IBM's Big Bets: Cognitive and Analytics

IBM boasts an extensive portfolio of products and services to help organizations develop analytics solutions to gain business advantage and to improve the human condition.

At IBM Information on Demand (“IOD”) in Las Vegas the first week of November, IBM SVP and Group Executive Steve Mills, and other IBM executives, unveiled 30 announcements that identified new and updated products and services to augment the IBM portfolio.

IBM also spent some time on at IOD educating attendees about the commercialization of its other big bet, cognitive computing, perhaps an even more strategic bet than analytics, operating under the now famous IBM Watson moniker. IBM, however, held the next major step about opening the Watson ecosystem development in abeyance for one full week after the end of IOD. 

IBM’s two big bets, cognitive and analytics, are situated at entirely different points of their respective lifecycles. Analytics, and related information management solutions, are commercially here and now. Cognitive computing has only recently hatched from the research side of R&D, and has nearly 100% of its commercial life still ahead of it. How do analytics and cognitive fit together into the larger IBM strategy to continuously help customers apply technology to the benefit of business and people?

Analytics

Despite the flurry of announcements one key message came through loud and clear at IOD: IBM believes that analytics is a primary game-changer for businesses, IBM believes customers should bet big on analytics, and preferably by buying and obtaining help applying IBM’s analytics and information management offerings. To IBM’s credit its analytics consultants receive no special compensation for selling IBM’s products — their primary objective concerns customer success. IBM even puts its money where its mouth is by entertaining the use of value-based pricing when applicable.

The IOD keynotes stirred attendee passion for analytics through a mix of IBM executive, customer, and partner presentations and interviews. Mr. Mills aptly drove the point home at a news briefing stating that we are entering an “era of decision-making excellence” and that we are just “… at the beginning of the revolution…” Despite IBM presenting a large quantity of analytics customer case stories, “You ain’t seen nothing yet” according to Mr. Mills. Mr. Mills cited decreasing hardware costs as contributing factors to the rise of analytics and predicted that eventually businesses would spend more on analysis and prediction than process automation.

Mr. Mills better be correct about the demand cycle for IBM has placed a giant wager on analytics. IBM employs over 9,000 business analytics consultants, and has helped customers implement over 3,000 big data deployments to date. Though IBM has experienced 5 consecutive declines in year-over-year quarterly revenue, business analytics has grown 8% year over year through the first 3 quarters of FY13. IBM has and will continue to make organic R&D investments “measured in the billions.”  Dating back to and including the 2009 purchase of SPSS, over the past 40 months IBM has made 43 acquisitions, with more than half fitting into either analytics or related information management spaces.

IBM hinted that is nowhere ready to sit on its laurels, and customers should expect on-going innovation in both the analytics and related information management space such as in databases, business process automation, integration, data governance, and content management. Some complain that IBM’s portfolio is difficult to navigate because there are so many options and sub-brands. IBM exhibited awareness of the issue, and customers may see IBM realign and simplify the portfolio during 2014.

If the realignment and considerable evangelism on display at IOD, which will be called IBM Insight in 2014, makes it simpler for customers to grasp the benefit and move towards solutions with IBM more quickly, IBM will happily continue to make such investments. Analytics in 2013, 2014, and probably for several years thereafter, will be looked to by IBM’s executives and shareholders as a lynchpin for moving IBM revenues in a more northerly direction.

Cognitive

If analytics and all that it entails carries and will carry an important revenue load for IBM in the near and medium term, cognitive computing supplies the air cover to keep customers coming back to IBM for tech innovation-based transformation. Though IBM Watson continues in its technology transfer phase, make no mistake about it: IBM Watson is already attracting and attaching developers, and is already being used to help customers, albeit on a limited basis.

The most fascinating angle about IBM’s recent Watson announcement is the notion of “cognitive applications.” IBM’s new ecosystem program for Watson aims to recruit entrepreneurial ISVs, putting IBM into the pole position with a new platform for the first time in a generation. With a few exceptions, IBM largely left the packaged enterprise application market to the likes of SAP, Oracle, Microsoft, Infor, and Salesforce.com, choosing instead to win at the edge of those solutions where services, infrastructure, customization and hand-holding were required.  That may very well change with Watson.

Perhaps whetted by the value-added nature of analytics, and some of the industry-specific applications where IBM has succeeded, the notion of cognitive as an entrée into the next generation enterprise application space portends an IT competitive overhaul. Given that the focus on SMAC – social, mobile, analytics, cloud – by the developer, VC, and tech entrepreneurial community has been racing for several years now some have begun to whisper “but what’s next?” IBM’s greatest challenge with Watson over the coming years may be how to manage the explosion of interest from developers. Being a “platform” vendor is the right problem to have.

EMA Perspective

Virtually every Global 2000 company has implemented ERP, CRM, and SCM solutions. While all of these core solutions are experiencing a refresh cycle due to SMAC, and in doing so delivering improved business effectiveness, another slice of attention has gone towards derivative applications, including:

• Analytic apps offer insight-driven business solutions that leverage existing data. Visit EMA’s Business Intelligence and Data Warehousing research for more detailed coverage.
• By wrapping APIs around data integration, data governance, and business processes, organizations may now develop a fresh set of integrative applications. Just as big data opens the door to better insight, evolution in the integration space allows for a refresh in business process optimization. On a visionary basis this has to do with harnessing IoT, or the Internet of Things, but on a practical basis the integrative approach will help enterprises harness YoT – Your own Things. Many of IBM's comprehensive offerings on this front were evident at IOD.
• Cognitive applications, which also tap largely into existing informational and process assets, promise an entirely rethought approach to business model re-engineering.

Investors worry about IBM revenue growth.  Share prices have reflected the concern recently. Industry analysts, however, enjoy the freedom to look many years ahead when assessing vendor success probabilities. Between analytics, integration, and now particularly cognitive, over the long run IBM is as positioned as well as any enterprise IT solution supplier.

By: Evan Quinn
Link: http://blogs.enterprisemanagement.com/blog/ibms-big-bets-cognitive-analytics/