IBM recently held the Smarter Analytics Leadership Summit[1] in NYC where executives and senior staff explained the increasingly influential and essential role that Smart Analytics plays in a data-centric world. The pace of annual data accumulation increased from gigabytes to terabytes to an estimated 2.7 zetabytes (2012), potentially reaching, in the words of EVP Steve Mills, to ‘yadabytes[2]’.

Such large data volumes are a hallmark of ‘Big Data’ that goes hand-in-hand with Analytics. Other Big Data characteristics include velocity. It changes quickly, streaming into the enterprise while rapidly diminishing in value as it ages. Big Data comes in varieties including text, video, audio, streams, etc. as well as structured data. Smarter Analytics are needed to handle Big Data.

Business analytics experts have been around for a long time. The difference today is that analytics are more accessible and affordable to non-expert staff. IBM contributes to that accessibility with a variety of product and services. IBM Signature Solutions provide an example.

IBM Signature solutions describe patterns for applying analytics to a specific class of problems. IBM discussed three signature solutions. These and the respective target markets (in brackets) are:

• Next Best Action – intended to increase customer value returns with every customer interaction because long-term relationships are built one interaction at a time. (Telecommunications, Banking, Insurance)
• CFO Performance Insight – intended to increase the visibility, insight and control of financial performance using predictive analysis to gain insights from data on key metrics and past performance. (Cross-Industry)
• Anti-Fraud, Waste and Abuse – intended to detect suspicious transactions before payment acceptance, minimizing overpayment loss and recommending methods of intervention. (Government, Healthcare, Insurance)

More details are available from IBM[3].

The event also highlighted the measured, documented success of firms using sophisticated analytics to obtain insight and information that pays off in better performing business operations, research and problem resolution. Customers from Sprint[4], McKesson[5] and Seton Healthcare[6] discussed the details, benefits and challenges of using Analytics to improve customer services, operations and overall performance in telecommunications, insurance and healthcare.

IBM provided an overview of their portfolio of products (Big Data Platform[7], industry-targeted Netezza Accelerators[8], Watson) resources, generic and specialized applications (IBM Cognos Insight[9], IBM Cognos TM1[10], IBM SPSS Decision Management[11], etc.), activities with specific customers (Watson[12] and WellPoint[13] – to improve patient care; Watson and Citibank[14] to improve the customer banking experience, etc.) and in market segments (Finance, Information management, Marketing Management, Healthcare, Retail, Smarter Commerce, etc.).

IBM introduced the www.analyticszone.com website to build a community of IBM Cognos Insight users. It allows individuals to explore and learn the power of analytics. Members can visualize, build ‘what-if’ scenario models and share results with others.

Final Word

Promoting the use of analytics makes eminent sense to us. For years, IT and business staff accumulated data, only to be frustrated by the lack of information and insight they were able to obtain through analysis. For too long, they made do with do-it-yourself spreadsheets and basic analytical tools working on ‘data at rest’, i.e. stored data or data changing at regular but infrequent intervals.

But, today’s world is dynamic. The ability to capture, analyze and take action using data that is at-rest as well as in-motion, (i.e. traversing a network, or only temporarily available) is critical to success. Resources and analytics exist that allow the capture and analysis of customer and transaction data on-the-fly, in the midst of experiencing a service, and permit adjustments to assure a positive customer interaction.

Making sophisticated analytics more accessible and useable is necessary. It will bring welcome relief to data-rich but analytics-challenged, statistically-unsophisticated staff.  IBM has broken the trail in a dramatic way. Let’s hope more join in.