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April 9, 2013

With Great Knowledge (May) Come Great Power

The following was originally written as an assignment for information systems, a course at the Johns Hopkins University Carey Business School.

 

[divider]SUMMARY [/divider]

“Half of my advertising budget is wasted, but I’m not sure which half.”
– Lord Leverhulme, founder of Unilever

This phrase has resonated with marketing professionals for decades; only recently has the paradigm begun to shift. Today, marketing professionals are able to use data mining software to collect a wealth of information about their customers. Access to this kind of data is unprecedented, and can have a big impact a businesses level of success. ­McKinsey claims, for example, that a “retailer using big data to the full could increase its operating margin by more than 60 percent” (McKinsey 2011).

Unfortunately many organizations, especially small businesses with limited capital and capacity, aren’t able to optimize this data. The vast amount of information quickly coming into many businesses may render that very information irrelevant (Meyer, 1998). Information overload makes Leverhulme’s famous quote more frustrating than ever, as the data is available but beyond human comprehension.

As data mining becomes a more integral part of the business environment, managers and analysts will need to be trained on how to use data analysis to make effective decisions. By 2018, the United States is expected to be short of at least 140,000 people with the deep analytical skills to understand this information (McKinsey 2011). As human talent will be limited, it will be important to develop technologies that make information more clear and accessible to non-analysts.

Only once available data is made understandable will marketers finally begin to understand which dollars are being wasted.

 

[divider]ANALYSIS [/divider] 

Data mining technology is a remarkable business asset to those who are able to translate that data into useful information. However, the number of qualified analysts is already falling short of what would be needed to analyze the staggering amount of available data. That divide is expected to grow within the next five years (McKinsey 2011). Something will need to happen to either create more qualified analysts or make the information within the data more accessible.

Tools like Google Analytics begin to make vast quantities of mined data more accessible to everyday people. By using data visualizations, the patterns within data may become visible to the marketing manager of a small health clinic or advertising firm – places that don’t have the capacity to hire dedicated analysts. This visual information can help in determining what strategies are working and lead to more successful campaigns.  Information visualizations may be used to justify actions, campaigns, and decision-making (Ganapathy, 2004).

Firms and individuals must be careful, though, as the visualization of data often leads to the manipulation of data. Tufte explains the need to display quantitative evidence in ways that are “truthful, credible, and precise” (Tufte 1997). By using software that displays data in a visual and engaging way, specialized analysts may not be the only ones with the capacity to understand complex data.

Visualization software may help small firms compete in a growingly complex marketplace while identifying what parts of these firms’ budgets are being used most effectively.

 

[divider]REFERENCES [/divider]

Big Data: The Next Frontier for Innovation, Compeition, and Productivity. Mckinsey Global Institute (May 2011). http://www.mckinsey.com/insights/business_technology/

Ganapathy, S., Ranganathan, C. C., & Sankaranarayanan, B. (2004). Visualization Strategies and Tools for enhancing Customer Relationship Management. Communications Of The ACM47(11), 93-99.

LaValle, S., Lesser, E., Shockley, R., Hopkins, M. S., & Krushwitz, N. (2011). Big Data, Analytics and the Path From Insights to Value. MIT Sloan Management Review52(2), 21-31.

Meyer, J. (2998). Marketing Intelligence and Planning. Journal of Marketing Practice: Applied Marketing Science,16(3), 200-209.

Tufte, E. R. (1997). Visual and statistical thinking displays of evidence for making decisions. Cheshire (Conn.) (Box 430, Cheshire 06410): Graphics press.

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