Business intelligence

Schneider Electric
Business Intelligence
March 2011 / White paper

Make the most of your energy SM

Summary

Executive summary ..................................................................................... p 1

Introduction ................................................................................................. p 2

Business Intelligence technology at the customer’s service .......................... p 4

ETL processes ............................................................................................ p 6

Business Intelligence tools ........................................................................... p 7

Method . ...................................................................................................... p 9

Risk factors in the implementation of Business Intelligence technology . ....... p 10

Schneider Electric services........................................................................... p 11

Schneider Electric success stories................................................................ p 12

Conclusion .................................................................................................. p 15

Schneider Electric Business Intelligence

Executive summary

The wide range of processes within the successful business, from planning to
strategic implementation, requires accurate and ready information throughout. The
cast of personnel involved across the business operation requires widely varying
types of information to perform their assignments. In all, the successful business
requires a powerful Business Intelligence technology.

Discussion covers the constitution and requirements of the effective Corporate
Information Factory (CIF) Architecture. The Data Warehouse component of the
CIF Architecture must be a flexible and reliable store of company information that
allows a high degree of differentiation in data selection, modeling and analysis.

Next, the ETL processes — extract, transform and load — are responsible
for accurately populating the Data Warehouse with information and enabling
the use of this data. Again, differentiating methodologies, along with validating
performance testing, must be accommodated.

Third, Business Intelligence tools for multi-dimensional analysis, budgeting and
forecasting, efficient reporting, and data mining for enhanced insight assure the
proper information is accessed for each specific business process. Developing
and implementing the CIF Architecture involves definition of short-, medium-, and
long-term objectives for the system as well as definition of the elements involved.

When a company implements a Business Intelligence technology, it is important
that risk factors be identified and evaluated, including the scope and degree of
difficulty of information integration, speed and adaptability, utility and practicality
for the employee, and long-term effectiveness.

Schneider Electric Business Intelligence services are based on the company’s vast
experience in helping organizations define their BI policies and develop their BI
Architecture. It offers a productive competence center for consulting support, a
proven product portfolio that allows efficient and effective development of specific
BI solutions, and highly reliable technical assistance for specific needs or longer
term. Several successful Business Intelligence technology solutions implemented
by Schneider Electric are described.


White paper on Business Intelligence | 01


Introduction

Business Intelligence can be defined as a collection of tools and processes that
helps users make decisions. Generally, business processes can be divided into three
phases: planning, implementation and strategy — each requiring unique information.

The planning phase allows the user to take into account known details such as
budget, the previous planning period and the point at which the previous plan
deployed. In creating the new plan, the user wants to present various scenarios
supporting improved decisions — considering factors related to the past, present
and future — and simulate deployment of each situation in the proposed scenario.

During implementation, users must monitor the project as it progresses and
modify processes, make changes and solve problems. To this end, they need
information in real time, along with warning systems and specific indicators that
enable early detection of mistakes. At this stage, the user’s questions are focused
on the actual situation and on the short term.

Information is essential for the selection, design and implementation of a strategy.
Based on information, users can define the weak points in the process and
capitalize on the strengths — resulting in improvements. During this phase,
questions can vary widely but are always based on actual implementation and
particular information.

In addition to these three phases of the business process, it is essential to deal with
the R&D&i Management and Marketing, involving different segments of users with
different behavior and information requirements. Management users view the key
aspects of the company from a global perspective and, consequently, require a high
level of data aggregation. Their questions refer to various Key Performance Indicators
related to operative, economic and marketing factors. Graphical interpretation allows
fast, intuitive understanding of the way in which a situation is developing.

R&D&i Marketing users pay special attention to their customer’s needs. They
study customers, segmentation processes, campaigns, product analysis, market
and niche market research, and research and development. Therefore, they need
an enormous amount of data addressing their wide range of questions regarding
the competition, the customer, the product and the supply chain, in order to adapt
to the reality of the market

In this paper, we speak to the flexibility and capabilities necessary in the design
and implementation of a Business Intelligence technology that successfully serves
all of these corporate needs.


Business Intelligence can
be defined as a collection
of tools and processes that
helps users make decisions


Business Intelligence technology
at the customer’s service
CIF (Corporate Information Factory) architecture

With the aim of giving an answer to the needs of the
customer through Business Intelligence Technology it
is necessary to understand what the CIF (Corporate
Information Factory) Architecture consists of: the Data
Warehouse, the ETL processes and the Business
Intelligence tools.

