CIPD Data Analysis: Impact of Brexit on Organisation

Report
(CIPD data analysis)

Contents
INTRODUCTION...........................................................................................................................................3
ANALYSIS.....................................................................................................................................................3
Question 1...............................................................................................................................................3
Highlight interesting findings................................................................................................................12
Recommendation to government about the possible impact of Brexit and the proposed new
immigration system on organisation......................................................................................................13
CONCLUSION.............................................................................................................................................14
REFERENCES..............................................................................................................................................15

INTRODUCTION
The method of gathering, modelling, and evaluating data in order to extract information that
aid decision-making is known as data analysis. Depending on the sector and the goals of the
research, there are a variety of approaches and strategies for conducting it. Developing a broader
understanding of various data collection approaches, as well as qualitative and qualitative
processes (Billing, McCann and Ortega-Argilés., 2019). This would offer the data analysis
activities a more well defined path, so it's usually a good idea to soak up this specific expertise.
In addition, there will be able to generate a powerful analytics report which will speed up your
research. Fortunately, key facets of the potential construction, such as consumer entry, which
accounts towards 80% of either the U.K. market, currently unclear. This prevented a “no-deal”
Brexit that may have been costly for the domestic economy. This article is focused on a study of
the employers and employees after Brexit and how it affected both. In addition, make proposals
for the organization's immigration scheme.
ANALYSIS
Question 1
Sector Private sector
organisation size
Privat
e
sector
Publi
c
secto
r
Third/
voluntar
y sector
Private
sector
SME
(2-249)
Private
sector
large
(250+)
A B C J K
Q1. Does
the
organisati
on
planning
to recruit
employees
in the next
THREE
months? Mean
Mo
de
Media
n
Standard
deviatio
n
Unweighte
d base 1433 427 193 781 652 3486
#N/
A 652
468.426
3
Base 1560 349 144 708 852 3613
#N/
A 708 546.02
Yes 532 217 63 150 382 1344 #N/ 217 187.908

A 8
No 869 94 70 498 371 1902
#N/
A 371 328.261
Don't
know 159 38 11 60 99 367
#N/
A 60
57.6827
5
1 2 3 4 5
0
200
400
600
800
1000
1200
1400
1600
1800
1433
427
193
781
652
1560
349
144
708
852
532
217
63 150
382
869
94 70
498
371
159
38 11 60 99
Q1. Is your organisation
planning to recruit
employees in the next
THREE months?
Unweighted base
Base Yes
No Don't know
Interpretation: As according to graph above, however many businesses expect to hire
new employees over the next 3 months in various industries such as private and public sectors.
The average, modal method, medium values as well as standard deviation was used to determine
the outcomes (Brown, Liñares-Zegarra and Wilson,, 2019). Based on these findings, determine
which sectors intend to add new talent, while the United Kingdom faces several challenges
following Brexit.
QE1. In the
past 3
years, has
your
organisatio
n employed
people
from any of
the
following
groups?
Please tick
all that
Priva
te
sector
Publi
c
secto
r
Third/
volunt
ary
sector
Privat
e
sector
SME
(2-
249)
Private
sector
large
(250+)
Mean Mo
de
Media
n
Standard
deviation

apply.
Un-
weighted
base
1433 427 193 781 652
3486
#N/
A 652 468.4263
Base 1560 349 144 708 852 3613
#N/
A 708 546.02
People aged
50-64 1024 257 112 397 627 2417
#N/
A 397 356.9066
People aged
65 and
above
467 128 62 139 328
1124
#N/
A 139 167.74
People with
a disability
or long-term
health
condition
656 216 91 176 479
1618
#N/
A 216 235.6402
People from
a Black,
Asian or
minority
ethnic
background
853 247 98 238 615
2051
#N/
A 247 312.958
People aged
19-24 with
few or no
qualification
s
883 207 77 306 577
2050
#N/
A 306 321.9208
People aged
16-18 with
few or no
qualification
s
477 121 43 133 345
1119
#N/
A 133 180.486
Ex-
offenders 206 69 25 44 162 506
#N/
A 69 78.73182
Parents
returning to
the
workforce
715 206 84 184 531
1720
#N/
A 206 266.8586
People
returning to
the
workforce
after time
out of the
labour
market for
500 159 63 91 409 1222 #N/
A
159 197.5824

reasons
other than
having a
child, for
example
because of
other caring
responsibilit
ies or a
health
condition
War
veterans 269 98 21 41 228 657
#N/
A 98 111.5137
None of the
above 130 10 7 114 16 277
#N/
A 16 61.14573
Don't know 136 32 5 22 114 309
#N/
A 32 59.01017
0
1000
2000
3000
4000
Private sector
Public sector
Third/voluntary sector
Private sector SME (2-249)
Private sector large (250+)
Mean
Mode
Median
standard deviation
Analysis: This graph shows how companies have chosen employees from various groups in the
last three years, such as public and corporate (large and SME). According to this study, how
many workers were working during the Brexit process, as well as how reaction that occurs in
various ways (Brownlow and Budd, 2019). The central-tendency of numerical values is
effectively numerically measured using the Mean estimation measurements method. This is the
sum of everything is equal to the main average of values. The exploratory analysis' key goal is to
discover, because as name implies. There is also no measure of the link in between data as well