KNOWLEDGE MANAGEMENT IMPLEMENTATION UTILIZING THE
DAILY EXERCISE FOR EMPLOYEE (DEEP46) AT BANK BNI
Abdi Setia
Arief Putra1, Achmad Fajar
Hendarman2
Institut Teknologi Bandung
abdi_putra@sbm-itb.ac.id, achmad.fajar@sbm-itb.ac.id
Abstract
In line with the company's vision,
where through BNI Corporate University it seeks to create a world-class
learning entity, transformation is needed to change the mindset and behavior of
BNI people in learning. Currently, the value of implementing knowledge management
at BNI is faster, better, cheaper, wider. The application of knowledge
management at Bank BNI has an important value in business continuity. The
application of knowledge management can accelerate every development of incoming
information, create new innovations, and increase the efficiency of business
processes at Bank BNI. One of the implementations of knowledge management at
Bank BNI is creating a culture of learning and sharing. Of course, learning and
sharing activities are recognized (recorded), appreciated, and assessed in
determining the Tallent Classification of each BNI
employee (commonly called BNI Hi-Movers). One of the tools for implementing
knowledge management that runs at Bank BNI is BNI DEEP46 (Daily Exercise for
Employee Program). Where every day BNI Hi-Movers receive material in the form
of a bite-sized learning method and there are quizzes to answer. Every 1
question is recognized as 5 minutes of learning time. In the implementation of
BNI DEEP46 it can be seen that the implementation results are not optimal.
There are still many BNI Hi-Movers who do not carry out the obligation to carry
out BNI DEEP46 work. In the data presented there was a decrease in participants
(employees), from 26,885 employees to only 24,611. As of December 2021, the
number of employees is 27,085 people. This means that compulsory learning has
not met 100% as expected by BNI management. In evaluating the effectiveness of
implementing BNI DEEP46, researchers used the APO (Asian Productivity
Organization) KM Assessment Tool. The 7 element components will be combined in
the form of a questionnaire. The maximum score is 210, and there are 42 questions
covering the seven audit areas. There is a maximum possible score of 30 points
in each section. Each item can be assigned a rating between 1 (poorly or not at
all) and 5 (very well) (very well). Primary data was collected using a
questionnaire then SPSS Statistical Software version 26 was used to analyze the
data. From the results of the study it can be concluded that the Leadership
variable (X1) has no influence on the outcome, and also the People variable
(X3) has no influence on the outcome, this is indicated by the sig. 0.521 and
0.234 <0.05 which means that the leadership and people variables have no
influence on the outcome. For process, technology, knowledge process and
learning variables, they have a positive and significant influence on the
outcome, which can be seen from the significance value of each variable
<0.05.
Keywords: knowledge
management, BNI DEEP46, APO (Asian Productivity Organization).
Introduction
Background
Knowledge Management (KM) is a systematic effort to make
information and knowledge evolve, flow and create value. Efforts to optimize
Knowledge Management in an organization result in:
●
Precise knowledge
●
Can reach people who need it
●
To take action at the right time
On the basis of the 3 components above make optimal performance. In implementing Knowledge Management at BNI Corporate University, the Knowledge Management Life Cycle can be explained as follows:
To store knowledge documents that are not updated Distribute knowledge
to BNI personnel Structured, systematic,
easy & faster access • Increasing the capability of BNI personnel to achieve
efficient and effective performance • Gain knowledge for innovative & appropriate
solutions at work • The process of
learning from the experiences of others (BNI Expert Locator) • Gaining New
Knowledge • Sources for
making studies & research • Implementation of
periodic knowledge reviews by involving committees • Changing
knowledge from tacit form to explicit • The source of
knowledge comes from the BNI ecosystem • Screening &
Validation by committee • Implementation by
all BNI High Mover A network system
for storing knowledge with structured management
Figure 1. KM Life Cyle
BNI Corporate University
Company Profile
Bank Negara Indonesia (Persero) Tbk
BNI is one of the oldest commercial banks in the history of
the State of Indonesia. This bank was established on July 5, 1949 as the
central bank and in 1968, BNI was designated as “Bank Negara Indonesia 1946”,
and its status became a State-Owned Commercial Bank.
