Business Intelligence and Analytics in Performance Management Analysis

This report delves into the critical relationship between business intelligence (BI) and performance management. It examines how BI, supported by business analytics, enhances decision-making by leveraging key performance indicators (KPIs) and data-driven insights. The report explores the integration of BI with performance management, emphasizing the use of data to assess and improve organizational strategies, including the use of balanced scorecards and other performance measurement tools. The analysis covers the relevance of business analytics in performance management, highlighting its role in forecasting, trend analysis, and the identification of efficient decision-making variables. The report concludes that effective implementation of BI and analytics is essential for organizations seeking to improve performance, requiring careful consideration of internal and external factors as well as a supportive organizational culture to maximize the benefits of data-driven decision-making.

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1Business Intelligence and Analytics and Performance Management
Executive summary
The purpose of this report is to analyse the relationship between the performance management and
business intelligence. The next part of the essay is to analyse the relevance of Business analytics and
business Intelligence in performance management. To improve the performance the key performance
indicators are analysed and how they can be measured in help in making decisions. For the betterment
and increasing, the effectiveness of the decision-making business intelligence and analytics is needed.
Business intelligence is deriving the concepts with the business decision making and fact based support
system. Due to individualisation and globalisation of business environment, the dire need of business
analytics has increased. Considering the factors of performance drivers also equips the managers with
implementing the best outcome of taken actions in the business process.

2Business Intelligence and Analytics and Performance Management
Table of Contents
Introduction....................................................................................................................................................3
Discussion......................................................................................................................................................3
1) The relationship between business intelligent and business performance management.......................3
2) Relevance of business analytics in business performance management as well as performance
analytics.....................................................................................................................................................5
Conclusion.....................................................................................................................................................6
References......................................................................................................................................................8

3Business Intelligence and Analytics and Performance Management
Introduction
There is a significant relationship between the performance management and business
intelligence. This relationship will be established through different aspect of performance management
role in a business functions. The next part of the essay will analyse the different aspect of performance
analytics. This next hypothesis will take into account, different relevant factor of performance measure in
an organisation that leads to necessity of measuring them. The key performance indicators are to create
the portfolio of the business’s strategical improvement (Bronzo et al. 2013). The objectives, mission and
values are the focus point of creating business intelligence, which leads to business analytics. For the
betterment and increasing, the effectiveness of the decision-making business intelligence and analytics is
needed. Both of this aspect is complement of each other. Integrating business analytics with performance
calculations have become necessary to build the necessary outcome of the process. It also enables top-
level management to verify the data that supports the decision (Hazen et al. 2014).
Discussion
1) The relationship between business intelligent and business performance management
Performance management may lead to consistency in efficient and effective management. The
process is to align the enterprise strategically align the objectives and priorities. A better decision making
can be backed by the knowledge of their business. Performance can be managed by different metrics
known as key performance indicators. Thus, the improvements can be measurable adding the values in
the indicators. The cycle is to measure, the performance is planning, progress review and evaluation
(George et al. 2014).
Business intelligence is deriving the concepts with the business decision making and fact based
support system. Converting the raw data got from different sources to information that can be used in
future are the basic steps of business intelligence. Thus, the information is used in intelligence and used in
the reporting department. Whereas business analytics is evidently based in building mathematical models
through statistical analysis and predicting the future based on the historic data. Business intelligence helps
in reporting the data based on the predictive model based on interrelationships of the variables identified
(Hazen et al. 2014).
In this case, the identified variables are the different metrics of performance indicators. The
evidence based decision-making and reporting on the outcome of the performance is known as the
performance analysis. Business analysis is used in every kind of business. The function where it is

4Business Intelligence and Analytics and Performance Management
necessary are customer acquisition and customer loyalty, cross and up selling, insurance rate setting and
others, risk in fraudulent. Performance management and business intelligence complements each other.
The correlations are shown on the strategic dashboards with periodic intervals. The predictive models of
performance management, after feeding data gives output on the scales and measure the outliers in their
performance. The periodical data can also be compared with respect to improvement in the performance’s
regard. Performance management is a departmental function of human resource management. The key are
of performance indicators are performance appraisals, compensation and their implementations and
evaluation. Relevant performance information is necessary for better decision making (Waller and
Fawcett 2013).
The integrated software solutions for the support to decision making are CPM (corporate
Performance Indicators) or EPM (Enterprise Performance Management). Oracle Big data are being used
by the Pepsico, IBM, P&G, Ford, Dell. The most important part where it is being used are in enhancing
the customer relationship management (George et al. 2014).
The Business Performance management area where BI can be included are balance score cards,
quality management, and comparison between previous and current data. The measurable aspects of a
balance scorecard are measure quality of execution on periodic basis and dashboards includes visual
display of BI implementation through graphs and lights (Waller and Fawcett 2013). This may be system
generated and can reflect the result on real time information at a glance. The top down approach in
management balance scorecard combines the vision of ultimate goal by monitoring key metrics of the
financial information and growth, customer interaction and business process and operational effectiveness
The variables of that are calculated to gauge the customer satisfaction are
 Customers experience
 Loyalty
 Customer satisfaction
 Trend in visits and buying rate
On a financial perspective, the balance scorecard contains the following balancing units for measure
 Revenue growth - Shareholder value which are divide in two that are building franchise and
customers value
 Productivity growth strategy – that can be build to improve cost and asset structure
The benefits of BSC are, it drives to enhance strategy using all the components measured in BSC
dashboards. The building blocks of the framework are given emphasis in terms getting the result. This

