IBM is taking aim at the Big Data market with ‘ground up’ solutions but rather than technology alone, is likely to see most success from its professional services, says Ovum analyst Fredrik Tunvall.
At its recent Smarter Analytics Leadership Summit in New York, IBM focussed heavily on Big Data and highlighted the need for a ‘ground up’ approach. Considering the abundance of data-governance, processing and analytics solutions in its arsenal this is not surprising, says Tunvall.
“However, the challenge for IBM is twofold. It has to map its deep solution portfolio (both proprietary and acquired) to several Big Data needs such as storage, processing, and exploration, and also has to integrate and package these solutions in a consumable way for customers,” he adds.
The analyst explains that IBM is looking to supercomputer Watson for solutions for the Big Data market; bringing together deep content analytics, evidence-based learning, and natural language processing, it should be an interesting addition to the space.
Watson first shot to fame last year after appearing, and winning, on US game show Jeopardy. Since then, IBM has worked to advance the use of Watson’s 41 underlying subsystems in the healthcare and financial services sectors, in collaboration with Wellpoint, Seton Health, and Citigroup. But to win over more clients, IBM will need to focus development on viable business use-case scenarios for Watson’s core capabilities, says Tunvall.
Although admitting there is some work to be done, the company is confident that the first commercial implementations of Watson will roll out of production later this year, with plans to introduce Watson to specific key verticals as service-led engagements.
Tunvall notes the admission made by Manoj Saxena, IBM’s general manager of Watson Solutions, that Watson will be based on an outcome-based pricing model. Although no details were disclosed, Tunvall predicts that earlier research published by IBM suggests that pricing will be dynamically formulated by the types of analytic insight that Watson can deliver to specific parts of the business, and the business outcomes that these insights drive.
“Ovum believes that IBM is opting for this pricing model because the company envisages that usage of Watson will vary greatly between clients. We also believe it part of a strategy to get customers interested in buying this technology by offering Watson at price points that closely match the investments to the expected business benefits. It will be interesting to see how this model evolves in practice. This is likely to become clearer as IBM figures out how to more accurately define and quantify ‘outcome’ and as more commercial deployments of Watson are referenced,” he says.
The Ovum analyst also highlights IBM’s launch of Cognos Insight, the self-service business intelligence tool which aims to help users visualise and explore company data in an easy-to-use drag-and-drop interface.
“IBM has extensive experience and expertise in the analytics industry, something it is now leveraging with pre-packaged solutions branded as Smarter Analytics Signature Solutions,” says Tunvall.
“IBM sees a gap where organisations miss out on good data because they do not know how to best utilise their datasets with their current systems. Offering pre-packaged solutions that encompass both consulting services and software for a holistic approach to analytics therefore makes a lot of sense.
“With more than 20,000 analytics projects under its wing, 9,000 dedicated consultants, and a vast software and hardware portfolio, IBM has both the experience and the technology to provide overall value to customers. Three solutions will initially be offered through GBS consultants: Customer: next best action (consumer experience optimisation), CFO Performance Insight (financial risk estimation), and Anti-Fraud, Waste, and Abuse (financial fraud detection), and IBM is likely to target more areas throughout the year.”