BNI Corporate University
In conducting this research, the
discussion focuses more on activities in the BNI Corporate University unit. One
of the organization's strategic engines that integrates all "Learning
Resources, Process & People" within the company, to improve performance
through increasing the knowledge, skills & attitudes/beliefs of each
individual in the "business eco-system".
BNI Corporate University Organizational Structure
Figure 2. BNI Corporate University Organizational
Structure
Business Issue
Based on
discussion with Deputy Division Head of Learning Experience & Operations,
BNI Corporate University has problems in the effectiveness of Learning &
Sharing Activity. The first step in prioritizing problems is by measuring the
level and weight of the problems from the largest to the smallest. As for the
method I did using the Kepner Tregoe method.
Table 1 Kepner Tregoe Knowledge Management Tools BNI
|
Problem |
Timing (H,M,L) |
Trend (H,M,L) |
Impact (H,M,L) |
Next
Process |
|
Effectiveness of BNI MoRe UnLeash |
L |
L |
M |
PA |
|
Effectiveness of DEEP46 |
M |
H |
H |
DA/PPA |
|
Effectiveness of Learning
Point |
L |
L |
M |
PA |
|
Effectiveness of Assignment |
L |
L |
M |
PA |
|
Effectiveness of
Appreciation & Motivation Awards for Learning Resources & Learner |
L |
L |
M |
PA |
The Effectiveness of Daily Exercise
for Employee Program (DEEP) to define new business strategic plan.
Table 2 5W 1H BNI DEEP46
Daily Exercise for
Employee Program (DEEP46)
|
What |
When |
Who |
Why |
Where |
How |
|
Program to encourage employees to always improve their competence through “bite sized learning” and daily tests |
Every weekday, open from 00:00 – 19:00 WIB |
All BNI employees who meet the criteria for their unit |
All employees must continue to improve their capabilities to support Person Value |
Wherever the employee is |
Accessed via BNI Smarter or digiHC max 5 Deep46 a day |
To especially assign business environment analysis according the scope of my business
issue, proposed to use fishbone approach
/ Ishikawa Diagram:
No one has filled
the KM manager position yet. Awareness is still
lacking for leaders to evaluate Lack of variety of
questions Not all inline with employee competence The question data
is not evenly distributed, it only focuses on several aspects. Coordination
between work unit divisions and BNI Corpu is not
optimal Learning culture is
carried out every day using the application KM Methode DEEP 46 employment
is still low, below 50% of total employees Lack of
understanding of the essence of working on DEEP 46 Work reports are
not updated regularly Questions from DEEP
46 are always repeated, not updating BNI Smarter
Application and Digi HC via Apps Store / Android Not all layering
employees understand IT / applications Learning Point
Figure 3. Ishikawa Diagram BNI Deep 46
The context of my business problem, especially in BNI DEEP46, I
use cause mind mapping to explain the problem, including:
The 5 Whys
:
Figure 4. The 5 Whys BNI Deep 46
Cause Map Diagram
Figure 4. Cause Map Diagram DEEP 46
Evaluation of the Daily Exercise for Employee Program
(DEEP46)
Evaluation is
usually preceded by a question about how well a particular design or aspect
meets the user's needs. In this case the use of the Daily Exercise for Employee
Program (DEEP46) for all BNI employees. The perspective of evaluating an
interaction design will result in a different way of testing. The interaction
design evaluation paradigm consists of: (i) 'quick
and dirty', (ii) usability testing.
‘Quick and Dirty’
Evaluation
Quick and
dirty evaluations are feedback in the form of wishes and preferences from users
(BNI employees) or consultants that are conveyed informally to designers about
the products they make. This evaluation can be carried out at all stages of
product manufacture and the emphasis is on quick/shortest possible input rather
than carefully documented findings.
Usability Testing
Usability
testing involves measuring the user's performance in preparing their tasks
carefully. It is from this process that the system design is created.