5Business Intelligence and Analytics and Performance Management
also takes into consideration about different level of scores and integrates them for quick and visual
prediction on data (Walle and Fawcett 2013).
Managing the quality of the operations and continuously improving the performance is done
through six-sigma scorecard. Main criteria of measuring the performance are to driving for excellence
through effectiveness of operations. Thus, the performances are managed on financial perspectives.
Increasing the market share and sales volume is also part of business intelligence process.
Business analytics comes after business intelligence, as data needs to be gathered on the above-mentioned
aspects are and then information will be processed. The performance indicators metrics are decided based
on the functions that they belong to (Rausch et al. 2013).
2) Relevance of business analytics in business performance management as well as
performance analytics
Managers face problems in categorising the competitive advantage. Affectively using the
business analytics can help in decision-making. The visualisation of the performance metrics generalises
the outcome and facilitate the decision-making capability of the managers. Considering the internal and
external output of the environment can lead to betterment of the outcome. A strategic business decision
making helps in drawing conclusion, identify, and implement the alignment of the strategic goals. The
direction of the goals is directed towards the desired performance standards. Business analytics identifies
the efficient way of decision-making variables. The forecasting of sales and demand as well as analysing
the trends of the marketing, consumer behaviour gives valid insights in the problem-solving path
(Kasemsap 2015). Forecasting and predicting based on the variable on performance level are
implemented in the organisation. However, the down turn of the predicting based on the historical data
have some drawbacks but at the same time, it gives approximately close value of the variables.
Transforming the data by using the business intelligence tools like data warehousing tools,
reporting and dashboards and analytics tools are is initial stage and output are measured by the business
performance management models and dimension. Aligning the business objectives of the company with
the business process and creating BI portfolio map are used in approaching the objective (George et al.
2014).
The prospect of using analytics in planning, forecasting, budgeting to assess the soundness of the
performance is very important. To check trends, identify relationships analytics is needed. The
prescriptive data regarding any performance indicators like key performance drivers are identified in the
first essay are balance scorecard, total quality management and customer relationship management. These

6Business Intelligence and Analytics and Performance Management
ones use the business analysis of to achieve the ultimate goals. The performance analytics is used in
finding the meaning in the data that can help in forming decisions. Creating a novel insight from
statistical analysis of the dataset helps in embracing the possibilities that could not have been identified in
a manual analysis. Executive level of business analysis of optimises the business process which serves as
a asset to companies which are data driven (Kasemsap 2015).
Performance analytics uses the indicators, targets and threshold decided by the administrators.
The power user here uses the system configuration data on collection of jobs as well as in data
modification layer. Performance analytics target administrator is in position of formulating dashboards
and scorecards. The analytics viewer is the one that views the dashboards based on assigned rights. The
access control breaks-down the elements of security from the source. The relevancy of the Performance
Analytics lies in the six-divided part of the performance overview. The dashboards, scorecards, widgets,
indicators, data collector, automation, system. The dashboard of performance contains the property and to
view points. The scorecards are to break down performance type of the indicators. The indicators are
manual or automated which gauge the relevant updates of the score sheets (Laursen and Thorlund 2016).
Targets and threshold are the elements reporting and alerting about the score of the performance after
breaking it down to view and analyse it. The most essential part of performance analytics are the data
collector phase. Creating and running schedule jobs to collect scores periodically. To view information
the job logs are searched for different information (Stefanovic 2014).
The reason behind the failure of strategic improvement is the lack of getting meaningful clue of
the data gathered. Thus, business analytics helps enabling the manager to draw proper conclusion of the
inputs of the business. The performance management helps in targeting specific part of the organisation to
implement analytics with holistic approach. The factors discussed above are foundation of the variables
that are required to assess the performance. As companies is complex part of societies. The
interdependency factor that works in them is also complex in nature (Phillips-Wren et al. 2015).
Therefore, creating a link between the organisational strategy and performance has become necessary for
the organisations. Thus, the data driven outcomes becomes most reliable part for the managers to make
decision. Overload of data leads to limit the processing the data capabilities. The performance
investigation is includes more variables that indicates the success factor of the individuals. Therefore, it
can be said that the affective decision-making is enhanced by several level of business analytics and
business intelligence (Hazen et al. 2014).

7Business Intelligence and Analytics and Performance Management
Conclusion
Therefore, it can be concluded that Business Intelligence and Business Analytics has become
essential for organisations who are looking for While taking into consideration the internal and external
factors of environment in organisation integration of business analytics with the performance drivers also
helps in management action and control system. Due to individualisation and globalisation of business
environment, the dire need of business analytics has increased. Considering the factors of performance
drivers also equips the managers with implementing the best outcome of taken actions in the business
process. Benefits of business analytics can be reaped if chosen strategically. The necessity of the proper
internal and external environment can be used in terms of implementation of analytics in business
environment. Business analytics enables administration to take affective and rationale decision making
based on historical data. However, its affective implementation requires supportive organizational culture,
stakeholder awareness and support from top-level management. Therefore, careful contemplation is
required to develop the benefits associated with business analytics and addressing hindrances associated
with its performance.

8Business Intelligence and Analytics and Performance Management
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