In a May 31, 2009 article in the business section of the New York Times about techniques to evaluate the effectiveness of different types of advertisements, a marketing analyst said, “It’s putting to an industry that never had numbers before… Before, nobody could really tell you that.” The analyst was referring to a quantitative method that measured in near real time the relative impact of consumer responses to 27 different variations of a single web advertisement with different tagline words, offers, discounts and even shapes. The analysis also looked at where and when the ads were placed and which type of consumer responded. The advertisers were surprised by the conclusions of what worked best. Adjustments to the ads were immediately revised.
Why is applying business analytics to understand cause-and-effect relationships in business so new? Come on. It is 2009. Analytical methods have existed for decades. The scientific community, such as pharmaceutical drug developers, has always relied on quantitative analysis.
One explanation for the delay is that top-level executives are not adequately familiar with the power that business analytics, such as those offered by my …
In a May 31, 2009 article in the business section of the New York Times about techniques to evaluate the effectiveness of different types of advertisements, a marketing analyst said, “It’s putting to an industry that never had numbers before… Before, nobody could really tell you that.” The analyst was referring to a quantitative method that measured in near real time the relative impact of consumer responses to 27 different variations of a single web advertisement with different tagline words, offers, discounts and even shapes. The analysis also looked at where and when the ads were placed and which type of consumer responded. The advertisers were surprised by the conclusions of what worked best. Adjustments to the ads were immediately revised.
Why is applying business analytics to understand cause-and-effect relationships in business so new? Come on. It is 2009. Analytical methods have existed for decades. The scientific community, such as pharmaceutical drug developers, has always relied on quantitative analysis.
One explanation for the delay is that top-level executives are not adequately familiar with the power that business analytics, such as those offered by my employer SAS, can have in improving effectiveness and yield. Is the executive’s learning a slow and gradual process, or is there a moment of punctuated change where executives finally “get it” – an eye-opening revelation?
I think it is the latter. My suggestion to middle managers who have become passionate advocates of applying business analytics is to start educating your leadership team. Help them lead. Leadership is there primary role and responsibility. Executives lead by both communicating their vision to employees and inspiring employees. My advice to middle managers to influence your executives is to be frank and open. Do not fear that executives will reject your ideas. Create pilots and test experiments that demonstrate the power of business analytics.
A call to action to apply business analytics is needed now more than ever. The global economic downturn is creating pain but also opportunities. Take advantage of this opportunity. Executives are seeking answers, and business analytics can provide them.