Navigant Consulting, Inc. was an American management consultancy firm. It had offices in Asia, Europe and North America; the head office was in Chicago, Illinois. The stock was a component of the S&P 600 index. Navigant was acquired by Guidehouse in 2019.
Sensors, actuators, and controllers, which collectively serve as the backbone of cyberphysical systems for building energy management, are one of the core technical areas of investment for achieving the U.S. Department of Energy (DOE) Building Technologies Office's (BTO's) goals for energy affordability in the national building stock - both commercial and residential. In fact, an aggregated annual energy savings of 29% is estimated in the commercial sector alone through the implementation of efficiency measures using current state-of-the-art sensors and controls to retune buildings by optimizing programmable settings based on occupant schedules and comfort requirements, as well as detecting and diagnosing equipment operation and installation problems (Fernandez et al. 2017). Monitoring and control of building conditions and operations has advanced significantly, from the invention of the modern thermostat just before the start of the 20th century to the midcentury incorporation of direct digital control into devices, the introduction of open protocols and network communications at the end of the century, and finally the invention of cloud-based computing and additional advancements that have enabled remote operation and a proliferation of connected and intelligent devices in building automation. Despite this potential, however, two main challenges hinder widespread adoption of sensors and controls in building operations that can ensure savings for high-efficiency components and equipment (e.g., heat pumps, windows, and lighting devices), as well as additional savings from more sophisticated control architectures and algorithms. energy savings of 29% is estimated in the commercial sector alone through the implementation of efficiency measures using current state-of-the-art sensors and controls to retune buildings by optimizing programmable settings based on occupant schedules and comfort requirements, as well as detecting and diagnosing equipment operation and installation problems (Fernandez et al. 2017). Monitoring and control of building conditions and operations has advanced significantly, from the invention of the modern thermostat just before the start of the 20th century to the midcentury incorporation of direct digital control into devices, the introduction of open protocols and network communications at the end of the century, and finally the invention of cloud-based computing and additional advancements that have enabled remote operation and a proliferation of connected and intelligent devices in building automation. Despite this potential, however, two main challenges hinder widespread adoption of sensors and controls in building operations that can ensure savings for high-efficiency components and equipment (e.g., heat pumps, windows, and lighting devices), as well as additional savings from more sophisticated control architectures and algorithms.
The aim of this article is to provide an overview of greenhouse gas emission reduction potentials for 2030 based on the assessment of detailed sectoral studies. The overview updates a previous assessment that dates back more than ten years. We find a total emission reduction potential of 30–36 GtCO2e compared to a current-policies baseline of 61 GtCO2e. The energy production and conversion sector is responsible for about one third of this potential and the agriculture, buildings, forestry, industry, and transport sectors all contribute substantially to the total potential. The potential for 2030 is enough to bridge the gap towards emissions pathways that are compatible with a maximum global temperature rise of 1.5–2 °C compared to preindustrial levels.
As data centers proliferate, their energy intensity deserves close attention. Always-on operations and growing usage for cloud and other backend processes make servers the fundamental driver of data center energy use. Yet servers’ power draw under real-world conditions is poorly understood. This paper explores characteristics of volume servers that affect energy use, quantifying differences in power draw between higher-performing Standard Performance Evaluation Corporation (SPEC) and ENERGY STAR servers and that of a typical server. First, we establish general characteristics of the US installed base, before reporting hardware configurations from a major online retail website. We then compare idle power across three datasets (one unique to this paper) and explain their differences via the hardware characteristics to which power draw is most sensitive. We find idle server power demand to be significantly higher than benchmarks from ENERGY STAR and the industry-released SPEC database, and SPEC server configurations—and likely their power scaling—to be atypical of volume servers. Next, we examine power draw trends among high-performing servers across their load range to consider whether these trends are representative of volume servers, before inputting average idle power load values into a recent national server energy use model. Lastly, results from two surveys of IT professionals illustrate the incidence of more efficient equipment and operational practices in server rooms/closets. Future work should include server power field measurements in data centers of different sizes, accounting for variations in configurations and setting changes post-purchase, as well as investigating the linkage between time and server energy efficiency.
The rise of new product classes such as biologics and complex molecules over the past two decades have brought to light some of the unique market dynamics that such products face. While we have seen and experienced the inception, growth and expansion phase of such products, the ongoing incumbent decline due to loss of exclusivity (LoE) is yet to be fully experienced. This raises the question of how one may go about modelling such a scenario given that forecasting the expected erosion curves accurately can ensure full brand value is retained for pharmaceutical companies. This research looks to analyze the ‘patent cliff’ across varying product classes and, in doing so, understand the drivers behind the different market dynamics post-LoE for traditional molecules, complex molecules and biologics. An extensive list of molecules across various therapeutic areas succumbing to loss of patent exclusivity between 2014 and 2019 were categorized according to product class, and sales data were analyzed to reveal trends across different product classes. The analysis of sales behavior of these compounds revealed distinct tendencies in terms of sales erosion across the various product classes. The largest determinant for the behaviour of a prescription drug post-LoE is the degree of generic competition, which in turn is primarily influenced by the barriers to entry. This research details some of the key challenges relating to regulatory, legal and manufacturing aspects that distinguish biologics and complex molecules from traditional small molecules and ultimately lead to different market dynamics post-LoE. Unlike for traditional small-molecule generics where originator manufacturers have limited options to fend off generics, the greater degree of ‘brand–brand’ competitive dynamics seen in the biologics and complex generics space allows manufacturers of originators to protect market share. This analysis represents a meaningful addition to understanding LoE across various class types and thus highlights the importance of strategic decision making that pharmaceutical companies need to take at LoE.
For potentially innovative devices and diagnostics, Breakthrough Device Designation (BDD) has been touted as a key facilitator for accelerating market access – broadly defined as U.S. Food and Drug Administration (FDA) approval and favorable coverage policy determinations by U.S. health plans. We assessed the association between BDD status and positive coverage by health plan payer stakeholders. Study authors identified interventions with BDD status and U.S. regulatory approval as of December 2019 and confirmed accuracy through correspondence with FDA. Available clinical evidence for included interventions, including data submitted for FDA approval, was reviewed along with target patient distribution, coverage status, and commentary from Medicare and the top 20 commercial insurers (by number of covered lives). Eight FDA-approved interventions with BDD status were identified across 7 broad therapeutic indications – emphysema, diabetic retinopathy, iris defects, type 1 diabetes, and chronic heart failure therapies; and traumatic brain injury and solid tumor cancer diagnostics. Of these devices, 3 were widely non-covered, 4 had limited coverage, and 1 had insufficient data for analysis among commercial insurers; in contrast, Medicare and its regional contractors explicitly covered 1 of these devices, with no formal policy for the remaining devices. Non-coverage rationale stated by health plan policies was primarily insufficiently compelling evidence of clinical efficacy. A prospective analysis of these products, assuming retroactive coverage aligned with H.R. 5333 (116th Congress; 2019-2020) or similar legislation, determined that during a 3-year effective period, market access would increase by 55% or more, driven primarily by the distribution of Medicare beneficiaries across target patient populations. Breakthrough Device Designation, while potentially valuable to expedite U.S. regulatory clearance, does not directly correlate with coverage by payer stakeholders. While pending legislative efforts may offer guaranteed, temporary Medicare coverage, innovators must pair these initiatives with additional, payer-resonant clinical evidence to secure widespread market access.
