Acompany can achieve increasing levels of maturity in itsorganization-wide analytic capabilities by sticking to the CapabilityMaturation Model. The tool defines a gradual path through whichinstitutions can develop their capacity to use and benefit fromanalytics(Cosic et al., 2012).In the first phase, the software adoption causes crisis andinconsistencies. The management relies on talents to and individualefforts to support the technology. In the next phase, an organizationdevises a project management department that allows the repeat of therealized successes. For example, the leadership can introduce theposition of a program manager to oversee the entire process. Thethird stage reflects a more stable organization that has standardizedits analytic tools and performance. The program management tailorsthe technology to suit the business operations. In the fourth level,an enterprise can take stock of the achievements and evaluate theeffectiveness of the analytics (Cosicet al., 2012).Finally, an organization achieves maturity and focuses on continuallyimproving the processes and maintaining the quantitativeachievements.
Samplesize is intricately related to statistical methods and outcomes. Thesize of the representative group determines the size of the datacollected and consequently the statistical method used to analyze theinformation(Marshall et al., 2013).For example, in a study relating to the effects political stabilityon investment choices in the state of Texas, researchers are likelyto collect numerous data that has to be analyzed to determine thecorrelation between the variables. They may employ tests like SPSSand ANOVA since the two are exploited when scholars have big data.Sample size also affects the outcomes of a study. According toRobinson(2014), abig group is considered to have more reliable results that allowresearch to be generalized in different settings. For example, in theabove example, Texas has a big number of investors. Singling out only10 of them would not be a true representation of the whole group.Therefore, the outcomes of such a study would not be reliable.
Planningthe sample, size before collecting data is imperative for variousreasons. First, it helps in determining whether the group is a truerepresentation of the target population. Secondly, it allowsresearchers to source for enough personnel and materials to be usedin a given study(Robinson, 2014).Finally, planning the sample helps in identifying the characteristicsof the population, for example, their proximity from each other, todevelop the most effective way to collect data.
Cosic,R., Shanks, G., & Maynard, S. (2012, January). Towards a businessanalytics capability maturity model. In ACIS2012: Location, Location, Location: Proceedings of the 23rdAustralasian Conference on Information Systems 2012(pp. 1-11). ACIS.
Marshall,B., Cardon, P., Poddar, A., & Fontenot, R. (2013). Does samplesize matter in qualitative research?: A review of qualitativeinterviews in IS research. Journalof Computer Information Systems,54(1),11-22.
Robinson,O. C. (2014). Sampling in interview-based qualitative research: Atheoretical and practical guide. QualitativeResearch in Psychology,11(1),25-41.