IBM Helps Organizations Tackle Industry Specific Big Data Challenges
Posted: 23 October 2012 | Source: | Source: IBM - Risk Analytics
At IBM Information On Demand & Business Analytics Forum 2012, IBM (NYSE: IBM) today unveiled a new digital marketing system and big data software designed to help organizations gain actionable insights on the broadest range of data to transform the way they do business with customers, employees and partners.
The new offerings tackle the most pressing big data challenges facing organizations today -- accessing and gaining intelligence into an enormous stream of data generated from mobile, social and digital networks. The offerings, part of IBM's big data platform, can be up and running in hours, analyze petabytes of industry specific and social media data in sub-second response times, and continuously analyze geospatial, financial services and telecommunications data in motion.
According to Gartner, worldwide big data IT spending will grow from $27 billion in 2012 to $55 billion in 2016.
Enterprises across all industries are under increasing pressure to extract new insights from an explosion of available data. In communications, six billion global mobile phone subscribers are demanding unique and personalized offerings that match their individual lifestyles. In financial services, Wall Street firms generate five new research documents every minute. In addition, nearly $100 billion in total sales are missed each year because retailers don’t have the right products in stock to meet customer demand.
As part of today's news, IBM is also bolstering its cloud analytics offerings across industries. The first of its kind portfolio of cloud-hosted applications deliver predictive analytics directly to a company's line of business employees. Financial services, retail, and education industry clients can use the new software to develop personalized insurance renewals, conduct retail purchase analysis, and tailor new programs for student retention through the IBM SmartCloud.
A recent global survey by the University of Oxford and IBM of 1,144 business and IT professionals from 95 countries and 26 industries shows 63 percent of respondents are gaining a competitive advantage by using big data and analytics for their organizations. This is a 70 percent increase from the 37 percent who cited a competitive advantage in a 2010 IBM study.
Today's news brings together IBM's unique R&D innovations with acquired technologies from Vivisimo and Unica to provide clients with federated data and Web analytics capabilities combined in a big data analytics platform. The new offerings include:
Big Data for Chief Marketing Officers
The emergence of big data technologies is driving the transformation of marketing for every channel. Chief Marketing Officers (CMOs) are now responsible for analyzing consumer demands from social media, mobile devices, and traditional channels and align these demands with product development and sales.
The new IBM Digital Analytics Accelerator helps CMOs tap into consumer sentiment to create targeted advertising and promotions, avoid customer churn, and perform advanced Web analytics that predict customer needs. Now, CMOs can bring advanced analytics to all their social media, web traffic, and customer communication behind their own firewall. The industry's first big data solution in the digital marketing arena is powered by Netezza and Unica technologies. With this integrated offering that includes the recently announced PureData System for Analytics, clients can run complex analytics on petabytes of data in minutes, and arm marketing professionals with instant insights. CMOs can use new insights to accelerate marketing campaigns and better meet consumer needs based on the broadest range of data.
For Trident Marketing, a direct response marketing and sales firm for leading brands such as DIRECTV, ADT and Travel Resorts of America, performing analytics on big data has helped the company gain unprecedented visibility into consumers – from predicting the precise moment in which to engage with customers to anticipating the likelihood a customer will cancel service. Working with IBM and partner Fuzzy Logix, the company has realized massive growth including a tenfold increase in revenue in just four years, a ten percent increase in sales in the first 60 days, and decreased customer churn by 50 percent.
"Today's marketing professionals can see for the first time how individual consumers respond to campaigns," said Brandon Brown, Trident Marketing Chief Information Officer. "Using IBM big data analytics to capture social media sentiment along with other relevant sales and supply chain data, we can help our clients move away from marketing to the masses and to marketing to masses of individuals in a personalized way. Without big data analytics, businesses will quickly lose out to competitors who get to know consumers better than they do."
Streaming Data for Communications Services Providers
According to a recent report from the United Nations Telecom Agency, there are now 6 billion mobile phone subscribers globally. Communications Services Providers (CSPs) are under increased pressure to analyze big data coming from their networks to improve service, detect fraud and reduce customer churn.
Developed by IBM Research, InfoSphere Streams software can analyze and share data in motion, allowing for sub-millisecond decision making in environments where millions of decisions can be made every second. The software continuously analyzes massive volumes of data at rates up to petabytes per day.
Initially tested on financial markets data, the new features include built-in accelerators to help CSPs continuously ingest and analyze data in motion from their networks. As a result, they can better understand how customers are using services and what their preferences are, making it easier to provide personalized products and billing reduce to churn and retain customers. The software also comes with built-in social media analytics to help marketers fine tune promotions in support of customer loyalty and retention initiatives.
