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Thereare several characteristics for the success of executives in ananalytical competitor. These characteristics are what have made thepeople standout in the organizations where they work.

Thefirst distinguishing factor is extensive use of modeling andoptimization. Unlike the previous business statistics whereby everyexecutive had access to basic information about their employees andthe sales they make, analytics provides more detailed data. Thesuccessful administrators use models to project future trends basedon the purchasing rates of their customers and even expected impactsof competitors (Schläfke et al., 2012). Thus, such managers are wellprepared for any possible outcome.

Anothercharacteristic of these executives is that they have an enterprisingtactic. They fully understand that for them to succeed in thecompetitive analytics, they should not rely on a specific innovation(Schläfke et al., 2012). These successful directors are versatileand find new ways to generate more income for their companies.

Lastly,these executives take full advantage of their sources of strength.Their strength not only comes from their experiences but, also, fromthe available resources (Schläfke et al., 2012). They achieve thisability through hiring the right people qualified to realize thegoals of the business. These administrators also ensure that theyselect the right strategy so that they know where to invest theirresources to attain their objective (He et al., 2013). They evencultivate the right culture in the organization to motivate everystakeholder towards that common goal (He et al., 2013).

Samplesize relates to statistical tests and outcomes since the sample sizedetermines the accuracy of the findings of the specific study(Marshall et al., 2013). An example is when a researcher wants toconduct a study based on the consumer’s response to a new softwareapplication. The sample size will affect the tests and outcomes sincedifferent people have various notions and opinions. Thus, theresearcher will have to be keen in selecting the population to bestudied based on several factors such as gender, age and level ofeducation (Marshall et al., 2013). It is important to plan the samplesize before data collection due to numerous reasons. The right samplesize will provide the most accurate results, hence, givingcredibility to the study (Marshall et al., 2013). Also, the samplesize will determine the duration and amount of resources needed toconduct the study (Marshall et al., 2013).


He,W., Zha, S., &amp Li, L. (2013). Social media competitive analysisand text mining: A case study in the pizza industry.&nbspInternationalJournal of Information Management,&nbsp33(3),464-472.

Marshall,B., Cardon, P., Poddar, A., &amp Fontenot, R. (2013). Does samplesize matter in qualitative research?: A review of qualitativeinterviews in IS research.&nbspJournalof Computer Information Systems,&nbsp54(1),11-22.

Schläfke,M., Silvi, R., &amp Möller, K. (2012). A framework for businessanalytics in performance management.&nbspInternationalJournal of Productivity and Performance Management,&nbsp62(1),110-122.

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