Data warehouse
This is a huge warehouse where all the company
information which is susceptible to analysis can be
integrated. A rigorous and exhaustive process is
required in order to transform the enormous volume
of data from different activities into information, this
transformation being one of the key points in the
success of the Data Warehouse.

• The capacity to respond to any type of question:
The design and modelling of the database is the main
What?, When?, How?, What if...?
factor that determines the smooth running of the
• Flexibility when faced with the changing needs
analytical environment. Different architectures exist
of the business, given that although the filed
to define the model that should be selected and
information does not change, the needs of the
function of the foreseen criteria of usage for the
user exploiting it does
information warehouse.

Furthermore, it has a number of differentiating
The key aspects that characterizes the Data
methodological aspects:
Warehouse are:

• Star or Snowflake models, according to the
• Uniqueness of information, given that at
exploitation needs
corporate level it must be the sole point of
• Special attention to the treatment of the
access in the search for the same data
Time dimension
• A logical and natural view of the information
• Denormalization of the relational model
directed towards the end user, creating an
• Neutral Modelling, independent from the
environment in which one can manage with ease
selected Data Base Manager
and flexibility



Data warehouse

• Normalization of concepts, abbreviations, formats, etc.
• Atomization of analytical entities
• Dimensional Structuring around the business processes
• Processes of checking and continuous auditing which guarantee
the lifetime of the model

The following are key areas of the Data Warehouse:

• Identification of analysis stars
• Model design:
• Identification of fact tables:
• Granularity, historicity, aggregation levels, volumetry
• Indicators and calculating formulae
• Identification of dimension tables:
• Special attention to the Time dimension
• Identification of hierarchies
• Indexing policies
• Partitioning policies



ETL processes

These are all the processes necessary in order to populate the Data Warehouse
with information, and one of the main factors in its optimum exploitation. Through
these processes the information is consolidated in various operating environments
(OLTP) in a unified and integrated way. These characteristics mean that a great
effort is required with respect to design and implementation and a maintenance
policy, given that the ETL processes can be defined by a certain temporary
nature. The processes of duplication and information cleaning, and integrating
elements of information from various origins, help the company to detect errors or
incongruence in the data from operational environments.

Among the differentiating methodological aspects within the ETL processes the
following are found:

• Definition of the ETL policies. That is to say, criteria for process re utilization,
best practices, etc.
• Definition of quality criteria: taking action against invalid values, duplications,
loss of integrity references, incomplete data, etc.
• Identification of data sources and the determination of relationships between
information from different sources
• Analysis and identification of patterns and assurance of the uniqueness of
transformation criteria, including typologies, formats, etc.
• Mapping of origins and destinations: definition of transformation flows
• Performance tests and procedure tuning
• Definition of the ETL processes via transformation workflows, which allow the
clear identification of the origin of the final data and the distinct processes
passed through in order to obtain it
• Traceability of the transformation steps. Through “rewind” and “pause” it is
possible to analyze, follow-up and audit each of the critical points in the process
• Management of planning calendars which permits a correct execution of the
different loading sequences and eliminates process obsolescence
• Filing history of process execution which allows the optimization of the batch
execution window



Business Intelligence tools

In view of the different tasks performed by users, their 2. Operative Reporting: systems of information
informational needs vary substantially. The Business use via predefined, formatted and flexible
Intelligence tools must allow fast, simple and questions, characterized by a highly operative
comfortable access to the information contained in and functional content; low volatility; application
the Data Warehouse or in the Data Marts, while never of parameters according to criteria such as
straying from the user’s point of view. time, organization and geography; low level of
detail, execution subject to planning; distribution
Needs vary with the type of user, and it is therefore to users without the need to connect to the
necessary to identify the user typology before Business Intelligence platform, and the possibility
deciding what technology will be selected in order to of integration within nonanalytical platforms.
cover their needs.
3. Balanced Scorecard: a system of information
1. OLAP (Online analytical processing): multi- use which makes it possible for a fast, visual
dimensional information analysis systems via analysis of the business circumstances through
non-predefined questions. It is directed at users the definition of Key Performance Indicators (KPI)
with a wide knowledge of the business as it based on a series of criteria of analysis (time,
responds to all types of question (what, when, geography, organization, etc.) It is characterized
why, how). It allows the creation of reports for the by elements of graphical analysis (such as
operating user and also the possibility to make traffic lights, maps and graphs); maps to help
forecasts, simulations, and generate scenarios. It with navigation through the information, from
assumes that the user can act independently of the highest aggregation level to the lowest level
the IT department. of detail; agility and versatility in the use of the
navigational elements (drop-down lists, radio
buttons and multiselectors) and the possibility
that the user can incorporate their own
information (notes and comments).