Sprint is using IBM analytics technology to capture and interpret all network data (e.g. location data, dropped calls, service interruption, network performance, etc.) to improve the overall customer experience and operational efficiencies.
“IBM is helping Sprint manage and analyze network data 90 percent faster than before,” said Von McConnell, executive director of the Innovation and Advanced Labs at Sprint. “We can now customize new products and services in real-time and respond instantly to changing market dynamics. The insights we gain from big data analytics allows us to create and deliver new mobile applications in minutes, instead of hours, giving Sprint the ability to stay well ahead of our competitors.”
InfoSphere Streams also provides the ability to drag and drop data sources to instantly and intuitively create new analytics applications. From a simple GUI interface, developers can visually design complex process flows instead of traditional programming. Data Scientists can take advantage of new toolkits that automate analysis of geospatial, financial markets, and machine data such as network event logs, call detail records and financial trades.
Hadoop-based Software for Industry-Specific Analytics
IBM InfoSphere BigInsights analyzes traditional structured data found in databases along with unstructured data to enable faster decision making. New features include built-in accelerators that analyze data flowing from digital infrastructures to help businesses in retail, manufacturing, oil and gas, energy and utilities, healthcare, and travel and transportation monitor operational efficiency, security incident investigation, proactive maintenance and troubleshooting and outage prevention.
BigInsights software now includes built-in social media analytics accelerators help marketers develop applications for customer acquisition and retention, perform customer segmentation and campaign optimization, and streamline lead generation. Employees can also select disparate data sources and instantly create new applications without the need for Hadoop skills.
BigInsights now features a new InfoSphere Data Explorer feature that enables advanced data federation capabilities from IBM's Vivisimo acquisition. The software automatically discovers and navigates available data wherever it resides to reveal themes, visualize relationships, identify the value of data and establish context of data usage.
Building on the strength of IBM's big data platform and seamless integration with Business Analytics software, analytic reporting on Hadoop data with IBM Cognos BI and IBM Cognos Consumer Insight is a turnkey data to dashboard solution for sentiment analysis of social data. This ensures more decision-makers can benefit from big data organization-wide.
Predictive Analytics for SMBs in the Cloud
Until now, predictive analytics has been deployed primarily by larger enterprises that are able to invest up front in the necessary software, skills and infrastructure. Analytic Answers offers small and medium sized businesses predictive analytics as a service, providing them access to the latest analytics capabilities without having to bring these skills or build models in- house.
Clients enter their data and questions, related to enterprise challenges such as fraud, customer loyalty, or predictive maintenance, and receive quick answers. For example, a small insurance company can easily enter their data to determine who are their most likely customers are to renew a particular policy. The service analyzes the data and provides an answer enabling the company to quickly act by tailoring a new policy.
The software used by the Analytics Answers service can analyze a variety of information from social to geospatial to machine data. To remove barriers to adoption, Analytic Answers is available to clients as a service via the IBM Smart Cloud, a subscription-based cloud environment. In addition, larger enterprises will find the capability appealing when trying to quickly ramp up pilot projects on a budget that could benefit from predictive analytics. For example, increasing retail customer spend with highly targeted offers for a new product launch, increasing insurance policy renewal activity by identifying cross selling opportunities, or determining at-risk students in time to address educational challenges.
Analytics Improves Finance Department Processes
Regulatory, compliance, and performance reporting requirements are growing in complexity and urgency, requiring a combination of diverse data from the enterprise and narrative text for regulatory filings such as 8Ks, investor presentations, debt management reports in treasury, and operation reviews. Today most finance departments use a very labor intensive, manual process to create required reporting. According to the Hackett Group, 82 percent of management reports are created using spreadsheets as the primary business application. This process is time consuming, error prone, and every time a change needs to be made the process has to be repeated, opening up greater risk.
New IBM Disclosure Management software addresses this complexity by capturing and analyzing diverse finance reporting data using a familiar spreadsheet environment. The solution addresses not only regulatory requirements, but also controllership, investor relations, treasury, and financial planning and analysis disclosure requirements.
For example, the software automates many labor-intensive tasks that had been necessary in the past to create management reports and related content. The solution also automates the creation of new reporting templates at the beginning of a financial reporting cycle, the review and approval process, and the transfer of data into these reports from relevant data sources. Last-minute changes to data now require far less work because when one is made, the solution finds all the impacted data points in tables, charts, and text narrative and automatically updates the content. In one major oil and gas producer, these process improvements reduced the amount of time spent by accountants and financial professionals by 91 percent.