers can either implement the recommendations themselves or outsource the actions to the manufacturing partner thereby creating a new revenue stream. This action in particular allows manufacturing companies to turn their data into dollars.
Whether it’s used to develop new products, reduce operational expenses or provide additional services, the data available to companies today, and in the future, are very real, very valuable corporate assets. Yet to truly reap financial benefits transforming bits and bytes into actionable data manufacturers require a connected network, real-time processing capabilities, and the ability to put information into context. Manufacturers are taking the lead, finding innovative ways to capture, analyze and act on data for the benefits of their customers. In doing so, they are providing a map through the world of data that they rest of us can follow.
Pradeep Amladi is Vice President and Global Marketing Head of High Tech and Manufacturing Industries, for SAP.