Performance is generally measured in the number of errors made and the time
required to complete the task [4]. The method that is generally used to create
this system is by: (1) Seeing directly; and (2) Record it on video.
This evaluation uses
questionnaires and FGD (Focus Group Discussion)
with users about how effective BNI DEEP 46 is at present and for
future improvements. Questions prepared using APO as one of the KM tools in
finding the most critical aspects of the problem. The current problem is based
on the data I obtained, where based on data obtained in the last 2 years
(2020-2021) there is a decrease in the work of DEEP 46 by employees. Attached is
a graph of employee progress in working on the DEEP 46 application. Based on
data obtained in the last 2 years (2020-2021) there is a decrease in the work
of DEEP 46 by employees. Attached is a graph of employee progress in working on
the DEEP 46 application.
In the graph beside, there is
a decrease in participants (employees), from 26,885 employees down to only
24,611. In December 2021 the total number of employees was 27,085. This
means that mandatory learning has not met 100% as expected by BNI
management.
Figure
3. Graphic Participants
Method
Research Design
The design of this study was to test the accuracy of the APO
framework used to answer research questions related to Knowledge Management (Blumberg,
n.d.). This research was conducted to
determine the effectiveness of the Deep 46 BNI application on employee
competency at PT Bank Negara Indonesia.
Figure 3.Research Design BNI DEEP 46
Data Collection Method
Data Collection
This study uses a sampling technique that is purposive
sampling. Purposive sampling is a sample selection technique from cases that
match the criteria set by the researcher (Onwuegbuzie
& Collins, 2017). Data collection in this study was
carried out by distributing questionnaires to respondents via the internet
(online) using Google Docs media to increase the response rate or assessment of
the variables studied. The variables used are using the APO KM Tool. The
questionnaire contains variable statements which are analyzed using a measurement
scale with a value of 6 points. According to (Baxter,
Joseph, Osborne, & Bedecarrats, 2014), the minimum sample size must be
100. The data collection procedure was carried out from 21 November 2022 to 25
November 2022, using a Google form for five days.
Participants
The target respondents of this study were current Bank BNI
employees who work as permanent employees in 6 regions throughout Indonesia.
This is done to see the equality of respondents to the implementation of BNI
DEEP 46 in each region. Another supporting factor is to see the effectiveness
of BNI DEEP 46 in each region towards the work culture that has been formed.
The author uses Google Forms to submit questionnaires and WhatsApp groups to
convey information. This survey was attended by 100 respondents from business and
support units from 6 BNI regional offices.
Results and Discussion
This chapter describes
the results of distributing questionnaires related to the data description and
presents the results of regression testing. In the description of the data, the
discussion includes descriptive statistical analysis, which explains the
characteristics of the data. Next is the testing of the validity and
reliability of the research indicators, and the last one is explaining the
suitability of the model along with testing the research variables.
Analysis
Respondent Graphic Information
This study distributed questionnaires to 6 working areas of PT Bank
Negara Indonesia throughout Indonesia with total 130 respondent with the
following composition of respondents showed on figure xx.
Respondents in this study are scattered in various work areas
of PT Bank Negara Indonesia throughout Indonesia. The area is divided into W02
(Riau/West Sumatra) with 25% (32 people), W08 (Bali, NTT, NTB) with 21% (27 people),
W09 (Banjarmasin/Kalimantan) with 15% (20 people), W11 (North Sulawesi,
Southeast, Maluku) as much as 12% (16 people), W15 (Jakarta Kemayoran)
as much as 15% (15 people) and W16 (Papua) as much as 12% (16 people).
To
better understand the results of the questionnaire more clearly, from each variable
and statement, the following are the results of the questionnaire per variable.
Leadership
Figure 5 Decsriptive
of Leadership
The average score for the leadership variable is 4,93. Based on the data
above, it can be seen that only questions 1, 2, 3 and 4 have scores above the
average score for the leadership variable, while questions 5 and 6 have scores
below the average score for the leadership variable. Question 5 is "Unit leaders spend more time socializing SOP
DEEP 46 to staff" and
question 6 is "Management
promotes, recognizes and rewards performance improvement, organizational and
employee learning, shares SOPs related to the implementation of DEEP 46".
