Increasing Analytic Project Success

The digital transformation is remaking business models, companies and entire industries. Look at the impact that online search, news, ads, auctions, and markets have had on traditional business. Digital transformation has resulted in a more agile and responsive environment, and it is all built on data.  Lots and lots of data. Data from all kinds of different sources. Sensing the changing world about them, executives from all industries are looking to add analytics to their products, services and operations and are launching new analytic initiatives to stay competitive. Often times, the only thing slowing them down is alignment with business needs. Developing a technical capability is fine, but analytics projects need to be designed to solve a business problem. A poor connection between business needs and analytic projects is why most projects don’t go into production. To increase the odds of success, make sure your project is solving a business problem. It’s also widely understood in the data science world that more data often improves analytic outcomes.  There is a real incentive to collect and use as much data as possible to optimize your project. All this data needs to reside somewhere.  You have heard about data lakes, a collection of data from different sources to provide a broader base for analytics to improve decision making. Data lakes can be a powerful tool, but for best results they should be used thoughtfully.