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Market analysis db
1. Marktanalyse Deutsche Bahn
Deutsche Bahn
Mobility, networks, logistics
Präsentation Marktanalyse WS 2013
Betreunde Professor: Prof.Dr. Tobias Schütz
Vorgelegt von: Fabio Cozzolino, Ziv Reichert, Juan
Carlos Zarraga Teuril
2. Marktanalyse Deutsche Bahn
Executive Summary
• Employer Branding is a relatively new discipline which has sparked the interest of many
researcher interested in identifying the components that make a successful employer brand.
• This study makes use of past research to build an employer attractiveness scale for German
employers and specifically for Deutsche Bahn. The findings identified 4 constructs Economic
Value, Social Value, Company Value and Development Value (Emvalue).
• Further analysis has been conducted in order to test the model and explore further solutions
for DB.
• Deutsche Bahn revealed to be poorly competitive in the Social value and Company Value
aspects.
• A step by step approach has been taken in order to provide an easy guide that will help the
firm in applying a strategic approach to the Employer Brand Experience.
• A set of 5 specific recommendations based on digital innovation, measurements and
evaluation, employer brand experience management has been developed.
• Further research ideas can help Deutsche Bahn in making full use of this study and develop a
customised employer brand solution.
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5. Marktanalyse Deutsche Bahn
Project
-> Build a franework that will help DB in measuring employer attractivness
-> Provide insights on main differences between female and male candidates
-> Provide recommendations on how to attract the target group.
Actions
• Leading passenger and logistic
company
• Operates in 130 countries
• 34.4 billions operating profit
(DeutscheBahn website, 2013)
Client Sponsor
Low female presence within employee
population
Difficulties in attracting young graudate
engineers
Corporate brand negatively associated to
company service s(e.g. ICE)
Situation
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6. Marktanalyse Deutsche Bahn
Background Research
Research Findings
Action Recommendations
Sample Description
Method and Rationale
Introduction to the Project
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7. Marktanalyse Deutsche Bahn
Method and rationale
Data collected from a questionnaire and
handed out to 350 participants
Use of exploratory factor analysis and
confirmatory factor analysis (through
PLS) to build an employer attractivness
(EA) scale.
Further investigations based on
constructs
Method
Previous research shows interest in
developing a significant way to assess EA.
This piece of research has support from a
previous study conducted on EA in the
Western Australia.
Focus on German engineering graduates
and on German employers.
Rationale
EA scale for German Employers
EA scale for German Employers based on young female engineers
Further analysis and action recomendation based on findings
Output
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8. Marktanalyse Deutsche Bahn
Background Research
Research Findings
Action Recomendations
Sample Description
Method and Rationale
Introduction to the Project
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9. Marktanalyse Deutsche Bahn
Total Sample Breakdown
Sex
Age
Studies
Semester
Institution
Region
Programme
231 Male
Students
119 Female
Students
Relevant
figures
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10. Marktanalyse Deutsche Bahn
Total Sample Breakdown
Sex
Age
Studies
Semester
Institution
Region
Programme
Mean Age:
24.21 years
Relevant figures
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12. Marktanalyse Deutsche Bahn
Total Sample Breakdown
Sex
Age
Studies
Semester
Institution
Region
Programme
Relevant
figures
Semester:
3rd semester
(69 students)
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Total Sample Breakdown
Sex
Age
Studies
Semester
Institution
Region
Programme
Count:
Bachelor:237
Master: 113
Relevant
figures
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22. Marktanalyse Deutsche Bahn
Females vs. Males
Further Studies: 83 (35.8%) Master
(31% no result)
Work Experience: 69 training , 141
Internship, 71 others and 33 no
experience
Experience at DB, LT, SI: 10% DB,
6.1% LT, 12.6% SI
Employer type: 127 (55%) Big
companies and conglomerates
Salary Expectation (1st):38800€ on
average
Salary Expectation (5): 56600€ on
average
Future: 69% plan to remain in
Germany, 4,3% will leave, 26, 4%
uncertain
Further Studies: 51 (42,98%)
Master (34% no result)
Work Experience: 14 training , 77