Figure 6 Descriptive of Process
The
average score for the process variable is 5,10. Based on the data above, it can
be seen that questions 3, 4, 5 and 6 have scores above the average score for
the process variable, while questions 1 and 2 have a score below the average
score for the process variable. Question 1 is " BNI 46 defines important front-line
capabilities that provide competitive advantage and aligns them with the
company's strategic mission and goals", question 2 is "BNI 46 designs work systems and key processes to achieve performance
excellence related to SOPs in DEEP 46".
Figure 7 Descriptive of People
The
average score for the people variable is 5,06. Based on the data above, it can
be seen that questions 1, 3 and 5 have a score above the average score for the
people variable, while questions 2, 4 and 5 have scores below the average score
for the people variable. Question 2 is “BNI 46 has a systematic onboarding process for new employees that
includes an overview of the SOP system, tools, and benefits.”, question 4 is “BNI 46 has an updated staff assessment
database regarding SOPs”,
and question 5 is “SOP knowledge
exchange and cooperation are aggressively encouraged and rewarded.”.
Figure 8 Descriptive of Technology
The average score for the technology variable is 5,25. Based on the data above, it can be seen that questions 1, 3, and 5 have scores above the average score for the technology variable, while questions 2, 4 and 6 have scores below the average score for the technology variable. Question 2 is "IT infrastructure at BNI 46 is aligned with the implementation of the SOP system" and question 4 is "Everyone has internet/intranet access and an email address." and question 6 is “To facilitate the transmission or sharing of SOPs, an intranet (or similar network) is employed as the primary means of communication within the business.”
Knowledge Process
Figure 9 Descriptive of Knowledge
Process
The average score for the knowledge
process variable is 5,18. Based on the data above, it can be seen that questions
1, 2 and 6 have scores above the average score for the knowledge process
variable, while questions 3, 4, and 5 have scores below the average score for
the knowledge process variable. Question 3 is “Knowledge gained from completed tasks or projects (branch
investigations, branch issues) is documented and shared with all workers”, question 4 is “Critical knowledge regarding employees
departing the organization is kept”, and question 5 is “BNI 46
communicates best practices and learning (branch investigations, branch issues)
with the rest of the company so that there is no continual and static
wheel-reinvention or duplication of effort”.
Learning
Figure 10 Descriptive of Learning
The average score for the learning
variable is 5,11. Based on the data above, it can be seen that questions 1, 3,
4 and 5 have scores above the average score for the learning variable, while
questions 2 and 6 have scores below the average score for the learning
variable. Question 2 is "BNI
46 considers taking risks or making mistakes related to SOPs as learning
opportunities as long as they don't happen repeatedly" and question 6 is "Workers are given incentives to work
together and share related SOPs, especially DEEP 46".
Outcome
Figure 11 Descriptive of Outcomes
Average score for variable outcomes
is 5,12. Based on the data above, it can be seen that questions 2, 4 ,5 and 6
have scores above the average score for variable outcomes, while questions 1
and 3 have scores below the average score for variable outcomes. Question 1 is
“BNI 46 has a history of
effectively implementing SOP systems and other change efforts, and continues to
do so.”, question 3 is “BNI 46 has increased its productivity as a
result of decreased cycle times, greater cost savings, increased effectiveness,
more efficient utilization of resources (including SOP systems), and improved
decision-making.”.
Outlier, Classic Assumption, Validity and Reliability Test
Outlier Test
(Ghozali,
2018) states that outliers are data with
unique characteristics that look very different from other observations and
appear in extreme values for either a single variable or a combination
variable. Before proceeding to the following process. It is a good idea to
detect outliers. Data containing outliers are not included in the processing of
this study. This step was done with the intention that the final results of
this research really fit the research needs. Based on the results of the outlier
test, there are 14 samples that have a z-score range beyond -4 to 4 namely,
(samples 4, 18, 19, 29, 50, 60, 70, 74 85, 93, 108, 123, 124 and 128) so that
these values are said to be outliers and must be removed from the data.
