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The power of business analytics


Syndicated from Smart Data Collective

I recently presented at IBM’s CIO Leadership Exchange on the power of business analytics. With 300+ of IBM’s top CIO customers this was a great event and it is clear that CIOs the world over are keen to adopt business analytics. They recognize, I believe, that they are the custodians of all this data and that business analytics offers the potential to turn the cost of storing and managing this data into a value for the company. After all, as someone once said to me:

Analytics simplify data to amplify its value

By taking all that data in all those datastores and applying business analytics, CIOs can reduce the complexity of the data and increase its value to the organization. The organizations that are making the most of business analytics have created an environment where analytics are pervasive, predictive and actionable:

  • Pervasive
    Used in every transaction, in operational decision making at the point of contact/delivery.
  • Predictive
    Applying predictive analytic techniques and creating predictive scores not just analyzing the past and reporting on it.
  • Actionable
    Making decisions and taking actions based on these analytics, not just presenting them to someone or using them to increase available knowledge.

The CIOs clearly want to reach this state but it is a big stretch for many so they wanted to know how to get there, what interim steps to take. In some research I recently completed I found that companies went through the following steps on their analytic journey:

  1. Integration
    Collect and integrate your data for a specific purpose or decision. Typically an operational decision and often not the original motivation for collecting the data.
  2. Understanding
    Analyze at the group level but for operational reporting, and new users, not for management/financial reporting
  3. Targeting
    Develop segmentation of customers, products, citizens, suppliers allows organizations to analytically focus resources based on trends and patterns
  4. Operationalization
    Focus on operational integration, on creating an operational framework that allows analytically-derived differentiation to be put into action. Adopt increasingly granular segmentation and increasingly prescriptive models. Consider business rules management as part of the new infrastructure.
  5. Prediction
    Focus on looking forward, on building models that support proactive decision-making. Examples include detecting fraud, targeting prospects, predicting retention risk. Adopt micro-segmentation and next best action.
  6. Optimization
    Balance risk and reward with formal trade-off analysis. Focus analytics on “Markets of one”

I regard the first three steps as building an information platform and the last three as delivering on the power of analytics. No matter where you are on the journey to analytics, the next step will add value and move you closer to pervasive, predictive, actionable analytics.


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