Internship, 30 others and 18 no
experience
Experience at DB, LT, SI: 9.9% DB,
6.9% LT, 7.9% SI
Employer type: 57 (47.9%) Big
companies and conglomerates
Salary Expectation (1st):40000€ on
average
Salary Expectation (5): 57000€ on
average
Future: 67.2% plan to remain in
Germany, 1,7% will leave, 31.1%
uncertain
Further Studies: 134 (38.3%)
Master (32.3% no result)
Work Experience: 83 training , 218
Internship, 101 others and 51 no
experience
Experience at DB, LT, SI: 10% DB,
6.4% LT, 11% SI
Employer type: 184 (52.6%) Big
companies and conglomerates
Salary Expectation (1st):39380€ on
average
Salary Expectation (5): 56810€ on
average
Future: 68.6% plan to remain in
Germany, 3.4% will leave, 28%
uncertain
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Background Research
Research Findlings
Action Recommendations
Scale Building and EMvalue
Research Hypothesis based on EMvalue
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Scale Building
THE Employer attractivness Scale (EMValue)
• Reliability measure and item purification (selection)
through Cronbach‘ alpha (see Appendix I)
• Explorative Factor Analysis to compute the model
• Only Factors with Eigenvalue >=1 where chosen (see
Appendix I)
• Confirmatory Factor analysis carried out through
PLS-SEM
Technical Information
• Ambler and Barrow three Dimensions
(1996)
• Berthon, Ewings and Hah five factors
(2005)
• Aberdeen group (2009) Employer
Branding inside and out.
Previous Research
Based on four factors:
->Economic Value, Society Value, Company Value and Development Value.
->It provides a base for comparison between the companies and could be applied to a German context
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Results
• Economic Value (1)
• Society Value (2)
• Company Value (3)
• Development Value (4)
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Factors
Factors components
1. Work-life balance, salary offer, bonuses, fringe benefits, benefits range, work
environment
2. Family influence, personal perspective(built upon society perspective), friends.
3. General financial performance, product performance, rankings, prizes, CSR.
4. Trainings opportunities, learning and talent development opportunities etc.
27. Marktanalyse Deutsche Bahn
Scores
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Deutsche Bahn Siemens Lufthansa Technik
EV =7.08
SV=6.63
CV=6.74 DV=7.21
SV=7.58SV=7.67 EV=7.53EV=7.53
DV=8.13DV=8.12 CV=8.42CV=8.39
EV= Economic Value
SV= Social Value
DO= Development Value
CP= Company Value
10
7
5
1010
7 7
55
28. Marktanalyse Deutsche Bahn
Testing the model
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Regression Analysis to confirm the influence
on the willingness of the students in
starting their career at one of the firms
The model explained that the factors
influence willingness to start their career at
one of the companies with a R2 of 0.8 in
almost all the observations (Appendix III)
-the society perspectives construct was the
most influential factors in the model.
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Further Testing (2) with PLS
• The model was further tested (see Appendix
II) via the Smart-PLS software.
• Really positive results showed that the data
actually fit the model previously explored
through factor analysis (see Appendix II).
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30. Marktanalyse Deutsche Bahn
“Step-by-Step” Recommendations
based on Total Scores
- Two main weaknesses: Social Value,
Company Value.
- Integrated Brand
Management and employer
brand experience (Mosley,
2007)
-Increase perceived brand
innovation and performance.
- Communication models and
channels
-By following a strategic
framework (Moroko, l and
Uncles, M., 2008)
-Differentiate career paths
and integrate a specific
communication means for
engineering students.
-Develop a personal Brand
identity and investigate
values experience by its own
employees (Ritson, M., 2013)
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Challenges
What to improve
How to Improve?
35. Marktanalyse Deutsche Bahn
Step-by-step solutions based on
female students scores
. Physical lack of female students
interested in the subject
- Culture communication
problems
-Level of engagement with
female population
-Increase interest in the subject
from first steps into education.
-Provide short term internships
for female students (at high
school level) in order to improve
interest in the subject.
-Start a female leaders
mentoring scheme aimed at
increase female workers at all
levels in the organisation
(Bonvissuto, K., 2001)
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Challenges
What to improve
How to Improve?