Classic Assumpiton Test (Normality)
According to (Ghozali,
2016), the normality test aims to test
whether the residual variables have a normal distribution in the regression
model. The normality test can be done through graphical analysis and
statistical tests. Researchers choose statistical tests to look at the level of
normality of research data using the One-Sample Kolmogorov-Smirnov Test. The
selection of the normality test using the Kolmogorov-Smirnov test is because the
Kolmogorov-Smirnov test is used in studies with more than 100 samples. besides
that, in this study, the researcher uses a p-value compared to α so that
the Kolmogorov-Smirnov test is suitable for use
in this research.
Table 3 One- Sample
Kolmogorov-Smirnov Test
|
|
Unstandardized
Residual |
|
N |
120 |
|
Kolmogorov-Smirnov Z |
0,096 |
|
Exact Sig. (2-tailed) |
0,205 |
Table 4.1 above is a data
normality test using the one-sample Kolmogorov-Smirnov (K-S) non-parametric
statistical test. The data is said to be normal if the exact value. Sig is more
significant than 0.05, which states that the normality assumption is fulfilled.
Based on the table 4.1 it can be seen that the exact value. The residual
variable sig is more significant than 0.05, namely 0.205, which means that
there is no significant difference between the data tested and standard normal
data, and it can be concluded that the data in this study fulfill the normality
assumption test.
Validity Test
Validity testing is
carried out to know the accuracy of a measuring instrument used (Blumberg,
n.d.). This technique aims to test whether
each item can reveal the factor to be measured or the internal consistency of
each measuring instrument item in measuring a factor. The technique used for
the validity test in this study was Pearson Product Moment. The correlation
value obtained is then compared with the correlation value table (r) Product
Moment to determine whether the correlation value obtained is significant or
not. If the index value obtained from the calculation is greater than the value
of the correlation table (R count > R table), the item is declared valid and
vice versa. The following below are the results of validity test using pearson’s correlation on each research variable.
Table 4 The Results of Validity
|
Variable |
Item |
R count (Pearson Correlation) |
R table (N=120 a=5% two tail) |
Description |
|
Leadership (X1) |
X1.1 |
0,514** |
0,1779 |
Valid |
|
|
X1.2 |
0,741** |
0,1779 |
Valid |
|
|
X1.3 |
0,647** |
0,1779 |
Valid |
|
|
X1.4 |
0,691** |
0,1779 |
Valid |
|
|
X1.5 |
0,569** |
0,1779 |
Valid |
|
|
X1.6 |
0,706** |
0,1779 |
Valid |
|
Process (X2) |
X2.1 |
0,776** |
0,1779 |
Valid |
|
|
X2.2 |
0,791** |
0,1779 |
Valid |
|
|
X2.3 |
0,742** |
0,1779 |
Valid |
|
|
X2.4 |
0,819** |
0,1779 |
Valid |
|
|
X2.5 |
0,778** |
0,1779 |
Valid |
|
|
X2.6 |
0,706** |
0,1779 |
Valid |
|
People (X3) |
X3.1 |
0,786** |
0,1779 |
Valid |
|
|
X3.2 |
0,854** |
0,1779 |
Valid |
|
|
X3.3 |
0,794** |
0,1779 |
Valid |
|
|
X4.4 |
0,796** |
0,1779 |
Valid |
|
|
X5.5 |
0,722** |
0,1779 |
Valid |
|
|
X6.6 |
0,722** |
0,1779 |
Valid |
|
Technology |
X4.1 |
0,783** |
0,1779 |
Valid |
|
|
X4.2 |
0,871** |
0,1779 |
Valid |
|
|
X4.3 |
0,808** |
0,1779 |
Valid |
|
|
X4.4 |
0,811** |
0,1779 |
Valid |
|
|
X4.5 |
0,726** |
0,1779 |
Valid |
|
|
X4.6 |
0,833** |
0,1779 |
Valid |
|
