Description
Closing the Management Information Gap with Operational BI
Closing the Management
Information Gap with
Operational BI
White Paper
sponsored by
Aligning Business and IT to Improve Performance
Ventana Research Headquarters
1900 South Norfolk Street, Suite 280
San Mateo, CA 94403
[email protected]
(650) 931-0880
Ventana Research Europe
2nd floor, Berkeley Square House
Berkeley Square, W1J 6BD London
[email protected]
44 (0) 20 7887 6012
Copyright Ventana Research 2007 Page 1 Do Not Redistribute Without Permission
Ventana Research – Closing the Management Information Gap with Operational BI
© Ventana Research 2007 Page 2
Table of Contents
Beyond Traditional BI ..............................................................................3
New Users, New Needs ............................................................................3
Challenges for Operational BI Systems ....................................................4
Operational BI Results .............................................................................5
Demands on Technology ..........................................................................5
Closing the Management Information Gap ...............................................6
About Ventana Research..........................................................................7
Ventana Research – Closing the Management Information Gap with Operational BI
© Ventana Research 2007 Page 3
Beyond Traditional BI
Traditional business intelligence (BI) technology assembles historical data, presents
it in forms such as reports, dashboards and scorecards, and analyzes it; it is
deployed to give analytical staff and senior executives information they require to
decide on the strategic course their business ought to take. A few years ago, users
saw that they might apply BI’s data assembly, visualization and analytical
capabilities to their operational needs and started using the technology to help
managers make tactical decisions about their business units.
It quickly has become clear that the data requirements of operational business
intelligence are different from those of traditional BI, and it has become clear as well
that it requires different visualization and analytical tools. These differences continue
to challenge most companies. We will explore what those challenges are and discuss
how new technology can meet them in your company.
The differences between traditional BI and operational BI are a useful starting point
from which to explain their data requirements and ways in which they diverge. Those
differences are rooted in the purposes of each system, as well as in the number and
types of users of each.
Traditional business intelligence looks to the past to understand how the business
has performed and to analyze what will improve business performance going
forward. For that historical approach to analysis, traditional BI relies on data stored
in formatted business records usually found in data warehouses or marts. The data
assembly requirements include bringing data into the system from various groups
and departments within the company, as well as from trading partners outside the
company. However, because this is always done after the fact, there is no need to
synchronize the timing of traditional BI analysis with ongoing operating or financial
processes at the company.
Data delivery to traditional BI users typically comes in the form of dashboards,
printed reports or data transferred into other applications, such as Microsoft
PowerPoint for presentation or Excel for further analysis. Whatever form they take,
the timing of the deliveries is not critical to the success of traditional BI.
The user group for traditional business intelligence is typically small and high-level,
consisting largely of two groups: business analysts and financial professionals, and
senior managers and executives. The decisions that result from traditional BI
analysis have a relatively long-term focus that affects the company’s business plans,
and so they are not generally time-critical with respect to day-to-day operations.
New Users, New Needs
Operational business intelligence, in contrast, focuses on those day-to-day
operations of the company, and it is used by a wide array of line management
personnel who are responsible for making decisions that drive the current business
performance of their units. That difference has several implications for how much
and what type of data operational BI needs, what types of decisions its users make,
how the business applies those decisions and the number and type of users that an
operational BI system must serve. It also has implications for how an operational
business intelligence system presents and analyzes data.
Ventana Research – Closing the Management Information Gap with Operational BI
© Ventana Research 2007 Page 4
Operational BI assembles data from the business as it happens, reports on it and
analyzes it. While this set of processes uses some historical data, it relies much more
on current transactional information. It is not unusual for operational BI systems to
require real-time access to data and to update its data stores several times during a
day. And their mission to make operational decisions requires more types of data
and more of it than the longer-term analysis of traditional BI.
More people use operational than traditional business intelligence systems, and most
of those people are not at that senior managerial or analytical level. As a result,
operational business intelligence systems have to scale to accommodate much
greater user demand, which may require additional hardware and networking
resources, as well as different types of software able to sustain high usage volumes.