36. Marktanalyse Deutsche Bahn
Models Pros and Cons
Difficult to guarantee external
validity despite numbers of tests
available
The model could overgeneralize
real situation and be to simplistic
Purely quantitative approach
Measurement errors might affect
the results
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A ready to use and powerful tool for
inexperienced HR teams
Provide the base for further research and
experimentation
It may provide a rare tool to examine the
characteristics of successful/unsuccessful
employer brands (Moroko, L., Uncles, M.,
2008)
An easy and concise way for comparison,
self-evaluation and problem recognition
- +
38. Marktanalyse Deutsche Bahn
Further investigations
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H1: Product performance (e.g. attractiveness, innovation etc.) influence candidates
choice when applying for a company
Results
-A Regression analysis approach was applied to investigate the hypothesis.
-The results were significant, showing a relationship between product and candidates choice when
applying for a job position. Thus, supporting the findings of Emvalue scale.
Hypothesis
39. Marktanalyse Deutsche Bahn
• On average our investigation showed that the
female students had poor knowledge of the
culture, environment etc. at each respective
firms.
• Surprisingly many other investigation showed
that male and female students are similar in
their preferences (e.g. Salary expectations and
career making)(see Appendix IV)
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Further investigations
41. Marktanalyse Deutsche Bahn
Action Recommendations
A digital Revolution –
Best tool for improving
reputation (Valor, 2009)
The scale itself could be used
as a measurement tool and
integrated in the whole brand
management experience
Implementing a specific
and strategic approach
to employer branding for
engineering students by
using a strategic
framework and by
integrating a specific
career profile (page)
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42. Marktanalyse Deutsche Bahn
Action Recommendations
Take advantage of the lack of
communication to female
graduates in the industry by
inspiring future qualified
women early in their career.
Redesign product
performance and
implementing innovative ideas
by digitalizing and reinventing
work environment.
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43. Marktanalyse Deutsche Bahn
Further research ideas
• Plan a larger sample of female students for a
more precise analysis
• Evaluate values experience by DB employees on
an annual basis with an in-house specific
questionnaire together with focus groups
• Repeat this study by using a combination of
qualitative and quantitative data to improve
performances
• Take into account more competitors in order to
achieve a better view of the German Employers
market
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45. Marktanalyse Deutsche Bahn
References/Literature
• Ambler, T. & Barrow, S. (1996) The employer brand. Journal of Brand Management,
4(3), pp. 185–206.
• Berthon, P, Ewing, M, & Hah, L 2005, 'Captivating company: dimensions of
attractiveness in employer branding', International Journal Of Advertising, 24, 2,
pp. 151-172, Business Source Complete, EBSCOhost, viewed 6 January 2014.
• Bonvissuto, K 2001, 'Women's initiative sets new goals', Crain's Cleveland Business,
22, 9, p. 23, Regional Business News, EBSCOhost, viewed 7 January 2014.
• Churchill, G.A. Jr (1979) A paradigm for developing better measures of marketing
constructs. Journal of Marketing Research, XVI, pp. 64–73.
• Jones, B, Temperley, J, & Lima, A 2009, 'Corporate reputation in the era of Web
2.0: the case of Primark', Journal Of Marketing Management, 25, 9/10, pp. 927-
939, Business Source Complete, EBSCOhost, viewed 6 January 2014.
• 'Lowdown' 2009, Prweek (U.S.), p. 10, Business Source Complete, EBSCOhost,
viewed 6 January 2014.
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46. Marktanalyse Deutsche Bahn
• Moroko, L, & Uncles, M 2008, 'Characteristics of successful
employer brands', Journal Of Brand Management, 16, 3, pp.
160-175, Business Source Complete, EBSCOhost, viewed 6
January 2014.
• Mosley, RW 2007, 'Customer experience, organisational culture
and the employer brand', Journal Of Brand Management, 15, 2,
pp. 123-134, Business Source Complete, EBSCOhost, viewed 6
January 2014.
• Ritson, m 2013, 'Employer branding can do real harm so stop it',
Marketing Week (01419285), p. 42, Business Source Complete,
EBSCOhost, viewed 7 January 2014.
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References/Literature
47. Marktanalyse Deutsche Bahn
Appendix I ExploratoryFactor Analysis
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Measure of reliability used for item
purification whole data set
Measure of reliability used for item
purification female data set
Reliability test shows extremely positive
results in accordance with Churchill ‘s
criteria (1979)
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Appendix I Exploratory Factor Analysis
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Relevant data total dataset
Relevant data female dataset
Both KMO test and Bartlett’s Test show
significant result
Especially KMO with the .963 and .975
measures
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Appendix I Exploratory Factor Analysis
• Eigenvalue Criterion
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The first four factors were extracted.
