June 2017


Digital: Transitioning from the spreadsheet to the Cloud

The Industrial Internet of Things is expected to create a $225-B market by 2020, opening new opportunities for industrial organizations related to data and asset management.

Renick, J., GE Digital

The Industrial Internet of Things (IIoT) is expected to create a $225-B market by 2020, opening new opportunities for industrial organizations related to data and asset management.1 Technology advances have allowed companies to capture large amounts of data from sensors, historians and enterprise asset management systems to help inform operators about asset health, performance, operational capacity and failures. With the massive amounts of data being generated, the Cloud serves as a scalable central repository for data and the insights that data can provide.

Many maintenance, reliability and operating professionals continue to rely on manual spreadsheets to manage their data. Spreadsheets are an easy, inexpensive “go-to” solution offering flexibility and adaptability. However, the simplicity of spreadsheets masks inherent drawbacks. Spreadsheets lack transparency when tracking data inputs and sources, and prove problematic with regard to data volume and scalability. Large industrial organizations have hundreds of thousands of instruments generating megabytes of data each minute, and spreadsheets are not built to store such enormous amounts of data, let alone keep all of that data properly organized and prioritized without significant manual effort.

Beyond these day-to-day challenges, a spreadsheet approach impacts an organization’s broader maintenance and reliability program. Since spreadsheets are created separately, by different teams within an organization, the overall process results in data source silos. Maintenance, reliability and operating professionals may not have insight into the maintenance efforts or issues being managed by other engineers in the organization, so the same failures and subsequent fixes may be repeated.

Ultimately, spreadsheets pose significant risks associated with the extensive use of unstructured and uncontrolled solutions for the storage, transformation, transfer and reporting of data. One organization with common maintenance, reliability and operations (MRO) directories contained more than 9,000 spreadsheets that had been used over a 5-yr period. Of these 9,000-plus spreadsheets, approximately half had been created or modified in a 12-mos span. The inevitable overlap in processes resulted in inefficiencies, rework and confusion.

As more industrial companies move to create transformational strategies around the IIoT, they will be faced with choices for data management and IT infrastructure. The difference between managing data for enterprise networks and for industrial networks and control systems is profound. These critical infrastructure systems operate continuously, and pose significant risks when they fail.

The Cloud enables companies to cost-effectively store and process massive amounts of data, along with implementing a standard enterprise reporting tool with connectivity to all asset data sources. A Cloud platform for the IIoT can singularly offer leadership and operators the assurance of the scale and speed they need to succeed within a highly secured global Cloud environment. More maintenance and reliability programs are looking to move to Cloud-enabled solutions to increase efficiency and lower costs.

Beyond the Cloud platform itself, industrial decision-makers must consider how to gain value from more connected systems and greater access to operational data. Analytical approaches that use asset data to reduce maintenance and operational costs can make manufacturing more affordable, safer and more environmentally conscious in a competitive market where consumers have greater influence. A Cloud-based asset performance management (APM) system allows users to both securely store and manage existing data, and run analytics from various systems across several sites.

One Australia-based LNG company wanted to expand its LNG markets and develop more intelligent asset strategies to achieve a Cloud-based APM initiative. The company previously relied on spreadsheets with a variety of siloed maintenance and operational data that led to individual decision-making and actions, with little corporate asset management strategy and untraceable knowledge and activity. The organization has since implemented a comprehensive digital APM system so that all operators, facility personnel and leadership are provided with complete management and reliability metrics integrated with information from all vessel and facility assets.

Engineers in the operations center can communicate with reliability engineers in the field and display their desktops—including videos, production data and other pertinent asset data—to enable better decision-making, faster response and more active support. APM decreased operating expenditures and reduced unnecessary maintenance cycles.

For industrial companies, digital datasets are quickly outgrowing spreadsheets. To keep pace with operations and incoming data, and to properly leverage data to manage asset performance, organizations must transition data storage and analytics systems to the Cloud. HP


  1. Forbes, “The Cloud is not good enough, and we can fix it,” Forbes.com, February 1, 2017.

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