Operational BI systems also perform reporting and analysis differently than
traditional systems.
Challenges for Operational BI Systems
Decision-making in both traditional and operational business intelligence
environments is collaborative. However, the decision latency that prevails in
traditional BI environments is unacceptable in environments where decisions may
affect business operations on the day they are made. That means that the decision-
making process supported by operational business intelligence has to keep moving at
a fast, steady pace. To do that, operational BI systems have to assemble a huge
volume of data, analyze it and present it in accessible ways to many users.
Not only do the types of data presentation and analysis used in operational business
intelligence have to be geared toward large numbers of people; few of those users
have the advanced technical and analytical skills of those using traditional BI
systems. And even if the skill levels are comparable, those users do not have the
luxury of time because they need to make operational decisions immediately. They
need quickly to access, absorb and act on information and analytical results.
The lack of timely access to information – latency – is one of the most difficult
challenges to using operational business intelligence systems successfully. In a
recent Ventana Research study of operational business intelligence, for example,
nearly three-quarters (71 percent) of respondents said that reducing the time it
takes to update their data was somewhat important or very important. In addition,
nearly one-quarter (22 percent) of the respondents said that adequate business
intelligence analysis requires real-time data, and 39 percent said they require daily
or more frequent updates.
Collaborative decision-making in an operational BI environment depends on shared
data, but data access often is confined to those who use it regularly. It is critical to
share information to be able to improve the quality of decisions. But many
organizations do not enable collaboration or understand it to be important; our
operational business intelligence study found only a small percentage of users who
rated collaboration as a high priority.
Compounding the collaboration problem are data silos, which effectively hide data
from many users. Departmental transaction data that users require for operational
business intelligence frequently resides inaccessibly in other functional or
Ventana Research – Closing the Management Information Gap with Operational BI
© Ventana Research 2007 Page 5
departmental areas of the enterprise. Even when it is available, automated transfer
mechanisms are not in place, so users must extract it manually, which can be
difficult and time-consuming to do. It can be even more difficult to acquire data for
operational BI from external sources, such as trading partners and industry
associations. And some of the data may be unstructured and therefore inaccessible
to traditional tools, further compounding the problem.
Integrating data from all the disparate sources into the operational business
intelligence environment requires intra-company and inter-partner collaboration. To
enlist the cooperation of these separate units requires executive support and diligent
bridge-building. What’s more, an operational extraction, transformation and loading
(ETL) environment of some sort has to be present at the front of the system to
automate transport of the data. This extra step can add overhead to the process, of
course; as well, it sometimes can create disparity in versions of the data. An
effective operational BI system can provide dynamic access to data across data silos,
making it possible to provide real-time information to operational workers.
Operational BI Results
Executives and management consultants agree that effective business process
management involves pushing day-to-day decisions down to the line-of-business
operations managers. Operational BI supports that by giving them access to
information and tools that help them make decisions that improve the performance
of their business.
The chief benefit of moving operating decisions to this level is that it improves the
quality and speed of the decisions. Making that move through operational business
intelligence can lead to several business benefits.
For example, you can increase revenue by using operational BI to create a more
effective product mix, optimize distribution techniques or find better marketing
partners. Operational business intelligence can enable you to manage target
marketing programs better by being able to measure the responsiveness of various
segments and recalibrating more quickly and precisely as you react to changes in
demand.
You can control costs by using operational BI to reduce waste and scrap and to
increase the productivity of materials and labor. You can find and evaluate less costly
manufacturing partners or parts suppliers and determine how to utilize plant
capacities more fully.
You can improve customer service by using operational business intelligence to
create a more responsive call center operation or more responsive restocking
programs. Operational BI can help you bring new products to market more quickly or
to clear inventory in a profitable way. You also can optimize shelf space to maximize
product exposure at lower costs.
