Risk Chat: How to Traverse the Great Data Divide. The right analytics can save companies millions and help them see the road ahead (and the opportunities that exist there) more clearly -- if they have the right tools, if they maintain a relatively sane information technology (IT) environment, if a broad range of decision-makers know how to use analytical tools, if... This string of conditionals adds up to a formidable obstacle. And one of the largest obstacles preventing companies from harnessing greater advantages from their analytics capabilities is what Lavastorm Analytics CEO Drew Rockwell describes as the "great data divide. " On one side of the divide, you will find relatively few companies with quick and easy access to all the data necessary to immediately fuel all of their analytical engines.
On the other side resides the vast majority of companies who must contend with data that is "increasingly fractured and allocated into separate departmental silos within an organization," notes Rockwell. Customers use more channels for better service. Staff writer | July 04, 2012 Enterprise Innovation Consumers are using more channels for feedback, averaging six different ones for contacting service providers. Results of the NICE 2012 Consumer Channel Preference Survey show that 86% of respondents say they are communicating more often, or at the same level, with businesses over all channels. The study also found that the web continues to be the most popular and growing self-service channel. At the same time, smartphone applications and social networks have grown in popularity with more than 40% of respondents saying they have increased their use of these channels. The survey polled around 2,000 people living in major metropolitan areas in the US, the UK and Australia.
Almost half of the respondents noted that if they are unable to accomplish a task on a company website, they will then turn to the contact center to resolve their issue. Big data: The next frontier for innovation, competition, and productivity | McKinsey Global Institute | Technology & Innovation. The amount of data in our world has been exploding, and analyzing large data sets—so-called big data—will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, according to research by MGI and McKinsey's Business Technology Office. Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers. The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future. MGI studied big data in five domains—healthcare in the United States, the public sector in Europe, retail in the United States, and manufacturing and personal-location data globally.
Big data can generate value in each. 1. 2. Podcast Distilling value and driving productivity from mountains of data 3. 4. 5. 6. 7. Smart meter data shared far and wide. Click here to see previous The Privacy Question articles DETAILED information about electricity customers' power usage, which gives insights into when a house is occupied, is being shared with third parties including mail houses, debt collectors, data processing analysts and government agencies. Customers with smart meters who sign up for Origin Energy's online portal must consent to their data being shared with a string of third parties. The data is stored in Australia but shared with US company Tendril, which is described by Origin as a smart energy technology provider.
Australia's privacy watchdog said the technology could threaten people's privacy. Advertisement Smart meters were a common concern among Age readers who responded to our series on privacy. Mr Pilgrim said electricity companies had a legal responsibility to delete or ''de-identify'' personal information that was no longer needed. An Origin spokesman said the portal was fully compliant with Australian privacy legislation. The future of risk technology. By many accounts, OTC derivatives date back to 1981, when IBM and the World Bank entered into the first currency swap agreement.
It is no coincidence that the IBM PC appeared on traders’ desks in the same year, running spreadsheet software capable of pricing this new type of financial transaction. Since then, the sophistication of capital markets and the associated enabling technology has grown to the point that millions of transactions can be processed on a daily basis, and complex instruments can be structured, priced and risk-managed. The pace of this innovation, by outstripping the capacity of financial organizations to adapt to new business models, played a major role in the financial crisis of 2008. Until then, the focus of investment was on trading technology to handle ever more complex instruments in new asset classes such as credit derivatives and commodities.
Newer technologies are also being adopted to solve computational problems. Talent war for data crunchers. Brian Corrigan Banks, telcos and other corporate giants are launching a fresh war for technology talent as they compete for a new breed of professionals capable of interpreting vast volumes of customer information. Enterprise architects who build data warehouses and business analysts who can spot patterns to deliver competitive advantage are in hot demand, but the insatiable thirst for knowledge has also blurred boundaries between art and science as marketing departments hire candidates with maths PhDs to do the slicing and dicing of information.
Ian Bertram, a vice-president of research with technology analyst Gartner, said a growing number of large organisations were looking to hire data scientists. These professionals, who typically had multiple PhDs in mathematics and related fields, could act as a hub and help different areas of the business look for patterns. However, such talent was in desperately short supply and service organisations had started offering data scientists for hire. Analytics is Rocket Science!