by Nancy Couture

How business-IT partnerships develop operational analytics

Jun 01, 2016
Agile DevelopmentAnalyticsData Warehousing

A look at some experiences with innovative solutions in data management, developed through collaboration between business and IT.

A great example of business and IT working together to innovate is in the development of operational analytics. As data volumes and frequency of data continue to increase, organizations have realized that it’s not enough to analyze their data – they must take action on it. 

The initial step that most companies have had in place for quite some time, and that most companies still think about when they think of BI, is to build out dashboards and reporting to enable analytics and decision making by the various business areas.  By taking the next step of developing operational analytics capabilities, some of that decision making becomes integrated into the transactional environment.  The analytics and associated results become a systematic part of the business process.  This can be done most effectively when IT and the business collaborate on the best possible solution from both a business and a technical perspective.

I was involved in the development and implementation of an operational analytics solution not too long ago.  The idea started when we developed an approach to load business generated results into our data environment.  Our data analysts in the business were generating information that could become very useful when integrated with other data.  This included the results of analytic models.  There were many benefits to doing this, since the data was then available to integrate with other data sets for even more robust analytics. 

This solution alone was very exciting to the business, enabling availability to business enriched data.   What was even more exciting was the way we continued to innovate by building a process to feed specific analytic model results into our transaction processing system.  These were predictive models that enabled our customer contact specialists to let the system determine the next best customers to contact.  The models leveraged assumptions developed by the business that could be tweaked as needed based on periodic reassessment.  The results of the models were loaded into our data environment so that they could be leveraged in several areas – in the analytics data lake, integrated into our standard data warehouse, and also fed into our transaction processing systems.  The transaction processing system was modified to incorporate business rules that leveraged the results of the predictive models.

The entire solution was built in such a way that business rules could be changed as needed with very little effort or lead time.

partnership 3

The benefits of this type of approach are numerous.  This one solution alone:

  • Improved the company’s ability to take immediate action on the results of analytics
  • Leveraged predictive models, resulting in improved transactions
  • Created automated decisioning within the application
  • Became a part of IT operations, ensuring its predictability
  • Resulted in more timely decisions
  • Created more actionable results that were based on analytics rather than individual on-the-fly decisions
  • Was developed in a way that the business rules could change as needed, without the typical IT development lifecycle timeline

As a result of this particular initiative, the company was able to bring in several million dollars in revenue over the course of the first year alone.  Just think of how many opportunities like this could be developed!

This is another real use case of ways that an organization can encourage a business / IT partnership.  These partnerships will inevitably improve the total solution, since they take into account the need for structure and predictability that IT can provide as well as the flexibility and speed that the business requires today in the world of data and analytics.