Define, Scope and Scale Improvements Via Operational Analytics

Companies often don’t understand where and how solutions can be applied to optimal effect, nor how to best integrate legacy technology investments.

By Mike Guilfoyle and Greg Gorbach, ARC Advisory Group

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Across industry, “disruption” is the word often used to describe a fundamental of today’s digital economies. It encompasses a broad set or market characteristics that have come about due to improvements in technology. Computing power is cheap and mobile, data is ubiquitous and easier to access than ever, and physical objects can increasingly connect and communicate.

Executives are deploying technologies such as smart, connected things; wireless networks; cloud computing; digital twins; and analytics to modernize, improve and transform their business processes, services, and cities.

There are now many paths to obtain improvements using data. However, there is no single, “right” path, nor does every operational area need to reach some transformational state of maturity. In fact, that may be overkill for parts of operations. Faced with this reality, executives are finding it difficult to understand how to define, scope and scale improvements using operational analytics. As a result, many organizations are still working through what to use, where to use it and when to stop.

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This article discusses the role and value of existing and new systems and solutions for improving industrial operations via data and analytics. To help frame the discussion, we provide a maturity model for operational analytics.

Why Companies Focus on Analytics

Analytics can underpin any endeavor in which data is produced. In today’s increasingly connected, digital world, that means they are applicable virtually anywhere. Look no further than historians, connected robots in plants, smart meters in electrical distribution infrastructure and energy management sensors in government buildings.

The benefits of analytics are evident. From creating new business models and achieving margin-boosting operational optimization to supporting consumer choices for energy consumption and reducing pollution, the effective use of analytics can drive benefits across the enterprise, including:

• Revenue generation from new methods for serving existing customers and ways to reach new ones
• Margin protection through value-added aftermarket services to offset the increasing commoditization of physical equipment sales
• Asset and process optimization through improved, proactive, and highly-automated management of infrastructure, resources, and capital
• Higher satisfaction and retention by engaging customers with highly-valued products and services where and when they need them
• Operational flexibility and responsiveness that comes from using data to improve the agility, speed, and accuracy of decision making

By embracing analytics to help drive better decisions and operating performance across all areas, organizations have an opportunity to modernize and transform their businesses to compete in 21st century digital economies. The difference now is that many organizations are looking to integrate more sources of new, complex and often real-time data for analytics.

They are also looking to combine that information with the performance data they have been gathering for decades. The data is structured and unstructured, and represents a dizzying array of information in many formats—assets, historians, logs, paper, pdfs, backbone operating systems, financials, spreadsheets, pictures and video, audio, weather, social media, etc.

Many Paths to Operational Improvement

The marketing hype surrounding new solutions, the role of legacy technology, and differences in analytics techniques make it challenging for business and operations executives in industry to understand how to move forward. Too often, the discovery process for doing so gets bogged down or derailed by complex discussions on technology and technique.

There are many different types of operational systems and solutions, both new and legacy. Each has a role in bringing value to the operations, from gathering and storing critical data to extracting and automating insight from it. To understand what each is trying to do, it is helpful to first examine what area of the operation is being impacted and what systems are commonly found within them. These include operations planning, process control, asset performance and operating performance.

It is also helpful to align those areas of impact with appropriate techniques and the associated systems and solutions. ARC has identified three overarching ways these can provide value:

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