A New Style of Analytics: Making Sense of Data Overload
If you’re in the business of making decisions…or if someone in your business supports you through decision making…then you’ll probably want to take note of an announcement IBM just made to help bolster decision making capability using analytics technology.
Yesterday, IBM announced new predictive analytics software that automatically correlates and analyzes big data to help clients embed hyper-intelligence into every business decision.
In addition to generating insights on internal data in a matter of seconds, the software measures the impact of social networking channels and factors this information into organizational decision making.
The software represents a new class of “decision management” capabilities that revolutionizes the way organizations gain, share and take action based on information gathered as part of business processes such as marketing, claims processing and fraud detection.
In these, and other data-rich areas – where anywhere from a thousand to five billion decisions are made daily – the software will put forward the next best action to front-line employees ensuring optimal interactions and outcomes.
Driving Repeatable Results With Fewer Resources
Companies across all industries are increasingly under pressure to drive immediate and repeatable results with fewer resources, react more swiftly to rising customer demands, and gain faster insights on business data.
These pressures are challenging organizations to strengthen their approach to decision making, and forcing organizations to act not only corporate policy and gut instinct.
For example, according to a Columbia Business School Center Global Brand Leadership report, 90 percent of senior corporate marketers believe that successful brands use customer data to drive marketing decisions. Yet 50 percent say that a lack of sharing customer data within their own organization is a barrier to effectively measuring their marketing efforts.
Compounding these challenges is the variety, velocity and volume of big data which is growing at record rates. According to IDC, the decision management software market is expected to exceed $10 billion by 2014.
“In today’s marketplace, when a customer says they’re not happy, companies must decide how to react — not later that day, or in an hour, but instantly,” said Deepak Advani, vice president business analytics products and solutions, IBM.
“With these new technologies, winning organizations can embed analytics into under-served areas of their business, empowering all employees to make information based decisions.”
IBM Analytical Decision Management Software
The new Analytical Decision Management software, part of a series of IBM Smarter Analytics initiatives, helps clients apply automated, real-time analytics into any operational data no matter where it resides, and instantly analyze it to uncover trends and expose hidden paths to growth.
As a result, insights can now be automated, socialized and used for predictive decision making.
In a single platform, IBM has combined the power of business rules, predictive analytics and optimization techniques through intuitive interfaces that allow users to focus on specific business problems. The resulting decision can be consumed by existing pre-packaged or custom-built applications, including many applications on the mainframe.
The platform also takes advantage of IBM InfoSphere Streams technology where big data can be analyzed and shared in motion, providing real-time decision making in environments where thousands of decisions can be made every second.
Entity Analytics: Making Sense of Data Overload
IBM is also extending the powerful analytical functionality with the inclusion of its newest entity analytics capabilities. For the first time, businesses can take advantage of entity analytics as part of the decision management platform.
This feature, especially well suited for big data environments, is a unique analytics engine that enables identification and matching for all entities – people, places, or things – making systems smarter as more information becomes available.
Unlike traditional methods, the IBM entity analytics capabilities are context based and accumulate knowledge, resulting in a more accurate picture, better models, and better outcomes. This ability to understand how the data is related delivers higher quality models and helps to ultimately produce smarter decisions.
Understanding Social Relationships and Influencers
A new social network analytics feature enables companies to take sentiment analysis a step further by analyzing who the influencers are around any given topic, who exactly is listening, and why people should care.
This feature enables decision makers to factor in how customers behave, what they say, and how big their sphere of influence is in a social network.
For example, which other customers does this person know? Does this person influence others in their social network? The ability to incorporate social network analytics into the predictive models used in analytical decision management helps organizations identify social leaders who can influence behavior.
C Spire: Predicting Customer Behavior
IBM client C Spire, a leading telecommunications service provider, is using IBM analytics to get closer to their customers by better predicting customer behavior and intervening before a problem ever arises, making their service and experience more personalized.
“The benefits we are able to see from using this advanced IBM analytics technology will give us the ability to put the right message in front of the right customer at the best time and in the best channel,” said Justin Croft, manager marketing campaigns and promotions, C Spire.
“We will now be able to deliver true personalization, giving the customer exactly what they need, without having to ask for it. Not only does this improve the customer experience, it also positively impacts sales and customer retention.”
This recent announcement builds on the recent release of IBM’s operational decision management software, and represents the first time that both analytical and operational decision management are provided to clients jointly on one platform.
IBM: Laser Focused on Business Analytics
The news is part of IBM’s larger focus on business analytics and optimization, which spans hardware, software, services, and research. IBM projects $16 billion in business analytics revenue by 2015.
To meet that target, the company has established the world’s deepest portfolio of analytics solutions, growing its business and industry expertise to approximately 9,000 business analytics and optimization consultants and 400 researchers, and created global analytics solution centers in Berlin, Beijing, Dallas, London, New York, Tokyo, Washington and Zurich.
IBM has acquired more than 30 companies to build targeted analytics and information expertise and continues to expand its ecosystem, which today consists of more than 27,000 IBM business partners. IBM has also secured hundreds of patents a year in analytics.
These investments have enabled IBM to develop breakthrough technologies like IBM Watson, a new class of industry specific analytical capability that uses deep content analysis, evidence-based reasoning, and natural language processing to identify relationships buried in large volumes of data that can be used to improve decision making.
Go here to learn more about IBM’s Analytical Decision Management technology. You can also following the ongoing discussion around IBM and entity analytics on Twitter via the following hashtags: #smarteranalytics #ibmbigdata and #decisionmgmt.