Knowledge Process (X5) |
X5.1 |
0,729** |
0,1779 |
Valid |
|
|
X5.2 |
0,783** |
0,1779 |
Valid |
|
|
X5.3 |
0,703** |
0,1779 |
Valid |
|
|
X5.4 |
0,720** |
0,1779 |
Valid |
|
|
X5.5 |
0,767** |
0,1779 |
Valid |
|
|
X5.6 |
0,781** |
0,1779 |
Valid |
|
Learning (X6) |
X6.1 |
0,835** |
0,1779 |
Valid |
|
|
X6.2 |
0,660** |
0,1779 |
Valid |
|
|
X6.3 |
0,812** |
0,1779 |
Valid |
|
|
X6.4 |
0,771** |
0,1779 |
Valid |
|
|
X6.5 |
0,736** |
0,1779 |
Valid |
|
|
X6.6 |
0,711** |
0,1779 |
Valid |
|
Outcome (Y) |
Y1 |
0,776** |
0,1779 |
Valid |
|
|
Y2 |
0,767** |
0,1779 |
Valid |
|
|
Y3 |
0,825** |
0,1779 |
Valid |
|
|
Y4 |
0,815** |
0,1779 |
Valid |
|
|
Y5 |
0,830** |
0,1779 |
Valid |
|
|
Y6 |
0,820** |
0,1779 |
Valid |
From the table above, it can be seen
that all items' questionnaire's value are greater than
r table with N=120 0,1779 which means that all the items used in this study are
valid.
Reliability Test
After conducting validity, the next
test that is carried out is the reliability of the measurement indicators in
the study. According to (Ghozali,
2018), reliability is carried out to
determine the stability of respondents' answers to measurement tools from time
to time. In this study, reliability testing was carried out by looking at the
value of Cronbach's alpha or the value of the composite reliability
coefficient. The reliability test is achieved if the Cronbach's alpha value or
composite reliability value is greater than 0.7 for all constructs (Latan
& Ghozali, 2012).
Table 5 Reliability Statistic
|
Reliabiality Statistic |
|
|
Cronbach’s Alpha |
N of Items |
|
0,970 |
42 |
Based on the reliability test results
in the table above, the Cronbach's alpha value for each variable is above 0.6
and it can be concluded that the measurement indicators in this study are
reliable so that they are feasible for further testing.
Multiple Regression Analysis Method
Multiple Linear Regression Analysis
MRA is an analysis that
aims to predict how much influence one or two independent (independent) variables
have on one dependent (dependent) variable. In this research, multiple
regression analysis will describe the effects of the following variables (leadership,
people, process, technology, knowledge process, and learning) toward
implementing DEEP 46 in improving employee’s competency (Serenko
& Dumay, 2017).
Individual Parameter Significance Test (Statistical T Test)
According to (Ghozali,
2018) the t-statistical test shows the
effect of one independent variable individually in explaining the variation of
the dependent variable. The t-test is, known as the partial test, used to test
the independent variables independently of the dependent variable (Hair,
2010). Significance in the t statistical
test can be seen in two ways, namely the first by using the significant value
in the coefficients table. If the significance value is less than 0.05, then
the independent variable affects the dependent variable, and if the
significance value is greater than 0.05, the independent variable does not
affect the dependent variable. The second is to compare the t count with the t
table. If the value of the t count is greater than the t table, then the
independent variable has an effect on the dependent variable; conversely, if
the t count is less than the t table, then the independent variable does not
affect the dependent variable.