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Appendix II Confirmatory factor
analysis with PLS
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Both Internal Validity and reliability parameters are satisfied. Furthermore, less only 4
iterations where completed. Thus, confirming that the data fit the model.
AVE= suggested values >0.5
Composite reliability = suggested values > 0.817
Cronbachs Alpha= suggested value > 0.8
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Appendix II Confirmatory factor
analysis with PLS
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All loadings from reflective items
respect the > 0.7 recommended
value
When performing
confirmatory factory analysis
on PLS, all the constructs
must be connected to each
other(Source: Smart-PLS
forum)
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Appendix III – Further Testing
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Results Regression
Analysis willingness
to start a career at
DB vs. Factors
All the variable
were significant to
the model as it is
possible to
observe from the
Sig. column.
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Appendix IV- Further Investigation
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Both the analysis show homogenous variance and thus F-test was analysed.
F-test shows that no significant difference has been observed. (Sig.>0.05)
Editor's Notes
The Executive summary provides a quick overview of the presentation and main findings. Although it is highly recommended to master the topics from the main presentation slides.
The presentations has been divided in three main cores: Background Research, Research Findings and Action Recommendations.The Background Research section is going to give a brief introduction to the background information behind this study, such as project information, proceedings etc.The Research Findings section gives a more detailed overview of how the study (analysis) was conducted technically and the discussion of the main findings.The Action recommendation section provides a set of actions that the firm should take into account after being presented to this study. This include formal resolutions for the Employer Brand and further ideas for research.
This slides provide an overview of the project. Deutsche Bahn (DB) is a leading firm in the fields of logistic and passenger transportation. With 34.4 billions of operating profit and operation in more than 130 countries, Deutsche Bahn is also one of the most present and successful firm in the industry. On the other hand, after an analysis of the approach to the firm and thanks to the telephone brief received by the client it was clear to the team that the firm lacked a strategic use of the HR function. Furthermore, bad corporate image through national scandals, a low female presence within the employee population and a corporate brand strongly related (negatively) to the services offered make difficult for DB to achieve its objectives of becoming on of top ten employers of Germany, especially for engineering students. The team perceived, from the very first moment, that DB lacked of structured and measures and methods in their HR function. Thus, this study was developed with the idea of providing this measures to DB by designing a framework that would help the firm in measuring its attractiveness in the German market and provide a study specifically for measuring attractiveness traits from the female students point of view.
Before explaining the method, it is interesting to look at the rationale behind this study. Previous research has shown great interest into exploring the different components that make a successful employer brand. It is possible to confirm this statement from the very first paper on employer branding written by Ambler and Barrow, which will explore later in this presentation. Further research, then, started to become also interested in how to measure this components (Look Berthon, Ewings andHah, 2005). This study has its grounds in the Berthon, Ewings and Hah research and their suggestions on further research on their study. As such, the very same method has been applied for the core analysis, although this analysis is purely quantitative respect to the one conducted by the mentioned researchers. This approach has been taken because no researcher has ever conducted this study on the German market, thus sparking the interest of this team in conducting this analysis.The data was collected through a questionnaire developed by the whole Market Analysis class and handled to 350 students through a third party organisation. The use of exploratory factor analysis ( better say principal component analysis) has been used to identify the model’ components and then a confirmatory analysis has been performed for confirming weather the data fit the model or not and for testing internal validity. (Further data on scale building presented later in this work)Furthermore, other investigations were conducted in order to gain a better picture of the model.The output is in the form of two scales: a total employer attractiveness scale and a female students EA scale plus a series of recommendations based on the findings.
This section goes through main statistics of the data sample
The average age of the sampled students was 24.21 years
Surprisingly, the biggest group of students was enrolled in aWirtschaftsingenieurwesen course, followed by Maschinebau.
Most students were enrolled in their 3rd semester of study
There was a relatively similar amount of university and university of applied sciences students with the least being in a slightly higher number.
Most of the student came from Baden-Württemberg, followed by Nordrhein –Westfalen. Overall most german regions were represented.
