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How the Industrial Internet is changing the competitive landscape of industries

Learn why there is a new sense of urgency to implement Industrial Internet solutions fueled by Big Data analytics.

October 8, 2014 -- New research from GE and Accenture reveals that executives across the industrial and healthcare sectors see the enormous potential of the Industrial Internet—the combination of Big Data analytics with the Internet of Things. The Industrial Internet enables companies to use sensors, software, machine-to-machine learning and other technologies to gather and analyze data from physical objects or other large data streams—and then use those analyses to manage operations and in some cases to offer new, valued-added services.

The research reveals that there is a growing urgency for organizations to embrace Big Data analytics to advance their Industrial Internet strategy. The vast majority of respondents believe that Big Data analytics has the power to dramatically change the competitive landscape of industries within the next year. Most are investing accordingly, with the support of their Board of Directors.

Nonetheless, challenges around security, data silos and systems integration threaten to delay Industrial Internet solutions that could offer distinctive operational, strategic and competitive advantages.

The Industrial Internet has the potential to drive trillions of dollars in new services and overall growth. To reap those rewards, industrial companies will need to use insights about their customers and their customers’ use of industrial goods to build new offerings, reduce costs and reinvest their savings.

Key Findings

The research reveals the following key findings that establish Big Data analytics’ potential:

  • Eighty-nine percent say that companies that do not adopt a Big Data analytics strategy in the next year risk losing market share and momentum.
  • Ninety-three percent of respondents feel that newer entrants are leveraging Big Data analytics as a key differentiation strategy.
  • Eighty to 90 percent of companies indicate that Big Data analytics is either their top priority or in the top three.
  • Eighty-four percent feel that Big Data analytics has the power to shift the competitive landscape for their industry in the next year. Eighty-seven percent believe it will have that power within three years.
  • Almost two-thirds of respondents (65 percent) focus on monitoring—the ability to monitor assets to identify operating issues for more proactive maintenance.
  • About one-third of healthcare organizations (31 percent) claim that they are significantly ahead of the game in the area of analytics.
  • About half of all healthcare organizations surveyed (clinical, 53 percent; operations, 50 percent) are investing from 10 percent to 20 percent of their overall technology budget on Big Data analytics.

    • Analysis

    Nearly half (49 percent) of the companies represented in the study said they plan to create new business opportunities that could generate additional revenue streams with their Big Data strategy, while 60 percent expect to increase their profitability by using the information to improve their resource management.

    Two-thirds (66 percent) of the executives surveyed believe they could lose their market position in the next one to three years if they do not adopt Big Data, which the report suggests is needed to support their Industrial Internet strategy. Additionally, with 93 percent already seeing new market entrants using big data to differentiate themselves, 88 percent of the executives stated that Big Data analytics is a top priority for their company.

    Despite the sense of urgency, there are roadblocks to realization. More than one-third of the executives (36 percent) said system barriers between departments prevent collection and correlation of data. Twenty-nine percent said consolidation of disparate data and being able to use the resulting data repository is difficult. Security also ranks high as a challenge with less than half (44 percent) reporting an end-to-end solution to defend against cyber-attacks and data leaks.

    Recommendations

    The research reveals several steps that companies can take to start advancing their Industrial Internet capabilities up the maturity curve to more value-creating activities.

  • Invest in end-to-end security. Enablers such as cloud, mobility, Big Data and analytics can expose a company to security risks. It’s important that companies assess the risks and consequences with the help of experts and understand the vulnerabilities.
  • Break down the barriers to data integration. Industrial companies need to reassess the time consumed for accessing, cleansing, manipulating and consolidating machine data before they are examined to create predictive models. Breaking down of organizational, data and system silos needs to be both a requirement and an outcome.
  • Concentrate on talent acquisition and development. About half of the executives surveyed have talent gaps in critical areas like analyzing data, interpreting results, and gathering and consolidating disparate data. Hiring talent with both industry knowledge and analytics skills can help to resolve the talent gap issue.
  • Consider new business models needed to be successful with the Industrial Internet. Businesses which convert products into product-service hybrids are capable of producing data for use in digital services. These services enable companies to achieve operational efficiency with recurring income streams from digital services.
  • Actively manage regulatory risk. Companies can leverage Big Data to actively manage their operating environment and risk profile, enhance emissions control and more effectively use resources such as water.
  • Leverage mobile technology to deliver analytic insights. Industrial workers perform their jobs in physically demanding circumstances with limited ability to interact with software and devices while they work. There is immense scope to deliver information to Industrial Internet users in a manner that is aligned to their working conditions.



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