Demands on Technology
A combination of modern technology and careful management can remove barriers
that stand in the way of a successful business environment. Technology for
Ventana Research – Closing the Management Information Gap with Operational BI
© Ventana Research 2007 Page 6
operational business intelligence is similar to traditional BI systems in that it gathers
and presents information to users, but it is different on several counts. Operational
BI has to serve more and less technically oriented users, be more responsive to ad-
hoc requests and be able to add new sources of data quickly as business models and
product mixes change.
As well as accessing historical financial and operating data, operational BI also
makes heavy use of current transaction data, along with a range of data – both
structured and unstructured – from other internal and external sources.
Therefore, a powerful and flexible data acquisition system is a primary requirement
of an operational BI system. It has to be able to access key data in real time and
other data manually or automatically. It also has to be able to absorb unstructured
data, and do all of this in a rapidly responsive way.
“Responsive” in this case means that users have to be able to specify where and
when to get new data that was not previously included in the system. Decisions
based on operational business intelligence often cannot wait for IT personnel to
create a data acquisition project when new sources of information are necessary to
support those decisions.
Presentation for operational business intelligence systems can use the same basic
dashboard paradigm that is popular in traditional systems and retain the basic
reporting capabilities. Those include the ability to drill down into data, to change the
type of graphic being used and to move table columns around. Here again, however,
operational BI requires certain changes.
The dashboards must offer more self-service for users. Just as they can’t wait for IT
to make changes in data sources, users also can’t wait for IT to adjust the
dashboards to present new types of data or to use data in a different way. Users
must be able to access data on their screens quickly and manipulate it as soon as
they need to.
At the same time as demand increases, the types of analysis available on the
operational BI dashboards must be manageable for the users accessing this type of
system. Most will not be technically competent enough to understand high-order
statistical analysis, and they probably do not have time to wait for such calculations
to be made. In addition, the larger number of users may necessitate, in order to
keep the system responsive, a simpler analytical and graphical presentation
environment. The analytical tools must be geared toward ad-hoc and what-if types of
analyses, rather than the longer-term analysis and projection models used in
traditional BI systems.
Closing the Management Information Gap
Operational business intelligence might better be called “pervasive business
intelligence” because, if effectively implemented, it will be used throughout the
operating side of the organization to improve its business processes. The right
technology applied through the leadership and support of committed management
will enable a company to operate as an intelligent machine that responds to inputs
from its line managers, who use its feedback to improve their decisions.
Ventana Research – Closing the Management Information Gap with Operational BI
© Ventana Research 2007 Page 7
In addition to direct benefits such as those cited above, there are indirect benefits to
operational BI. The nature of this approach requires and facilitates greater intra-
company and inter-partnership collaboration and integration, not just of data but of
operations. That collaboration in turn can produce further discoveries about how to
operate the business better.
But the bottom line is of course the bottom line: Operational BI brings the day-to-
day operations of the company and the line managers responsible for these
operational processes in line with modern management by pushing day-to-day
decisions down to them and placing before them the information and tools they need
to make effective operational decisions. Operational BI improves organizational
performance by expanding and localizing decision-making capability, eliminating
latency, enabling collaboration and improving access to siloed data, all of which will
significantly improve business performance.
About Ventana Research
Ventana Research is the leading Performance Management research and advisory
services firm. By providing expert insight and detailed guidance, Ventana Research
helps clients operate their companies more efficiently and effectively. We deliver
these business improvements through a top-down approach that connects people,
processes, information and technology. What makes Ventana Research different from
other analyst firms is our focus on Performance Management for finance, operations
and IT. This focus, plus research as a foundation and reach into a community of
more than 2 million corporate executives through extensive media partnerships,
allows Ventana Research to deliver a high-value, low-risk method for achieving
optimal business performance. To learn how Ventana Research Performance
Management workshops, assessments and advisory services can impact your bottom
line, visit www.ventanaresearch.com.