Table 6 R Square, F Statistic, F
table
|
|
Outcome |
|
Adj R Square |
0,899 |
|
t table |
1,984 |
|
Sig. t. |
0,00 |
Table 7
Multiple Regression Analysis
|
Independent Variable (X) |
Dependent Variable (Y) |
Adj R2 |
Beta |
t statistics |
t table |
Sig. t |
|
Leadership (X1) |
Outcome (Y) |
0,899 |
0,026 |
0,644 |
1,984 |
0,521 |
|
Process (X2) |
Outcome (Y) |
0,899 |
0,124 |
2,238 |
1,984 |
0,027 ** |
|
People (X3) |
Outcome (Y) |
0,899 |
0,075 |
1,197 |
1,984 |
0,234 |
|
Technology (X4) |
Outcome (Y) |
0,899 |
0,160 |
2,952 |
1,984 |
0,004*** |
|
Knowledge Process (X5) |
Outcome (Y) |
0,899 |
0,321 |
4,308 |
1,984 |
0,000*** |
|
Learning (X6) |
Outcome (Y) |
0,899 |
0,341 |
5,121 |
1,984 |
0,000*** |
From the result of multiple
regression analysis test, it can be concluded that as follows:
- Table
4.3 shows the adjusted r square value of 0.899 or equal to 89.9% which
means that the variables of leadership, process, people, technology, knowledge
process and learning have an effect on outcomes of 89.9% while for the
remaining 10.1% it is influenced by other variables outside the model.
- Individual
Parameter Significance Test (T-test) were used in this research and there
are four variables that has a significant affect to outcome. It can be
seen from the significant t value that they have is less than á = 0,05 and the Beta value are positives, the greater
one’s knowledge process or learning the higher employee’s competence will
be. This means that the when employee’s knowledge process or learning on
DEEP 46 at PT BNI increases, the employees’ competence will also increase
32,1% and 34,1%, respectively.
- From
the table above can be seen that there are two independent variables that
has sig t value greater than á = 0,05, Leadership (X1) and People (X3)
which means
they did not have a significant effect on outcome. This means that Leadership
and People are not the main factors that affect employee’s competency
improvement through BNI DEEP 46. This means that in this study, not all input
from KM affects outcome.
Focus Group Discussion
The researcher conducted a
Focus Group Discussion to find out more about the views of the respondents
regarding important matters and issues related to BNI Deep 46. This FGD was
attended by 14 people from 6 Working Areas of PT. BNI throughout Indonesia.
Furthermore, the results of this FGD will be used as a reference for
determining implementation and business solutions.
Table 8 Main Issues in Leadership
|
|
Leadership |
||
|
No |
Issues |
Total |
|
|
Most Important |
Most Problematic |
||
|
1 |
Branch leaders have not encouraged employees to fill in BNI Deep 46. |
10 |
5 |
|
2 |
Regional leaders do not use the BNI DEEP 46 Dashboard as evaluation material for decision making. |
14 |
11 |
|
3. |
Branch leaders have an important role in the realization of BNI Deep 46 filling |
8 |
13 |
|
4. |
Regional leaders carry out routine evaluations regarding BNI Deep 46. |
12 |
10 |
|
5. |
Regional leaders must improve the system for making questions at Bni Deep 46. |
11 |
10 |
|
6. |
Regional leaders must use BNI Deep 46 as a KPI for mandatory activity. |
12 |
9 |
|
7. |
BNI Deep 46 is a tool that can increase employee competency. |
8 |
7 |
Based on the table above, the 10
issues in Leadership, there are 2 issues that respondents consider very
important and are currently a problem in implementing the BNI Deep 46 application. The two issues include:
- Regional
leaders do not use the BNI DEEP 46 Dashboard as evaluation material for
decision making. (14/11)
- Regional
leaders carry out routine evaluations regarding BNI Deep 46. (12/10)
As for some issues that have been
considered good by respondents, including:
- Branch
leaders have not encouraged employees to fill in BNI Deep 46. (10/5)
- Branch
leaders have an important role in the realization of BNI Deep 46 filling.