Most students were enrolled in a bachelor programme.
The average age of female participants was 23.75 years
As for the total sample, most of the female students was enrolled in a Wirtschaftingenieurwesenprogramme
Also in this case, 3rd semester female students were the most represented
On the other hand, more female were studying at a University.
Again Baden-Württemberg was the most represented region.
Again Bachelor students were mostly represented in the female sample.
This slides present further information about the sample by dividing sample between female and male students. Also an aggregated solution was presented on the slide as well.The data for the work experience are repeated because some students had both training experience, internship and other experience in a firm. Surprising was the slightly higher salary expectation of the female sample respect to the male sample (further analysis conducted)On average, most of the students planned to stay in Germany after graduation.
This slides finally presents the model description.The items chosen for the factor analysis were chosen by giving the scale a reliability measure (Cronbach’s Alpha) computed with SPSS. The results were really positive as it is possible to observe in the Appendix I. Also the factor extrapolated were using a Varimax rotation and only the factors with Eigenvalue more than 1 were selected or (MINEIGEN criterion). Furthermore, to test whether the data selected fit the model and to investigate internal validity also a Confirmatory factor analysis was performed thanks to the support of the PLS-SEM software.The results were highly interesting as they are different from previous research even if they have same grounds. The model produced found factors that were named through the help of previous research especially the work of Ambler and Barrow and Berthon, Ewings and Hah.Previous research had identified three elements with Amber and Barrow :-Psychological benfits-Economic benefits-Functional benefitsBerton, Ewings and Hah, have first developed a five factor model:-Interest Value.-Social Value.-Economic Value.-Development Value.-Application value.Our study wanted to examines whether this factors would be present also on German market and the results showed similar component that we labeled based on Berton, Erwings and Hah work.Economic ValueSociety Value Company valueDevelopment valueOur factors differs in some aspects from the one found from the researchers quoted but they do incorporate the aspects of Amber and Barrow research.
Here is another example of study on employer brand components conducted by Aberdeen group. Many of these aspects were incorporated by the model produce from the factor analysis performed by this study.
Here is an explanation of our factor and what do they include.They differ from Berthon, Ewings and Hah factors as the interes value and application value factor are not present. Furthermore, the economic value includes all the company’s offer to the employee ranging from salary to work environmentThe second Social differs in its meaning of social as it represents all the influences of our friends, family, ourselves on our decisions.The third factor value is a new entry (as it was not present in the researchers model) and it might characteristic of the German market. It consider the overall performances of the business in different areas, such as product performances, innovation etc.The fourth factor represents the opportunities available at the firm in terms of training, international learning, talent development.
The model provided a base of comparison between the firms and from the results it was clear that Deutsche Bahn is performing poorly on the Company Value dimension and Social Value dimension. Thus showing the measurement potential of the model. Of course, these data should only be considered when assessing engineering student perceptions.
To provide further model testing a multiple regression model was built and the four factors were regressed against the willingness to start a career at one of the studied firms. The results showed a strong positive relationship and in the case of Deutsche Bahn 80 % of the variance was explained. By observing the table in Appenix III it is also possible to see that the most influential factors on the model in this case is the Social Value component.
The model was also built on PLS by using structural equation modeling and by using a reflective measurement in order to facilitate validity tests. The results can be observed in Appendix II and as it is possible to notice the model fit completely and thus confirm our exploratory analysis.
Based on the previous score and by research in the field of employer branding our team came up with a series of step by recommendations for the client. The previous model showed that DB was scoring poorly in two areas Social Value and Company value. The regression analysis showed also that Social Value plays an important role in engineering students mind. Thus, our team look at models that could improve performance in that area. Based on that, the integrated brand manage the integrated brand management experience of Mosley and the application of a strategic framework that will be explained in slide 33 will probably help DB in performing better in those two areas (CV,SV). It was also agreed that the career website of Deutsche Bahn should contain a specific section for engineers students.Deutsche Bahn does a great work in assessing employee satisfaction on a two year basis through questionnaires and base board directors salary on the results of this questionnaire. On the other hand, Ritson 2013 explains that his should be conducted yearly and be based on values experience inside the company.