doc_362107894.pdf
Closing the Management Information Gap with Operational BI
Closing the Management
Information Gap with
Operational BI
White Paper
sponsored by
Aligning Business and IT to Improve Performance
Ventana Research Headquarters
1900 South Norfolk Street, Suite 280
San Mateo, CA 94403
[email protected]
(650) 931-0880
Ventana Research Europe
2nd floor, Berkeley Square House
Berkeley Square, W1J 6BD London
[email protected]
44 (0) 20 7887 6012
Copyright Ventana Research 2007 Page 1 Do Not Redistribute Without Permission
Ventana Research – Closing the Management Information Gap with Operational BI
© Ventana Research 2007 Page 2
Table of Contents
Beyond Traditional BI ..............................................................................3
New Users, New Needs ............................................................................3
Challenges for Operational BI Systems ....................................................4
Operational BI Results .............................................................................5
Demands on Technology ..........................................................................5
Closing the Management Information Gap ...............................................6
About Ventana Research..........................................................................7
Ventana Research – Closing the Management Information Gap with Operational BI
© Ventana Research 2007 Page 3
Beyond Traditional BI
Traditional business intelligence (BI) technology assembles historical data, presents
it in forms such as reports, dashboards and scorecards, and analyzes it; it is
deployed to give analytical staff and senior executives information they require to
decide on the strategic course their business ought to take. A few years ago, users
saw that they might apply BI’s data assembly, visualization and analytical
capabilities to their operational needs and started using the technology to help
managers make tactical decisions about their business units.
It quickly has become clear that the data requirements of operational business
intelligence are different from those of traditional BI, and it has become clear as well
that it requires different visualization and analytical tools. These differences continue
to challenge most companies. We will explore what those challenges are and discuss
how new technology can meet them in your company.
The differences between traditional BI and operational BI are a useful starting point
from which to explain their data requirements and ways in which they diverge. Those
differences are rooted in the purposes of each system, as well as in the number and
types of users of each.
Traditional business intelligence looks to the past to understand how the business
has performed and to analyze what will improve business performance going
forward. For that historical approach to analysis, traditional BI relies on data stored
in formatted business records usually found in data warehouses or marts. The data
assembly requirements include bringing data into the system from various groups
and departments within the company, as well as from trading partners outside the
company. However, because this is always done after the fact, there is no need to
synchronize the timing of traditional BI analysis with ongoing operating or financial
processes at the company.
Data delivery to traditional BI users typically comes in the form of dashboards,
printed reports or data transferred into other applications, such as Microsoft
PowerPoint for presentation or Excel for further analysis. Whatever form they take,
the timing of the deliveries is not critical to the success of traditional BI.
The user group for traditional business intelligence is typically small and high-level,
consisting largely of two groups: business analysts and financial professionals, and
senior managers and executives. The decisions that result from traditional BI
analysis have a relatively long-term focus that affects the company’s business plans,
and so they are not generally time-critical with respect to day-to-day operations.
New Users, New Needs
Operational business intelligence, in contrast, focuses on those day-to-day
operations of the company, and it is used by a wide array of line management
personnel who are responsible for making decisions that drive the current business
performance of their units. That difference has several implications for how much
and what type of data operational BI needs, what types of decisions its users make,
how the business applies those decisions and the number and type of users that an
operational BI system must serve. It also has implications for how an operational
business intelligence system presents and analyzes data.
Ventana Research – Closing the Management Information Gap with Operational BI
© Ventana Research 2007 Page 4
Operational BI assembles data from the business as it happens, reports on it and
analyzes it. While this set of processes uses some historical data, it relies much more
on current transactional information. It is not unusual for operational BI systems to
require real-time access to data and to update its data stores several times during a
day. And their mission to make operational decisions requires more types of data
and more of it than the longer-term analysis of traditional BI.
More people use operational than traditional business intelligence systems, and most
of those people are not at that senior managerial or analytical level. As a result,
operational business intelligence systems have to scale to accommodate much
greater user demand, which may require additional hardware and networking
resources, as well as different types of software able to sustain high usage volumes.
