The wave of productivity driven by data and analytics - McKinsey senior partners
"You had the wave of lean, you had the wave of outsourcing, and now we’re seeing the wave of productivity driven by data and analytics, enabling organizations to refine the way that people work together, the way that processes perform, and the way assets are productive. If you think about an oil well, for example, you’ve got more than 300 sensors downhole that are spewing out data at the rate of about a gigabit a second, in some cases." - Bill Wiseman, McKinsey senior partner
How advanced analytics can drive productivity
Podcast August 2016
How Data Analytics Increases Productivity?
Technology and innovation drive productivity. But transaction costs of new technology implementation are considerable. Innovation requires capital and labor investment incurring transaction costs to build infrastructure and grow the market.
Analytics and decision science could provide the means to reduce the transaction costs and increase innovations to improve productivity in the economy.
Analytics provide a process to monitor, measure, and benchmark performance. By integrating diverse datasets from remote monitoring (IoT), measuring, and benchmarking can be accomplished automatically and economically. Reporting by anomaly and exception could free resources and thereby reduce costs and improve productivity.
Application of analytics to monitoring energy through sensors resulted in 17% reduction in energy costs for the NJ DOT main office complex. In another application, propensity models were constructed from customer profile and behavior data to identify candidates with highest conversion rates for sending sales promotion communications. Such examples are now many, to illustrate applying analytics to reduce costs and improve operations.
Low cost cloud computing together with large, diverse, and growing datasets, from the web to internal sources, and available statistical visualization tools, have dramatically changed the cost of data analytics. The low cost of data analytics is allowing more companies to use analytics and improve the productivity.
Source: Onoly Analytics and Analytics 2 Insight - White Paper
Analytics at the Speed of Insight: Simple, Fast and Actionable Tools to Improve Productivity
2017Ops 4.0: Fueling the next 20 percent productivity rise with digital analytics
By Mercedes Goenaga, Philipp Radtke, Kevin Speicher, and Rafael Westinner
Article April 2017
Be agile, Be focused on results and Take up manageable data analytics projects
Digital transformation-driven productivity
Don't underestimate the incredible power of DX turned inward, toward enhancing internal organizational productivity.
Digital Transformation Can Resolve the Productivity Paradox
EITN MALAYSIA, April 27, 2017
By Hu Yoshida, Chief Technology Officer, Hitachi Data Systems
How digital transformation improves productivity in manufacturing
By Alex Walker and Arnd Simon, Senior Directors, Industry Services, Global Manufacturing Practice, Microsoft Corporation; Contributor: Dr. Lei Liu, Digital Advisor, Microsoft Deutschland GmbH on May 5, 2017
Increasing Chemical Industry Productivity through Digital Transformation
May 12, 2017 | Showcase
Learn how Capgemini's ChemPath SAP – Certified Business All-in-One (BAIO) solution, will help your organization streamline and synchronize the operations, while achieving greater visibility and control over your core business processes.
IoT use cases with 2 year pay back period in global auto company mentioned.
Microsoft Workplace Analytics helps managers understand worker productivity
EXPLORING THE POTENTIAL OF DATA DRIVEN AGRICULTURE IN INCREASING FARM PRODUCTIVITY AND PROFITABILITY
Smart data is the way to boost mining productivity2 September 2016
Improving dragline productivity and increasing reliability using big dataAugust 2016
Mining operations produce an enormous amount of data through numerous parallel, though diverse, monitoring systems. Data mining and analytics can be a major part of a successful mining improvement process.
In this case, the goal is to find a single target variable and its value that will drive operator behaviour to operate the dragline at maximum production capacity and speed while not exceeding machine fatigue.
Production Data Analytics – To identify productivity potentials
Master Thesis - 2015
Department of Product and Production Development
CHALMERS UNIVERSITY OF TECHNOLOGY, Gothenburg, Sweden - 2015
Data Analytics and Continuous Productivity
September 18, 2013
Big-data analytics as a productivity tool McKinsey Global Institute
Sectors across the economy can harness the deluge of data generated by transactions, medical and legal records, videos, and social technologies, sensors, cameras, bar codes, and transmitters embedded in the world around us. Advances in computing and analytics can transform this sea of data into insights that create operational efficiencies.
By 2020, the wider adoption of big-data analytics could increase annual GDP in retailing and manufacturing by up to $325 billion.
Additionally as much as $285 billion savings can occur in the cost of health care and government services.
MIT professor Erik Brynjolfsson discusses how companies can increase their productivity by making better use of their data.
by David Talbot February 16, 2011
MIT professor Erik Brynjolfsson
Book Chapter: Business practices that enhance productivity along with IT investments.
Updated 23 August 2017, 16 August 2017, 10 July 2017, 30 June 2017, 22 June 2017