The fourth industrial revolution, driven by big data and machine learning, is upon us. With the power of the industrial internet, organizations are able to leverage new technology to drastically improve their productivity and asset reliability. The challenge for this new era of digital industry is understanding how to make the transformation to digital and learning to trust data for critical business insights.

Despite being in the midst of a data-driven industrial revolution, companies are not necessarily seeing the double-digit productivity that has characterized past revolutions. Rather, productivity has declined since 2010 from four percent to one percent. Companies have been struggling to capture the same amount of market share they once held.

In the oil and gas industry, revenue in the United States has decreased from 145.8 billion dollars in 2010 to 129.8 billion dollars in 2015. Similarly, in the manufacturing industry, Michael Mandel, chief economic strategist for the Progressive Policy Institute, recently explained how multifactor productivity, a measure of how efficiently a factory uses all its inputs including labor, buildings and software, has declined over the last fifteen years in nine out of 18 domestic manufacturing industries.

Companies are facing functional and structural inefficiencies as a result of outdated methods for measuring productivity. Over the last ten years industrial organizations have expanded rapidly, and with all the paper and computer records created during that expansion, companies have not been able to properly organize and analyze this data. With organizations today generating megabytes of data every minute, companies need to better leverage internal data to develop smarter business models driven by big data analytics. So how can organizations clean up existing data and embrace new data technology to transform operations?

In order to regain success, companies need to turn to data to become more efficient and rely on the industrial internet to help reduce inefficiencies across plants and global companies. With a proper asset performance management (APM) system that collects, analyzes and automates data processes, organizations can reimagine their asset strategy and drive significant performance improvements - ultimately leading to an increase in productivity and revenue.

As an example, one multinational chemical corporation was operating on various separate data management systems and a host of smaller independent solutions. The majority of these systems were custom built to enable the company’s work processes, which required a huge amount of ownership and created a siloed system with limited communication across reliability and maintenance teams. Fast forward 10 years and the company has since moved the entire corporation to one global system for maintenance and reliability. The system is highly integrated, with visibility from a corporate level down to an equipment level.

To create a unified APM system and build trust across the organization, companies must:

Develop a Game Plan: A clear game plan on how to restructure data intake and roll out new programs and tools is the first step to realize value. With a mature reliability program, all assets cannot be treated equally when it comes to inspection and maintenance strategies. Strict time-base inspection can lead to over-inspecting, increasing maintenance costs and even increasing risk levels. While all risk cannot be eliminated, most equipment risk can be avoided. APM helps identify the highest risk assets and then determine key damage mechanisms to set appropriate inspection frequencies based on risk levels.

Train Employees: Training is a critical component of APM that enables users to embrace new data-driven tools and trust the insights that these tools provide.

Embrace Teamwork: Organizations must foster a culture of reliability and teamwork to ensure everyone is working toward the same goals. If end-users within the company aren’t taking the time to capture complete and accurate data, the APM program will fail to deliver value.

Continue Driving Operational Excellence: Most organizations experience mergers, acquisitions and divestitures that change the dynamic of the business and bring new assets and practices into the fold. It’s important to never lose sight of the end goal where end-users, such as data analysts or maintenance technicians, can perform their jobs and help the company achieve operational excellence.

With a mature APM program in place, companies can expect to manage market volatility and exploit new opportunities in the industry. Financial savings realized from strategically managing assets and scheduling optimal levels of inspection and maintenance across industrial assets will help organizations embrace the full potential of the industrial internet.

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