Operational BI systems also perform reporting and analysis differently than
traditional systems.
Challenges for Operational BI Systems
Decision-making in both traditional and operational business intelligence
environments is collaborative. However, the decision latency that prevails in
traditional BI environments is unacceptable in environments where decisions may
affect business operations on the day they are made. That means that the decision-
making process supported by operational business intelligence has to keep moving at
a fast, steady pace. To do that, operational BI systems have to assemble a huge
volume of data, analyze it and present it in accessible ways to many users.
Not only do the types of data presentation and analysis used in operational business
intelligence have to be geared toward large numbers of people; few of those users
have the advanced technical and analytical skills of those using traditional BI
systems. And even if the skill levels are comparable, those users do not have the
luxury of time because they need to make operational decisions immediately. They
need quickly to access, absorb and act on information and analytical results.
The lack of timely access to information – latency – is one of the most difficult
challenges to using operational business intelligence systems successfully. In a
recent Ventana Research study of operational business intelligence, for example,
nearly three-quarters (71 percent) of respondents said that reducing the time it
takes to update their data was somewhat important or very important. In addition,
nearly one-quarter (22 percent) of the respondents said that adequate business
intelligence analysis requires real-time data, and 39 percent said they require daily
or more frequent updates.
Collaborative decision-making in an operational BI environment depends on shared
data, but data access often is confined to those who use it regularly. It is critical to
share information to be able to improve the quality of decisions. But many
organizations do not enable collaboration or understand it to be important; our
operational business intelligence study found only a small percentage of users who
rated collaboration as a high priority.
Compounding the collaboration problem are data silos, which effectively hide data
from many users. Departmental transaction data that users require for operational
business intelligence frequently resides inaccessibly in other functional or
Ventana Research – Closing the Management Information Gap with Operational BI
© Ventana Research 2007 Page 5
departmental areas of the enterprise. Even when it is available, automated transfer
mechanisms are not in place, so users must extract it manually, which can be
difficult and time-consuming to do. It can be even more difficult to acquire data for
operational BI from external sources, such as trading partners and industry
associations. And some of the data may be unstructured and therefore inaccessible
to traditional tools, further compounding the problem.
Integrating data from all the disparate sources into the operational business
intelligence environment requires intra-company and inter-partner collaboration. To
enlist the cooperation of these separate units requires executive support and diligent
bridge-building. What’s more, an operational extraction, transformation and loading
(ETL) environment of some sort has to be present at the front of the system to
automate transport of the data. This extra step can add overhead to the process, of
course; as well, it sometimes can create disparity in versions of the data. An
effective operational BI system can provide dynamic access to data across data silos,
making it possible to provide real-time information to operational workers.
Operational BI Results
Executives and management consultants agree that effective business process
management involves pushing day-to-day decisions down to the line-of-business
operations managers. Operational BI supports that by giving them access to
information and tools that help them make decisions that improve the performance
of their business.
The chief benefit of moving operating decisions to this level is that it improves the
quality and speed of the decisions. Making that move through operational business
intelligence can lead to several business benefits.
For example, you can increase revenue by using operational BI to create a more
effective product mix, optimize distribution techniques or find better marketing
partners. Operational business intelligence can enable you to manage target
marketing programs better by being able to measure the responsiveness of various
segments and recalibrating more quickly and precisely as you react to changes in
demand.
You can control costs by using operational BI to reduce waste and scrap and to
increase the productivity of materials and labor. You can find and evaluate less costly
manufacturing partners or parts suppliers and determine how to utilize plant
capacities more fully.
You can improve customer service by using operational business intelligence to
create a more responsive call center operation or more responsive restocking
programs. Operational BI can help you bring new products to market more quickly or
to clear inventory in a profitable way. You also can optimize shelf space to maximize
product exposure at lower costs.
