Category Navigate Uncertainty
Mega Trends Thematic Research and Analysis
As digital transformation grows, underlying technology platforms become a core differentiator for key players. Our research reveals that current market leaders need to identify and embrace important new technologies now and adapt to the continuous emergence of new innovative platforms — often through M&A activities. In our full report, we take a look at significant technology disrupters and identify key players to watch.
Two overarching themes, data and energy, inform our approach; and our core premise that drives our innovative technology analysis is that as more commerce commences over digital platforms, more energy is consumed and more data is generated. This lens enables us to identify important emerging trends as well as obstacles to progress; while sorting out the technologies and firms most likely to emerge as winners going forward.
Importantly, our ongoing research reveals that there is also a confluence of interactivity between classes of technology that results in cross dependencies, correlation, cross pollination and scale that creates nuances within each segment. It is our implementation of data collection and analysis between segments, comprehensively addressed in our full report, which adds the insight required for confident decision making. Order your copy now.
In our full report, we identify some of the sectoral trends fueling the new digital economy and the innovative technology companies creating value in our research. Let’s break it down by sector:
Energy Storage – is the key differentiator for electric vehicles (EVs) and the end-to-end mobility solutions of the future. It also plays a vital role in energy efficiency and resiliency. Energy storage is a core technology to address energy efficiency; critical to controlling carbon emissions, grid resiliency, and providing EV charging solutions. Energy storage systems have substantial benefits for energy consumers, including: industrial, commercial, public, and households. From cost reduction to business continuity and equipment protection, proper energy management delivers significant business efficiencies. There are, however, associated high switching costs for energy storage to be considered. Our focus in our full, in-depth report includes thorough analyses of Plug Power (PLUG), Ballard (BLDP), FuelCell (FCEL), Bloom Energy (BE) and QuantumScape (QS)
Cloud Architecture – another key sector we examine, provides a very cost-effective means of providing separate layers of data storage, computing and transactional services to enterprises and agencies where reliability, scalability and availability are critical to performance and the maintenance of a competitive edge. Virtualization services enable separation of hardware and software as well as method for separating data from control planes. Innovative tools including Databricks and recent IPO Snowflake provide scale and data integration to manage cloud services and data analytics. Our focus in this niche includes Alteryx (AYX), Datadog (DDOG) Palantir (PLTR) Splunk (SPLK) C3.ai (AI) and Snowflake (SNOW).
Why Data Analytics Process Blueprints Mitigate Productivity J-Curve and Create Value
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
Why Visual Data Analytics: Discovery, Innovation and Opportunities
A data analytics framework is applicable to insight discovery; provides a roadmap towards innovation; and enables capabilities that can optimize approaches to new business models and opportunities. The following paper provides examples revealing how and why to apply visual analytics for discovery, innovation and evaluating new opportunities.
Discover how waveforms and patterns are applied to science and finance, and how customer usage patterns can reveal new approaches to market micro-segmentation and persona classifications. Lastly we’ll reveal how the deployment of IoT devices across the enterprise fuels data flow in the physical world regarding the performance and conditions of business assets.
Introduction
Our theme is applying visual data analytics as a tool for discovery, innovation and evaluating market opportunities. We show how two metrics, price and volume, are able to convey insight and establish price targets for technical analysis. Why energy consumption patterns and waveforms lend themselves to understanding science and classifying human behavior. How proxy metrics can serve as measures for physical events. Why linking granular visibility into processes and the monitoring of conditions and operating performance help build an advantage in the digital economy.
Green Econometrics relies on visual analytics as a core fabric in our data analytics frameworks because visual analytics are integral to discovery, innovation and new opportunity development. Visual insights are easy to understand – allowing business objective and performance metrics to seamlessly transfer across business units. So how do we do it?