Business Intelligence tools

4. Data Mining: through complex processes it is possible to identify keys to
business that are hidden on first view and that can come to represent major
profit for the company. This tool requires a profound knowledge and analysis
of information, together with very high specialization in the use of statistical
techniques and logarithmic and segment information analysis.

5. Budgeting / Forecasting: they are control tools in order to know what the
situation of the organization should be and they are characterized by being
totally involved in order to make that better informed decision’s; to substitute
the rigid annual budget with a continuous plan which offers a greater capacity
to provide answers; to allow operations and finance to interconnect and aid
the generation of budgets from the bottom up, while adjustments are made
from the top down.



Method

The methodology for the implementation of CIF
architecture must follow certain guidelines
1. Definition of the strategy:

• The definition of the strategic framework in which
the short-, medium- and long-term objectives for
the proposed system are included
• Identification of key users and the areas involved
• Functional, non-functional and
analytical requirements
• Capacities analysis (volumetries,
concurrencies, etc.)

2. Definition and development of the process:

• System modelling
• Areas of analysis
• Identification of facts and dimensions
• Granularity The management of metadata is defined on
• Denormalization two levels:
• Study of the originating system
• Transformation workflows 1. User metadata
• Design of ETL processes
• Study of the analytical needs • Business dictionary and definition of
• Solutions design business entities
• Reporting • Description of business objects
• Analysis universes (metrics, hierarchies)
• Balanced scorecards • Description of reports
• The capacities of the Business Intelligence
tool are used

2. IT metadata (administration)

• Definition at data model level, within
its own database
• Definition of the ETL processes: defined at the
process level (in the case of ETL) and in the
database dictionary tables (in the case of the
model entities)



Risk factors in the implementation of
Business Intelligence technology
The following factors which could imply a risk in the 6. Loss of perspective regarding the needs of
implementation of Business Intelligence technology the users. The user must be provided with the
must be kept in mind. tool most compatible with their job, instead of
the tool most compatible with the IT department.
1. Projects which are too ambitious. It is 7. Dependency. Dependency on the IT
advised to face projects in phases and provide department is to be avoided by providing
results in each of them. compatible tools, a measure which will also
2. Difficulties with information integration. avoid disproportionate costs.
The processes of information clean-up are
expensive and the results obtained never match
expectations, so it is very difficult to explain to
the user why the systems are not as good as
they believed.
3. Long-term sustainability. Changes often
cause a loss of homogeneity in the system.
4. Adaptation. Given that a business is a living
organism that needs to change in order to
survive, the decisions related to changes are
taken through the Business Intelligence systems
which must be constantly adapting to change.
5. Speed of implementation. A solution
whose implementation takes more than three
months is ineffective to the user. For this reason
it is recommended to shorten the times of
the first implementations and define a gradual
development in the execution of the
remaining objectives.



Schneider Electric services

Schneider Electric Business Intelligence • Responsible Projects. Contracting a closed
services include: project with a reach perfectly defined by
deliverables, costs and fixed and defined terms
• Business Intelligence competence centre. laid out in a project plan.
A highly productive environment for the
development of Business Intelligence which • Remote assistance. Technical assistance
provides technology and methodology skills to from the offices of Schneider Electric. A direct
help organizations and the customers with the connection with the customer’s server or
definition of BI policies. development in the server itself.

• Product Portfolio. Market solutions which can be
adjusted based on the idiosyncrasies of customer,
oriented to the product and easy to implement.

• Technical assistance. The provision of our own
people to work with the customer in his office in
order to provide specialized capacities, to address
a specific need or for longer periods of time.