Demands on Technology
A combination of modern technology and careful management can remove barriers
that stand in the way of a successful business environment. Technology for
Ventana Research – Closing the Management Information Gap with Operational BI
© Ventana Research 2007 Page 6
operational business intelligence is similar to traditional BI systems in that it gathers
and presents information to users, but it is different on several counts. Operational
BI has to serve more and less technically oriented users, be more responsive to ad-
hoc requests and be able to add new sources of data quickly as business models and
product mixes change.
As well as accessing historical financial and operating data, operational BI also
makes heavy use of current transaction data, along with a range of data – both
structured and unstructured – from other internal and external sources.
Therefore, a powerful and flexible data acquisition system is a primary requirement
of an operational BI system. It has to be able to access key data in real time and
other data manually or automatically. It also has to be able to absorb unstructured
data, and do all of this in a rapidly responsive way.
“Responsive” in this case means that users have to be able to specify where and
when to get new data that was not previously included in the system. Decisions
based on operational business intelligence often cannot wait for IT personnel to
create a data acquisition project when new sources of information are necessary to
support those decisions.
Presentation for operational business intelligence systems can use the same basic
dashboard paradigm that is popular in traditional systems and retain the basic
reporting capabilities. Those include the ability to drill down into data, to change the
type of graphic being used and to move table columns around. Here again, however,
operational BI requires certain changes.
The dashboards must offer more self-service for users. Just as they can’t wait for IT
to make changes in data sources, users also can’t wait for IT to adjust the
dashboards to present new types of data or to use data in a different way. Users
must be able to access data on their screens quickly and manipulate it as soon as
they need to.
At the same time as demand increases, the types of analysis available on the
operational BI dashboards must be manageable for the users accessing this type of
system. Most will not be technically competent enough to understand high-order
statistical analysis, and they probably do not have time to wait for such calculations
to be made. In addition, the larger number of users may necessitate, in order to
keep the system responsive, a simpler analytical and graphical presentation
environment. The analytical tools must be geared toward ad-hoc and what-if types of
analyses, rather than the longer-term analysis and projection models used in
traditional BI systems.
Closing the Management Information Gap
Operational business intelligence might better be called “pervasive business
intelligence” because, if effectively implemented, it will be used throughout the
operating side of the organization to improve its business processes. The right
technology applied through the leadership and support of committed management
will enable a company to operate as an intelligent machine that responds to inputs
from its line managers, who use its feedback to improve their decisions.
Ventana Research – Closing the Management Information Gap with Operational BI
© Ventana Research 2007 Page 7
In addition to direct benefits such as those cited above, there are indirect benefits to
operational BI. The nature of this approach requires and facilitates greater intra-
company and inter-partnership collaboration and integration, not just of data but of
operations. That collaboration in turn can produce further discoveries about how to
operate the business better.
But the bottom line is of course the bottom line: Operational BI brings the day-to-
day operations of the company and the line managers responsible for these
operational processes in line with modern management by pushing day-to-day
decisions down to them and placing before them the information and tools they need
to make effective operational decisions. Operational BI improves organizational
performance by expanding and localizing decision-making capability, eliminating
latency, enabling collaboration and improving access to siloed data, all of which will
significantly improve business performance.
About Ventana Research
Ventana Research is the leading Performance Management research and advisory
services firm. By providing expert insight and detailed guidance, Ventana Research
helps clients operate their companies more efficiently and effectively. We deliver
these business improvements through a top-down approach that connects people,
processes, information and technology. What makes Ventana Research different from
other analyst firms is our focus on Performance Management for finance, operations
and IT. This focus, plus research as a foundation and reach into a community of
more than 2 million corporate executives through extensive media partnerships,
allows Ventana Research to deliver a high-value, low-risk method for achieving
optimal business performance. To learn how Ventana Research Performance
Management workshops, assessments and advisory services can impact your bottom
line, visit www.ventanaresearch.com.
doc_362107894.pdf