Employer satisfaction with the demand driven system in Michigan
The survey aims to
- Determine the frequency of use of the demand driven system by employers
- Discover the level of satisfaction amongst employees in the demand driven system of workforce development
- Find out if the demand driven is effective in production of suitably qualified personnel
- Determine if the system is efficient enough to produce an adequate number of required workers
- Determine the gaps in the demand driven system of sourcing and developing workforce
The demand driven system has been hyped as the ultimate solution to effective development of the workforce. The state of Michigan has rolled out the program and spread it to all areas of the state. Since the existing data is insufficient in gauging the effectiveness of the demand driven system of workforce development, this survey will be useful in collecting data that can help to judge the efficacy of the program. The survey will also determine the favorable outcomes of the system given the resources invested in the program.
The main research design to be employed by the survey will be the program evaluation typology. According to Paulsen and Dailey (2002),a program or intervention can be kept on track, monitored or controlled through the program evaluation. The program evaluation encompasses both formative and summative evaluation and can thus be used to monitor the implementation stages of the program hence determine whether or not the particular intervention or program is working.
Formative evaluation is the kind of assessment that is done to determine the quality of a program and feasibility of implementation as well as its impact. This type of evaluation is carried out in order to provide feedback and information, which is useful in improving the program at internal levels. Summative evaluation on the other hand is aimed at assessing the effectiveness of the program and it thus provides information regarding the impact of the program to external agencies. Therefore, the program evaluation research typology is the most appropriate research design that can help to determine the satisfaction levels of employers who use the demand driven system of workforce development.
The main operational indicator in this survey is employee satisfaction and it is the dependent variable of the study. The other operational indicator is the access to, and utilization of the demand driven system of workforce development which will be used as the independent variable in the survey.
Location of the survey
The study will be carried out in the Capital Area, Lansing Michigan
The target population of this survey will be employers who are registered at the Capital Area Michigan Works! Lansing Michigan.
The survey shall use stratified random sampling which ensures that the specific groups are well represented within the sample (Black, 1999). This technique helps to capture the key features of the population in the sample. In the stratified random sampling, the population is divided into strata according to common attributes and sample sizes from every strata can be manipulated to make sure that the sample is weighted and hence representative of the population. Stratified random sampling employ probabilistic techniques in the selection of units from the identified strata. Therefore, the statistical conclusions that can be derived from the data are considered valid.
Compared to random sampling, stratified random sampling is considered more precise during sample selection and this implies that smaller sample sizes can be utilized during the survey and hence save money as well as time. This technique also allows the researcher to make comparisons between the strata from the data collected and can thus help him or herin making”more valid inferences from the sample to the population” (Stratified Random Sampling, 2012).
Employers registered at the Capital Area Michigan Works! Lansing Michigan are the main target sample for this survey and the employers will be divided into strata in the following manner:
- The main criteria for categorization will be to create a group affiliated to industrial cluster as listed by the Michigan Works! workforce development center in Capital Area, Lansing.
- The employers will be divided into different substrata depending on their sizes. Basically there will be two broad categories consisting of small employers and large employers. The small employer will include “any person, firm, corporation, partnership, limited liability company or association actively engaged in business who, on at least 50% of its working days during the preceding or current calendar year employed at least 2 but not more than 50 employees” (Small Employer Group Health Coverage Act, 2014).
- The location will be the last substratum for dividing the employers in which case they will be divided into rural and urban employers.
The target population will be divided and listed according to the above three strata. After listing the employers in accordance with the given strata, the researcher will compare the population sizes of each stratum and calculate the percentage of each stratum in relation to the entire population. The total sample size will consist offorty employers and they will be selected from each of the stratum. The sample size selected from each stratum will be proportionate to the percentage of the sample in comparison to the total population and the researcher will use simple random sampling to pick out sample populations from each sample.
