Decision Making


Businesses exist in a dynamic macro environment, which requires appropriate changes to align business operations with the environment. As a result, analysis of various factors that affect a business is imperative not only for survival, but also for success of the company. Capable leaders who steer their businesses through the turbulence of the external environment are those that embrace objective methods of environment and situation analysis (Kohavi, Rothleder, & Simoudis, 2002). Quantitative analysis has always been argued to be the best approach to objective decision-making. Quantitative methods also rely heavily on technology, making the two seem to be inseparable in businesses that are deemed successful. This essay reviews the manner in which a company prospers as an analytic competitor, as well as the strength of an analytic competitor, with arguments being based on Davenport’s “Competing on Analytics” article

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Prospering as an Analytics Competitor

For a company to prosper as an analytic competitor, it has to be characterized by a number of factors. The company has to embrace a widespread use of both modeling and optimization. An analytic competitor should be able to go beyond the horizons of typical companies that only generate and rely on simple descriptive statistics based on various sections of the business such as marketing, human resource management, and finance among others (Davenport, 2006). Analytic competitor surpasses such basic statistics and reaches for predictive modeling, which enables the business to identify both profitable and unprofitable market segments. Data that are generated in-house as well as collected from other external sources are pooled together with the purpose of in-depth analysis and comprehensive understanding of the targeted phenomenon, for instance, customers. Models enable a business to check relationships, causes, effects or even predict the future. Quantitative methods can also be an asset in optimization when a business can determine consequences of unexpected constraints, develop alternatives, and thus solve various problems such as those relating to transport. The models are also important in the establishment of prices in real time so as to obtain the maximum yield from every transaction the business undertakes with a customer. Operational costs are determined based on complex models generated by an analytic competitor. All these applications of modeling and optimization are generated from complex and sophisticated experiments to ensure that the models generated have known impact on the overall organization and that existing models can be continuously improved.

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The second attribute of an analytic competitor is adopting an enterprise approach to its business organization. Such a business operates under assumption that all business functions can be continuously improved by some quantitative approaches. Often, such organizations do not rely on one application to determine a decision for all the sections of the business, but rather apply multiple quantitative applications to support various parts of the business. However, all applications used by the analytic competitor are supposed to link various stakeholders in both the backward and forward supply chain, i.e. both supply and  customers. According to Davenport (2006), analytic competitors often treat all activities from all origins as a single and coherent initiative that can be grouped into one rubric like the information-based strategy. Instead of dedicating the analytics to one department as traditional companies do, the enterprise approach allows for knowledge and participation of all sections of the company to generate models that will affect the organization as a whole. In that case, objective analysis of data, which considers all sections of the organization, leads to prosperity of an analytic competitor.

Lastly, senior executives’ advocates inform prosperity of analytic competitors. According to the common knowledge, company leaders are the ones who drive change and inspire adoption of new decisions in an organization. Accordingly, they play an important role in ensuring success of an analytic company. Embracing analytics, according to Davenport (2006), requires a change in culture, behaviors, processes, as well as skills on the part of employees. Leaders such as the company’s CEO are, therefore, required to be passionate for quantitative analytics and inspire their employees to develop a positive attitude towards analytics. Even without in-depth knowledge of statistics and qualitative techniques, leaders with positive attitude and passion for analytics lead their businesses to prosperity.

Sources of Strength for Analytic Competitor

Prosperity of an analytic competitor is derived from a number of aspects in the company that provide strength to the analytic competitor. One of these sources is right focus. Analytic competitor usually advocates for universal decisions that are backed up by facts. However, such a competitor chooses a direction in which the focus of the business is to be directed and then deploys sufficient direct resource intensive efforts in that direction (Davenport, 2006). Generally, several functions in the business or initiatives together provide focus to serve as an overarching strategy to guide the business. The focus is usually the focal point of the analytic competitor’s vision. Thus, mission and analytics are directed at analyzing variables in the mission and objectives.

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Having the right culture is also a very important source of strength for the analytic competitor. Davenport (2006) argues that analytics is a hard discipline. Nevertheless, the analytics competitor derives strength from instilling a companywide means of measuring and evaluating evidence quantitatively. The culture should always urge employees to arrive at decisions that are supported by facts. Similarly, measures of the human resources performance should be evaluated based on the same quantitative measures, rewards, and compensations given accordingly. Culture cannot be without people and, thus, right people are as well identified as a source of strength for the analytics competitor. Analytics competitors, therefore, often hire experts of analytics in every department. This cultivates the analytic culture and increases the possibility of considering issues quantitatively.

Finally, the right technology also counts as a source of strength. Analytical competitors investigate the latest quantitative methods and technology to supplement decision-making processes. Informed analytics ought to have  data strategy, which allows for collection, synthesis, and processing of data; business intelligence software that allows for making decisions based on collected data; and computing hardware, which determines the volume of information that can be accessed and capacity of the system to manipulate various data.

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