This blog originally appeared in ARC, Industrial IoT/Industrie 4.0 Viewpoints

Digital work environments provide a plethora of potential benefits for businesses operating within them. Consumers can be served faster and better, leading to high levels of customer satisfaction that generate loyalty. New revenue streams can open up, based on different ways of fulfilling customer needs. Operations become more efficient, reducing risk and cost while improving margin. However, to gain these benefits companies will need to reshape how they approach knowledge management.

Businesses undertaking digital transformation often find that some aspects of work become more difficult, even as customer service improves and the ability to compete increases. More data gets used, often for new ways of decision making. Information can be processed and delivered faster among people, systems, and devices. Expectations for speed and quality of service increase, putting more pressure on workers. The mantra of “do more with less” dominates the work environment, as competitive advantage is determined by wringing more productivity out of fewer resources. In this setting, workers are often unprepared for and overwhelmed by the deluge and complexity of information needed to execute work.

In order for companies to reap the benefits of digital work environments, they must deal with information overload by reshaping knowledge management. To do so, they must evolve the knowledge, skills, and ability (KSA) of the workforce. For example, cable and telecom industries went from analog to digital networks to provide better and additional services to markets, ensuring new revenue streams and competitive barriers. However, some of the KSAs required to complete work significantly changed, from call centers to the field.

Generally, the best field technicians were often distinguished by their ability to effectively run wire into customer premises and set up service. As networks went digital, these field technicians needed to become experts in network configuration and connection, enabling the delivery of more digital products, such as Voice over Internet Protocol (VoIP) phone service.

Driven by new technology and services, these networks became increasingly complex. It became impossible for individual technicians to know everything they needed to in order to do their jobs correctly. Forward-thinking companies adapted two ways:

They realized that electronic decision tools were critical to getting work done quickly and accurately. Accordingly, these tools were integrated into workflow, particularly in the field.

Knowledge management organizations within these companies remapped the knowledge, skills and abilities (KSA) for workers to account for digital networks. New competencies were taught, such as return path operations, which were critical to revenues from services such as video-on-demand and high-speed data.

Fast forwarding to the present, where companies need to take a cue from this example of the past. IIoT poses a similar step-change challenge for companies and their workers. To embrace the benefits of digital operations and business models, companies need to ensure knowledge management teams are informed about IIoT initiatives. Engaging these teams enables them to create KSA roadmaps for workforce development that complement the role smart, connected devices and high volumes of data will play in digitized businesses.

To embrace the benefits of digital operations and business models, companies need to ensure knowledge management teams are informed about IIoT initiatives. Engaging these teams enables them to create KSA roadmaps for workforce development that complement the role smart, connected devices and high volumes of data will play in digitized businesses.

About the author

Michael Guilfoyle

Director of Research, ARC

Over two decades, Michael has assisted organizations, including numerous Fortune 500 companies, in identifying and capitalizing on growth opportunities presented by the modernization of the energy, technology, and telecommunications industries.  ​Michael's expertise is in analysis, positioning, and strategy development for companies facing transformational market drivers.  At ARC, he applies his expertise to developments related to Industrial Internet of Things (IIoT) and advanced analytics, including machine learning.

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