Stratified random sampling has some limitation, and the first one is that this sampling technique is only valid if one obtains a “complete list of the population” (Stratified Random Sampling, 2012). It might be difficult to obtain this list and in order to minimize this challenge the researcher shall get lists from other credible bodies like the chamber of commerce to ascertain the completeness of the list obtained from the Michigan Works! office. The second issue arises from the fact that the population may not fit into the strata, as the population is not clearly delineated. In order to ameliorate this problem, the researcher has divided the main strata into substrata as thiswill help in extra differentiation of the population and make the population be betterseparated, compared to when using only one major stratum to classify the population. The above measures will help to minimize challenges and make the survey findings more accurate and generalizable to the whole population.
Data collection techniques
Data for this survey shall be collected through the use of questionnaires. Wilcox (1999) suggests that questionnaires need as much scrutiny as the methods or findings of a research and this is due to the dependence of the survey’s conclusions on data collected by the questionnaire. It is thus imperative to ensure that a questionnaire is of sufficiently high standard to generate credible data. A questionnaire has several benefits as a data collection instrument. It can help the researcher to collect a large amount of information within a short period and also enable them to contact a large number of respondents in a timely and cost effective manner. Questionnaires are also suitable for collecting data from employers who are located in different stations because it can help to get information from a wide geographical area.
When using questionnaires it is easy to code the data and this makes it easier to apply statistical methods of interpretation. Questionnaires can increase objectivity of the research findings because it is free of researcher’ bias. Since questionnaires are filled confidentially, the data obtained is likely to reflect the true picture and perspectives of the respondent.Rattray and Jones (2007) state that in order to be effectivea questionnairemust be reliable and valid. Inter-item correlations can be used to improve the reliability of the questionnaire which can be used to determine if constituent items measure the same domain. The questionnaire shall also be constructed in such a way that it will have content validity as well as construct validity.
There are many challenges of having questionnaires as a tool for data collection. First and foremost, it is not possible to determine whether a respondent is being honest or not when answering the questions. There are chances of respondents misunderstanding the questions and to avoid this scenario it is advisable to have the sample size spread over the whole population in order to remove the possibility of local bias. The questions should be worded simply and clearly so as to remove any aspects of ambiguity. During the questionnaire design phase, it is necessary to deal with all problems associated with validity.
In order to save on costs and time, the web-based tool, survey monkey will be used to collect data. This will enhance efficiency in data collection.
Analysis of data collected will be done using the (please indicate the statistical package you will be using to analyze the data)
The Business Services Team (BST), will use the findings from the survey to review the effectiveness of the demand delivery system. This information will be helpful in identifying new interventions that can help to improve the program and may also determine whether the service should be discontinued altogether.
Suggested questions to be included in the survey
- From which source did you learn about the demand delivery system?
- How long have you known about the demand delivery service?
- As an employer, how regularly do you use this particular delivery service?
- In what position(s) have you hired personnel by making use of the demand delivery service?
- Do the employees employed using the demand delivery system have appropriate academic qualifications for the positions employed?
- Have the employees employed using the demand delivery system shown job competency since they began working for you?
- Have you observed individual initiative and independence in the work of the employees employed using the demand delivery system? If yes, how often?
- How would you rank the employees employed using the demand delivery system in terms of carrying out their duties effectively?
- How often has the demand delivery system provided you with sufficient numbers of suitably qualified employees?
- Has the staff of Michigan Works! responded to your concerns and suggestions concerning the system? If yes, how often?
- In your opinion, what can be done to improve the demand delivery system and service?
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Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement, and statistics. Thousand Oaks, CA: SAGE Publications, Inc.
Paulsen, C. & Dailey, D. (2002). A Guide for Education Personnel: Evaluating a Program or Intervention. Retrieved from http://www.air.org/files/eval.pdf
Rattray, J & Jones, C. (2007). Essential elements of questionnaire design and development.Journal of Clinical Nursing 16, 234-243
Small Employer Group Health Coverage Act, (2014). Department of Insurance and Financial Services. Retrieved from http://www.michigan.gov/difs/0,5269,7-303-13648-82698– ,00.html
Stratified random sampling, (2012). Lund Research. Retrieved from http://dissertation.laerd.com/stratified-random-sampling.php
Wilcox, J. (1999). The Quest for Better Questionnaires. Am. J. Epidemiol, 150 (12), 1261-1262.