Schneider Electric success stories

Described below are some of the Schneider Electric 3. Iberia migration project:
success stories in the implementation of its Business
Intelligence technology: • Administration, development and maintenance
of metadata
1. Project development with Powercenter and • Development of new analyses and reports
Business Objects for Isban including: • User support and incidents
• Maintenance of the loading process
• Means of payment Data Mart (Oracle warehouse builder)
• Mortgage holder Data Mart • New balanced scorecard developments
• Account Balance Test Model for Abbey Bank • Balanced scorecard development with OBI
• PMO Data Mart (Project Management Office)
• MIS NEWCO Project, migration and integration 4. Audit of the implentation and performance
of data with Powercenter of the Data Warehouse for the Hospital
• Financial consolidation L’Horta Manises:
• Digital signature integration
• Remote collaboration in projects via models of • Audit of data models
software industrialization • Audit of the metadata level of the model
• Administration of environments and • Development with Cognos 8
process monitoring • Definition of Best practices
• Definition of methodologies
• Training in Powercenter 5. Definition of reports and balanced
scorecards for J. García Carrión:
2. Implementation of the BI platform for
Parques Reunidos: • Definition of logistics management
commercial indicators
• Implementation of Data Warehouse (Illuminate) • Definition of sales management
• Training commercial indicators
• X Cognos version 8 projects • Elaboration of the Sales Dossier for
• Projects for migration from Analysis Service general management
• Training of users in the Cognos and
Illuminate tools 6. Analysis of the implantation and
• Implementation of the Cognos 8 corporative performance of the Powercenter tool for
reporting platform Caser Seguros:
• Implementation of the Planning and
Forecasting module • Audit and tuning of Powercenter processes
• Audit of methodology and administration
of Powercenter




7. Analysis and exploitation of DWH financial 11. Development of Balanced Scorecard for
services for Carrefour: B:SM (Barcelona de Serveis Municipals):

• Development of indicators • Balanced scorecard for payroll and human
• Maintenance and evolution of the Data Warehouse resources departments
• Model optimization • Development of reports with DC-Reporting
• Design and development of Data Mart with
8. Analysis and development of the ETL SQL Server
processes for Arias:
12. Balanced scorecard for Financial
• Development of the ETL processes from the ERP Management with Apesoft for Grupo Abades:
• Definition and development of indicators
• Modelling • Data Warehouse analysis
• Database concepts and calculation criteria check
9. Analysis and development of the ETL • Training for developers and users
processes (Powercenter) for Sage:
13. Definition of strategic maps for
• ETL processes for medium-sized Ono Companies:
businesses (KRONOS)
• ETL processes for sales system (ASTEC) • Development of balanced scorecard for the
• Sales team information exchange files (MDB) departments of Ono Companies
• Definition of the architecture
10. Cognos Migration Technology for Bristol- • ETL process
Myers Squibb Company:
14. Design and development of a Data
• Requirements, planning, unit tests and Warehouse for Ericsson:
user guides
• Intermediate and advanced user training • Design and development of the Data Warehouse
• Configuration of a development environment • Implementation of indicators
• ETL Processes
• Creation of reports, consultancies and alarms




15. Design and development of Data
Warehouse for the Management Control
department for La Razón:

• ETL processes
• Modelling of data structures
• Development of Reporting

16. Design and development of Data Mart
Commercial Network with Apesoft for
González Byass:

• ETL processes
• Analytical structure modelling
• Platform management

17. Implementation of a reporting system for
Zena catering group:

• Distribution, operative and accounting
information reporting

18. Implantation of Integrated Balanced
Scorecard for Movie World:

• ETL processes
• Analytical structure modelling
• Design and development of the
Balanced Scorecard



Conclusion

Business Intelligence in a nutshell:

• The strength of a company’s Business Intelligence technology in meeting the

informational needs of all business units of the organization is highly dependent
on proper planning during definition and design, to assure adequate flexibility
and longevity of the architecture.

• Other factors bearing on the success of a Business Intelligence technology

include the robustness of data analysis collection and the processing elements
that act on the data.

• The successful Business Intelligence solution must make the tools available

to employees that empower them to query, process and report the
information needed.

• Business Intelligence technology should serve the organization, and not the

other way around.

A Business Intelligence competence centre provides
technology and methodology skills to organizations
and customers


© 2012 Schneider Electric. All rights reserved.

Schneider Electric
C/ Valgrande, 6,
28108 - Alcobendas (Madrid) (Spain)
Telephone: 34-902-33-55-99
Fax: 34-91-714-70-05
http://www.schneider-electric.com
July 2012

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