“We can’t solve problems by using the same kind of thinking we used when we created them.” – The famous quote attributed to Albert Einstein applies as much to Business Intelligence & Analytics as it does to other things. Many organizations that turn to BI&A for help on strategic business concerns such as increasing customer churn, drop in quality levels, missed revenue opportunities face disappointment. One of the important reasons for this is that the data that can provide such insights is just not there. For example, to understand the poor sales performance in a particular region during a year, it will not just help to have data about our sales plan, activities, opportunities, conversions and sales achieved / missed, it will also require understanding of other disruptive forces such as competitors promotions, change in customer preferences, new entrants or alternatives.
Thomas Davenport, a household name in the BI&A community, in his book ‘Analytics at Work’, explains the analytical DELTA (Data, Enterprise, Leadership, Targets and Analysts), a framework that organizations could adopt to implement analytics effectively for better business decisions and results. He emphasizes that besides the necessity of having clean, integrated and enterprise-wide data in a warehouse, it is also important that the data enables to measure something new and important.
Thomas Davenport, a household name in the BI&A community, in his book ‘Analytics at Work’, explains the analytical DELTA (Data, Enterprise, Leadership, Targets and Analysts), a framework that organizations could adopt to implement analytics effectively for better business decisions and results. He emphasizes that besides the necessity of having clean, integrated and enterprise-wide data in a warehouse, it is also important that the data enables to measure something new and important.