(8/13)
- Regional
leaders must improve the system for making questions at Bni Deep 46. (11/10)
- Regional
leaders must use BNI Deep 46 as a KPI for mandatory activity. (12/9)
- BNI
Deep 46 is a tool that can increase employee competency. (8/7)
Table 9 Main Issues in People
|
No |
Issues |
Total |
|
|
Most Important |
Most Problematic |
||
|
1 |
It is difficult to access the information or knowledge needed regarding the Bni Deep 46 application for new employees |
8 |
6 |
|
2 |
Dependence on certain employees. |
5 |
8 |
|
3. |
Employee awareness to fill in BNI Deep 46 |
10 |
4 |
|
4. |
Employee difficulties in answering BNI Deep 46 questions |
11 |
13 |
|
5. |
Giving rewards that are given does not motivate employees to fill in Deep 46 |
10 |
7 |
|
6. |
Punishment is not implemented for employees who do not fill in BNI Deep 46 |
9 |
6 |
|
7. |
Employees do not get an evaluation regarding filling in BNI Deep 46 |
14 |
12 |
|
8. |
Flexibility when working on BNI Deep 46. |
5 |
3 |
|
9. |
Employees do not have confidence in filling out BNI Deep 46. |
3 |
11 |
|
10. |
The Deep 46 application user interface is still not optimal. |
2 |
2 |
Based on the results of the FGDs that
have been conducted, of the 10 issues in People, there are 3 issues that
respondents consider very important and are currently a problem in implementing
the BNI Deep 46 application. The three issues include:
- Employee
difficulties in answering BNI Deep 46 questions. (10/12)
- Giving
rewards that are given does not motivate employees to fill in Deep 46.
(10/7)
- Employees
do not get an evaluation regarding filling in BNI Deep 46. (14/12)
As for some issues that have been
considered good by respondents, including:
- It
is difficult to access the information or knowledge needed regarding the Bni Deep 46 application for new employees. (8/6)
- Dependence
on certain employees. (5/8)
- Employee
awareness to fill in BNI Deep 46. (10/4)
- Punishment
is not implemented for employees who do not fill in BNI Deep 46. (9/6)
- Flexibility
when working on BNI Deep 46. (5/3)
- Employees
do not have confidence in filling out BNI Deep 46. (3/11)
- The
Deep 46 application user interface is still not optimal. (2/2)
Business Solution
Based
on the results of this study, it is known that the process, technology,
knowledge process, learning are the variables that have a positive and
significant impact on outcomes. Improvements to these four variables will have
a positive impact on outcomes. Knowledge management
is the answer to every human resource development. In an organization, through
the authorization and development of the organization, information and
knowledge are converted into decision-making capital and employee learning. Edvarson & Oscarsson's
research (2013) proves that organizations that adopt knowledge management plans
and processes have improved employee skills and enabled employees to make
better decisions compared to other organizations (Hendarman & Cantner, 2018). Implementation of knowledge management is expected not only
to be a model in management; if it is implemented effectively, properly, and
correctly, it will significantly impact organizational outcomes (Awad, 2007). However, based on the
tests that have been carried out, the two variables, namely leadership and
people have not been shown to improve the outcomes of PT BNI employees.
Knowledge
Management is conveying the right knowledge to the right people at the right
time with the right combination of abstracts and a series of activities to
achieve organizational goals (Szakaly, 2002). In
practice, filling in BNI DEEP 46 aims to increase employee competence by
filling in daily activities found on applications and websites. Employees are
guided to fill in 5 questions that do not only focus on their job description
or part of the organization. For example, a BNI Bank CS works on questions that
are not in accordance with the CS job description but must answer questions
related to the credit analyst job description. In addition, the work results
from the beginning of DEEP 46 was present until now have never been evaluated
in the sense that top management did not take effective steps to increase the
effectiveness of BNI DEEP 46 implementation. This is
what causes Input (People) in Knowledge management cannot affect the outcome of
employees at PT BNI.
Conclusion
Knowledge is important for companies,
without knowledge the organization has to try extra hard to encourage resources
/ members of the new organization who quickly have to be able to explore the
culture, ways of working and everything related to the job. KM that is well
managed, can ensure that knowledge is available for new members of the
organization to learn so that it can help them carry out their job desks or to
be traced to find best practices that are available and have been done before,
or encourage members of the organization to find new or best knowledge. the
latest practice for the company.
This study examines the effect of
knowledge management on employee outcomes at PT BNI. The results of the study
found that process, technology, knowledge process and learning had a positive
effect on the outcome. While the other two variables, namely people and
leadership, do not affect employee outcomes
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