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How can IoT sensors help businesses achieve sustainability goals

Michael S. Davies, CFA, CMVP 0 Comment

https://marketscale.com/industries/industrial-iot/putting-iot-to-work-for-u-s-sustainability-goals/

MarketScale Podcast with Daniel Litwin

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Why Data Analytics Process Blueprints Mitigate Productivity J-Curve and Create Value

Michael S. Davies, CFA, CMVP 0 Comment

Analytics platforms transform technology adoption

Engendering a data analytics framework culture to optimize process innovation will lead to improving productivity. The adoption of new technologies is often challenging with lagging productivity gains. Investments into business processes contribute to faster adoption of new technologies and higher market valuations. For example, workflow processes provide a framework to better leverage new technologies by shortening the time to productivity gains. In addition, investments into business processes, intangible assets, contribute to higher equity valuations and are often reflected in growing levels of goodwill generated with technology company acquisitions.

As a core process we suggest a data analytics framework using feedback loops to optimize outcomes and deliver a better approach to leveraging technology adoption. This approach ensures that technology adoption strategies and implementations are based on data and driven by process optimization. In addition, employing an analytics roadmap to manage disruptive technology adoption with defined feedback loops set to optimize successful outcomes further improves value.

Technology and the Productivity J-Curve Paradox

As mega trends unfold; such as cloud architecture, 5G cellular, big data, IoT sensors along with machine learning, a successful structural framework for embracing these new technologies needs to embrace and address the disruption while engaging with processes that optimize desired outcomes. 

In 1987, Robert Solow, a Nobel Laureate and MIT professor, quibbled about the preponderance of computers and lack of productivity. So this is not a new issue. The economics of business process and the Productivity J-Curve concept was framed by Erik Brynjolfsson, Daniel Rock, and Chad Syverson – who examined the often slow and bumpy productivity gains arising from the adoption of new technologies. Their collective studies from the National Bureau of Economic Analysis offer a compelling rationale for developing business processes that enhance the adoption of innovative technologies. In essence, because training, experience curves, changes to business operations and services lag productivity gains. Their findings suggest “the more transformative the new technology, the more likely its productivity effects will initially be underestimated.” A recent article in The Economist, Reasons to be Cheerful, highlighted how education and training that speed the adoption of new innovation could raise productivity. 

Figure 1 Productivity J-Curve

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