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IBM and delivering differentiated client value


IBM clearly realizes that people, process and technology all must go together to deliver value. This means that clients need both software and services and was the subject of this next session.

Business Analytics and Optimization is a segment that crosses hardware, software and services at IBM. IBM is committed to growing this business from over $10B in 2010 to over $16Bn in 2015 and is reporting on this as part of its financial reporting. Their intent is to develop a business analytics and optimization account plan for every customer, showing how that customer can expand their existing analytics investment to build new capabilities. IBM feels this message is working well, with strong adoption of the various business analytics products across its customer base.

The Business Analytics category at IBM is a product of a historical IBM focus and various acquisitions – Cognos, SPSS, OpenPages, Clarity Systems – all brought together to deliver analytics capabilities around business intelligence, financial performance management, predictive analytics, Governance Risk and Compliance (GRC) and analytic applications. This stack of capabilities might be initially deployed in finance, line of business, risk or IT. Finance tends to start with financial performance management, LOBs focus on customer analytics, IT focuses on the BI platform and risk folks focus on GRC. An industry and geographic focus can be layered on to these entry points, especially where there is growing adoption. IBM is focusing also on packaging business analytics into industry solution areas – in retail, for instance, focused on shopping experience and merchandising or in banking where the focus is on risk and customer service. Increasingly these solution packs use Cognos, SPSS, ILOG and more – the new smarter city control center solution for instance uses them all.

IBM’s study with MIT on analytics led it to focus on a five point approach to operationalize analytics:

  1. Focus on biggest and highest value opportunities
  2. Start with questions (decisions) not data – Begin with the decision in mind
  3. Embed insights to drive actions and deliver value – operationalize analytics
  4. Keep existing capabilities and add new ones
  5. Plan for the future with an information agenda

To help companies get started, IBM offers Business Value Accelerators like “Jumpstart” or “Predictive Analytics Jumpstart” as well as others based on Watson, performance management, Cognos health check, and Fraud and Abuse research. For instance, the predictive analytics jumpstart is designed to address the question “how do I start with predictive analytics”. It focuses on a specific pain point (a decision) and then quickly delivers a workable POC/Pilot based on improving the quality of that decision using predictive models. This provides a quick win as well as trained users and a recommended process and framework for moving forward. I like this style of consulting project – which is why I use a similar approach– and it makes good sense for IBM to offer these to help companies adopt their business analytics products.

Besides these accelerators, IBM Global Services delivers asset-based solutions in various areas such as Next Best Action, Dynamic Inventory Optimization, Real-Time Analytics Matching in call centers, Tax Audit and Compliance and a Crime Information Warehouse.