Sipping from the Firehose: Advanced Analytics holds the key to insight for CMOs

General Manager & VP Analytic Solutions, Netezza, an IBM Company

CMOs today are inundated with massive quantities of data from external data providers and internal systems. Yet the still strive to find elusive answers to these questions:

  • What new product can we introduce that will address new highly profitable emerging markets we’d like to enter?
  • If we make this competitive maneuver, what are the most likely moves our competitors will make and how will that impact the entire market?
  • The economy is collapsing in our highest profit region, what are the best actions to take now to backfill for that profit?
  • What are the right messages to convey in our advertising that will positively impact the customer experience?
  • How can we maximize our overall marketing budget and resources while simultaneously increasing revenue growth and customer loyalty?
  • What are the right social networks to tap into to leverage and extend our reach?

The data deluge alone can’t provide CMOs with the insights needed to address these critical issues.  Advanced analytics, with the ability to create predictive and optimized insights based on the historical data, may hold the key to unlocking data’s promise.

Today’s analytic tool limitations make it difficult or impossible to get timely insights to these complex and data intensive issues. After all, an analysis that takes months to obtain often misses the window of opportunity or shrinks the window of opportunity so significantly that it doesn’t make sense to pursue.

The convergence of advanced analytics inside a data warehouse provides the CMO with the enabling technology to fully exploit their growing data assets. This new generation of in-database advanced analytic capability clears the road and gives the CMO the opportunity to benefit from insight derived from massive data volumes, in a timeframe that bolsters rather than squanders competitive edge.

Let’s take a look a closer look at scenario planning which has been used by the military for decades and is in the early stages of being applied to commercial enterprises. Scenario planning analyzes current conditions and uses new and evolving information to analyze and predict possible future outcomes or scenarios in highly uncertain circumstances. The complexity and amount of data involved with accurately modeling real-world situations varies but can includes market disruptions by competitors, introduction of new products into the marketplace, customer behaviors, shifting international operations, expanding geographic sales channels, global economic factors and much more.

Scenario planning uses simulation techniques that are computationally intensive to evaluate hundreds, thousands and more possible scenarios. Those possible outcomes can be fed into an optimizer to present an organization with a portfolio of the best possible actions to take based on the predicted scenarios.

Traditional scenario planning environments are limited and constrained by the complexity and amount of data that can be considered due to the computational processing requirements to evaluate the huge number of possible outcomes.  However, today’s powerful massively parallel processing database warehouse environment with the ability to process analytics next to the data in the database provides the right enabling technology to make the seemingly impossible possible for the CMO.

Constraints that force limiting model complexity into something simple can turn a valid analysis into a meaningless representation of the real world problem. Complexities are a reality for CMOs. Advanced analytics coupled with the analytic performance of in-database capabilities finally represent an enabling technology that allows the CMOs to analyze real-world situations with all the data available in a timeframe that keeps them far ahead of the competition.