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Statistical Concept

A statistical concept refers to a statistical feature of either an observation or a time series.

However, these statistical concepts come in different formats. For instance, they can either be

coded or not depending on the validity of the available data. In other words, a statistical concept

can be used to denote statistical principles or guidelines that are accepted globally, based on

established definitions and concepts. These concepts, however, should be from accepted and

recognized statistical standards as much as possible (MacLaughlin).

Statistical concepts are very fundamental in organizations in ensuring the services

disseminated, and products produced are of good quality. Thus, having a basic understanding of

statistical concepts plays a very significant role in interpreting conclusions from gathered data.

This form of knowledge ranges from being able to discern and use basic statistical concepts

which include measures of central tendency, probabilities, percentages, and ratios. However,

having more advanced knowledge of statistical concepts can help an organization to interpret

other statistical information demonstrated in graphs and tables. This is very advantageous

especially when analyzing and interpreting more exhaustive data. Hence, with a more advanced

statistical knowledge, it would prove more comfortable for logically examining any form of data

and as a result, make informed statistical decisions (MacLaughlin 61-65).

Availability of extensive data in our businesses and nonprofit organizations today has

necessitated institutions to start adopting analytical solutions to draw meaning from their

operations while enabling them to make informed decisions. However, these facilities require

general statistical abilities to allow for them make a better analysis of their historical data and

make valid forecasts based on trends towards their future business operations. When an

organization relies extensively on data and becomes data-driven, chances of it becoming great in

its operations becomes imminent. Thus, when firms exploit their statistical analytical

capabilities, favorable outcomes such as an increase in revenue, lowered costs in operations,

product mix portfolio and improved customer service delivery are more likely to be evidenced.

There exist myriad statistical analytical options and analyzing them singly can prove a

dashing chore. However, fortunately, these statistical concepts and their systematic alternatives

can be broadly be categorized into three major classes. These include descriptive, predictive and

prescriptive statistical analytical options. All the three distinct categories tend to answer

questions such as "What has happened?", "What could happen?" and "What should we do?"

respectively (MacLaughlin 35-39).

This study aims to establish the best statistical analytical approach especially for a

nonprofit organization, and determine how the approach helps these agencies in making better-

informed decisions. I will use Catholic Relief Service, CRS, as my case study. CRS was formed

in 1943 in the United States during the Second World War and has grown to a prominent

nonprofit organization that assists the impoverished and the disadvantaged group in the society

(Cekan). Its organizational faith is based on Catholic doctrine and teachings in advancing and

promoting the dignity of the human race. It also upholds the sanctity of the human life regardless

of an individual's religion, race, needs, and ethnicity (Govekar 102-103). My focus will be on
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prescriptive analytics which centers its abilities in finding out the best mode of action to take in a

given situation and determining the best outcome among several available alternatives. The

prescriptive analytical approach applies the desirable features of both the predictive and

descriptive analytics in suggesting desirable decisive options (MacLaughlin 94-98). It is also

instrumental in exploiting available opportunities for future use or even extenuates a likelihood

of a future risk while clarifying the impact of every decision alternative. Some of the techniques

used by this approach comprise of simulation, decision making and analysis methods,

optimization and game theory (Wheelan 37- 43).

Nonprofit organizations are most favored by the prescriptive analytical approach due to

its ability to automatically process and analyze newly acquired data. This significantly improves

the accuracy and reliability of the organization's forecasts thus enabling it to make right decisions

in both the current period and in the future. The Catholic Relief Service, CRS has extensively

applied the prescriptive analytical approach in most of its operations. For instance, CRS uses this

method in estimating the extremity of food insecurity, successful recognition of vulnerable

groups and identification of appropriate interventions. Over the years, the organization has been

facing acute shortage of food to feed its ever increasing population which risks their sustenance.

As a result, the prescriptive approach has been very instrumental in evaluating the scope of the

existing challenge while assessing the feasibility of supporting the livelihood of its needy cases.

The plan has also enabled the organization in pointing out implementation strategies and phasing

out some of the likely undesirable impacts. In all their operations, the central question they

strove to answer is "What should we do?"

After analyzing and evaluating the harshness of the risks of its needy cases, CRS assesses

the prevailing condition by critically looking into some of the leading aspects of their challenges

such as.

1) Who are the leading susceptible group and why are they so

2) What are the available primary aspects of livelihood support

3) What is the most feasible strategy of livelihood support

4) Who are the most effective informal organizations to work with and how will that

impact positively their priorities

5) What is the most likely potential negative implications of livelihood support

After this critical analysis of the underlying problems, CRS came up with a variety of the most

applicable solutions. Some of these potential solutions are;

a) Providing a multi-dimensional approach to identifying the most vulnerable group.

This enables them to focus more on these groups and sufficiently prioritize their needs.

b) Determining the current level of food insecurity while applying sufficient food,

health as well as medical interventions.

c) Providing a timely warning concerning susceptibility of information.

d) Disseminating relevant cultural and social knowledge on necessary interventions

to relevant stakeholders.

The approach helped rectify the enumerated challenges which assisted the organization to

attain its equilibrium. Moreover, the prescriptive approach was very instrumental in clearing out

inefficiencies especially in programs accountabilities.

Catholic Relief Service's ability to efficiently manage and utilize their resources can be

significantly attributed to its prescriptive approach in its accountability. Accountability has

always remained the leading concern of the CRS. This has contributed enormously to the hefty

donations they receive from well-wishers as well as other stakeholders. It is also viewed as one

of the most competent organizations globally. It is approximated that 90 percent of the money

donated and spent towards its course goes to the poor abroad. The organization also boasts of a

financial efficiency which has enabled it to be honored by the Wise Giving Alliance, Charity

Watch among other renowned charity bodies. Conversely, the prescriptive analytical approach

aids the organization in making prompt responses during emergency cases such as delivering

emergency supplies and in food distribution to deserving locations. They also have a well-

organized network that manages critical instances of natural disasters such as tsunamis,

earthquakes as well as typhoons among other calamities.

In conclusion, though the prescriptive analytical approach is considered the most

advanced form of a statistical concept, it cannot, however, be viewed as a perfect, flawless

approach. In some instances, the method suffers from the similar distortions that are experienced

by both the predictive and descriptive approaches. These distortions may include data restrictions

and the accuracy of the decision models used in formulating a given decision. However,

prescriptive analytical approach adoption by organizations has rapidly increased which has

intensified the acceptance of the prescriptive models. Thus, when this approach is enforced

efficiently and accurately, it can pose a very significant impact towards an organization's

decision, making it progress at a robust pace.

Work Cited

Cekan, Jindra M. "Catholic Relief Services." (1995).

Govekar, Chris. "Catholic Relief Services." International Encyclopedia of Civil Society. Springer

US, 2010. 102-103.

MacLaughlin, Steve. Data driven nonprofits. 1st ed. Cardonald, Glasgow, G51 4EA.: Saltire

Press, 2016. Print.

Wheelan, Charles. Naked statistics: Stripping the dread from the data. WW Norton & Company,

2013.