The integrated corporate brand: This model represent the service brand management model. Following the author ideas, this model has helped firms such as Microsoft in gaining recognition and avoid the general idea of becoming a top employer (Mosley, 2007). This model call for a more integrated approach between external marketing of the brand and internal marketing of the brand. These, approach is a more sustainable way to achieve both external and internal recognition. Thus, the application of this model could be beneficial for DB as it could improve their Social Value both internally and externally through appropriate communication and behavior. The scope of this model is also to align the employer brand to the customer brand and employer brand in order to have a clearer and more defined strategic view.
This second model is again introduced by Mosley (2007). This model emphasize that an employer brand must be both distinctive and consistent and this set can help firms in developing both a consistent brand through touch points (established rituals) and the HR functions and both by aligning all its strategic objectives. In this way, DB will be able to attract the right kind of people and at the same time enforce the right type of culture. This must be part of the integrated process and the right application of these models can lead at a better scope and at a more sustainable development than just being the top employer of Germany.
This model was researched through a more qualitative approach and thus, it can be considered a good addition to the frame built by this study. Furthermore, it provides a good framework for developing a good SV score at Deutsche Bahn.Communication Breakdown: A company with a good employer brand that does not manage to attract candidates as it wants. This might be due to communication problems at a corporate level. Introduce a strategic integrated approach to communication might help DB in communicating better its employer brand and achieve its scope. Strategic mismatch: It attracts the right type of employees but it fails in delivering its values promises to these employees.Sustained Success: This represents the best position to be in. As the company has a good and sustainable employer brand image Long term disconnect: This represents a company that does not have employer brand experience and it is not seen as an attractive employer.By the analysis made by the team , the position of DB should be the Communication Breakdown cell as the integration of employer brand was not clear.
Based on our findings we attempted to build a scale also for the female students. Although, the factor indicated by the analysis were four (following the Eigenvalue>1 Criterion). There was only one loading on the 4th criterion thus, we agreed that the 3 factors represent better female expectation for employer attractiveness. This could bring us back to the Ambler and Barrow theory of the three dimension. The way the factors were analysed was completely identical to the Male scale construction phases. Unfortunately the sample was not big enough for the PLS model and thus no structural equation modeling was performed.
Based on the previousmodel, this slide offers the step by step solution for female candidates. Generally, it was noticed that there is actually a physical lack of female studying engineering subjects and thus, given the low supply, it is more difficult to recruit this type of students. It was also observed that on average female students know little about the careers opportunities, culture etc. at the three firm observed in this study. Thus, making space for a chance to exploit an advantage in the market. We agreed that female interest in engineering subjects should be sparked from high school level education. Another industry that has difficulties in hiring girls is the finance industry. In the past years financial institutions have started mentoring schemes and high school conference and insight experiences that revealed to be successful. Deloitte for example started a mentoring scheme that had two successful outcomes:-Increase level of female employees at all levels-Improve brand recognition between female students and female employees in general.
This slides focus on what are the possible limitations of the models.Generally, it was difficult to verify the validity of the model (External) as it is based solely on engineering students. The context also plays a great role when testing for validityThe model is based on numerical data only and moreover it might be possible that it overgeneralize real world processes As a first time user of SPSS and of this type of research and methods it is possible that calculation and measurement errors might be present in the model.This slide also works on some of the pros previously explored by this work:The main role in Deutsche Bahn would be to help the HR function measure Employer Brand attractiveness and provide a base for future resolutions in employer brand integration.
Further analysis on the product correlation and willingness to apply for one of the firms was conducted and it seems that there is a relationship between these two variables as the SPSS document reveals. Product performance was part of the Company Value construct and thus it might be useful improve also this aspect of the construct in order to engage more engineering students.
Anova analysis has been applied in order to determine clear differences between male and female dataset. Surprisingly the areas studies did not show any significant difference especially for career making and salary expectations.
Valor (2009) explains how digital tools can help firms in improving their reputation once damaged. The author also explains that a clear strategy is needed to improve clarity between firms and major stakeholders. As argued before in this work. It is believed that communication strategy for DB should be revisited in order to take advantage of communication gaps in the industry.Most of the recommendations touched here were previously discussed and the last two slides should be treated as a summary.
This slide provide ideas for further research at DB. It could be used as a base for model evaluation and further application in different contexts.
