Industrial Analytics

The Industrial Analytics Market Research delivers current market analysis plus a five year market and technology forecast. 

Accelerated Growth Forecasted for Global Industrial Analytics Market

ARC’s research on industrial analytics finds that a healthy double-digit growth is expected across multiple geographies and industries as industrial analytics play a pivotal role in helping companies tackle digital transformation strategies including predictive and prescriptive analytics, quality control, process optimization, supply chain optimization, safety and risk managements, and energy management. Focusing on industrial and infrastructure markets, this ARC Advisory Group Global Industrial Analytics report provides concise research of the market for analytics that focus, in part or whole, on operational data, processes, and use cases. The report includes information on market size, growth, and business 
strategies.

Industrial Analytics Strategic Issues

In addition to providing a five-year market forecast, the Industrial Analytics market research provides detailed quantitative current market data and addresses key strategic issues as follows.

Expand Peer Network

Analytics can serve as a lynchpin for transformation. When engaging in anything transformational, it requires learning new things and experimentation. Those requirements present additional challenges for industrial companies that are hardwired by controlled and stable operations and transactions. That instilled caution often translates to poor planning, piloting, and adoption when it comes to analytics. Therefore, where investments are made, use cases often do not scale as anticipated and are often abandoned.

To break that cycle, companies need to accumulate digital wisdom, learning what it takes to motivate the organization to build digital competencies, scale them, and sustain success. However, most organizations look either within their four walls or existing ecosystems to learn. That does not work. After all, if companies already knew what to do (or had ready access to that digital wisdom), they would be doing it.

By aggressively expanding their peer network beyond those they know well, digital transformation leaders are naturally forced to bring a more open perspective. This can help them quickly learn “why” others do things rather than simply “how” they are done. Instead of seeking to imitate known uses cases, competitors, or similar companies, leaders learn how to problem solve better when it comes to digital transformation. Armed with that wisdom, they are much more willing and are able to tackle entrenched issues around customer relationships, organizational culture, processes, data, and the like. They are also more patient in doing so, realizing that the return on investment will scale as they improve their digital competencies.

Seek Collaboration Across Multiple Divisions

Embarking on implementing any transformative technology is a complex endeavor that transcends the boundaries of individual divisions within an organization. To truly succeed in implementing industrial analytics and AI projects, organizations must collaborate across multiple divisions. This imperative arises from the intertwined nature of modern business functions, where siloed efforts can lead to inefficiencies and missed opportunities. Collaboration facilitates the alignment of goals, strategies, and resources, ensuring a cohesive approach toward digital transformation. Different divisions bring unique expertise and perspectives to the table, allowing for a comprehensive understanding of the organization’s current state and future objectives. Moreover, cross-divisional collaboration fosters a culture of innovation.