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Yellowfin, Powered by J2EE, Spring, iTEXT, JFreeChart, BIRT, Jasper
Introducing Business Intelligence appliances across the enterprise
promises a whole new level of data awareness for the staff base, which
can promote new efficiencies, transparencies and open new ways to
target and serve customers. But it still scares some.
Rolling out a quality BI product through the enterprise is not a task
that can be just assigned to a single silo group, it requires
management and work groups to commit to a long term project, it
requires cross group co-operation, data cleaning, data sharing and
most importantly education. Resistance groups can appear during the
project when people feel the challenges out way the benefits to them
or that better reporting may threaten their own jobs; while others may
believe that company data should not be openly available.
To address these blocks and help get BI implementations off the ground
more quickly we have compiled a list of the top ten most common
cultural issues with BI project rollouts. We then asked the CEO of
"Yellowfin Business Intelligence", Glen Rabie, to detail some of his
own company's frontline experiences with enterprise BI and provide
some solutions to alleviate the anxiety.
1. Complexity
(ACW) BI projects bring with them a new set of problems, company data
is generally is disparate systems that must now be linked, data is
often duplicated, data archiving and cleaning become more important,
there are political issues to solve, different hardware and opsys to
consider, which appliance to use and then the massive problem of
educating people. What is it about BI projects that make them so
complex?
(Glen Rabie)
To be honest I do not actually think BI is that hard. The true
complexity lies in a number of items - one, actually defining the
reports and data that people want. Business analysis and really
engaging the end users is critical. Two, data cleansing - many
applications allow users to enter junk - and the BI tool by exposing
data makes this data visible. Now you have to go back and clean all
that up! Lastly, you have the big bang approach. To many companies
feel they have only one shot at a BI project. In my view this is the
wrong approach. Start small and develop an incremental framework for
delivering BI over time. Let you users see what they are getting in
stages and allow them to learn what they actually need. And yes -
give people time to improve business processes to clean up that data.
2. Change
(ACW) This single issue can stall an IT project at any point, people
fear change or perceiving a threat to themselves, whether it results
in more work for them personally, greater scrutiny or worst case make
their jobs irrelevant/obsolete. Business Intelligence tools can result
in a great deal of change - what are the cultural impacts of this
change?
(Glen Rabie)
Like any project there are always a bunch of people that just like
doing it the old way. Their power is derived from being the gate
keeper to data - take that away with a BI tool and you do change their
working lives. The problem with the BI project is that the gate
keepers are critical to success. If they block or attempt to de-rail
the project then there is little chance of delivering a great
outcome.
There has been a tonne of articles written on the blocker so I will
not delve to deeply. However, another more subtle failure occurs when
key users do not get involved in a project due to other higher
priority tasks. For BI to be successful a series of sign-off steps
need to occur to ensure data accuracy and that what will be delivered
will be of business value. If the key internal users do not get
involved and are just waiting for the delivery of the BI project - the
project will fail. And as usual the project team is held
accountable. Drive the change management and really make sure that
all stakeholders are involved and sign-off on every step within the
project.
3. Investment
(ACW) Like any IT project, BI projects require investment in time,
money and human effort. The investment can seem too steep for the
payoff for some.
Why do BI projects suffer from a perceived lack of ROI?
(Glen Rabie)
Well this is the recurring theme of BI. Business users want it, and
yes it does cost money and yet putting your finger on the value of
information and how that translates into accountable business benefits
is incredibly difficult. The way we like to think about it is simple
- imagine working without internet access - in the early days no
conceivable benefit but now, who could imagine a knowledge workers
life without it? Sure you can continue to use excel and cobbled
together processes and save money by not going out and doing that BI
project - but in the long term will your business grow and thrive
using that strategy? Probably not!
4. Just another Buzz phase
(ACW) Like many of the must have technologies that have propagated
through international corporations, from CASE tools in the 80's to
WEB2.0 today. IT managers fear Business Intelligence for the masses
will have limited usefulness and after the initial interest period
will gather dust as people get on with their established ways of
working. What is you view on this?
(Glen Rabie)
I think the opposite will occur. If we look at the history of
business computing the persistent trend is to making users self
sufficient. Lets take Excel as an example. In the early days there
were a handful of excel super heroes in an organisation - now it is
ubiquitous - everyone pretty much knows how to navigate a
spreadsheet. What is lacking from the spreadsheet, however, is the
centralised access to multiple data sources - and that is BI. People
now are starting to want direct access to their data without IT's
intervention. And that is a trend that will not stop.
5. What's wrong with Excel? attitude!
(ACW) Business and IT groups have become used to using the tools they
have at hand. Traditionally Excel is the application that people are
quite comfortable for most of their data manipulation and reporting.
Do IT managers believe it is sufficient for most staff?
(Glen Rabie)
Look it depends - I do not want to speak for all IT managers but I
suppose a large set would feel this way. There are a myriad of
problems about using excel - most of them not visible to management -
and so in that sense not a problem.
Some of my favourites - How did users get their data that they are
manipulating in the first place? How much time do they spend putting
it together and re-running each month? It's a great way to blow away
a few days every month. How accurate are their assumptions and
calculations - and on it goes. Sure excel is a great tool but it does
not deliver consistent, auditable and replicatible BI - end of story!
6. Measurement
(ACW) CIO's and business groups want to implement BI across the
organization to drive new efficiencies, but once that decision is
made. The next phase is to establish how to prove those efficiencies
are occurring and that people are embracing the technologies benefits.
(Glen Rabie)
As I mentioned earlier - measuring BI is incredibly hard to do. How
do you measure the value of email within a company? Why bother with
PCs. Simply put - BI tools are enablers - they will become critical
business infrastructure.
7. Executive expectations
(ACW) Often a key driver for a BI project is the executive team's
desire for a sexy (sic) business dashboard. Do many IT managers fear
that the BI rollout will not meet the lofty goals executive have
envisioned.
(Glen Rabie)
The needs of the executive team differ vastly from those of
operational users. In my view it is best to deliver operational
reporting first and then the executive dashboards - problem for the
guy paying the bills I know! However, the reason for this is that if
you deliver high level dashboards to the exec team if the data is
trending the wrong way they will want to drill down for answers from
their staff. If their staff do not have access to the same data at a
lower level - how will they respond? Well basically they will query
the data - the numbers can't be right - that tool is wrong! So it is
a fine line - our approach is to deliver less data initially but
deliver to all segments of the business, so that the executives get
sales data but so do the customer care people etc. That way everyone
has access to the same data; all be it from different views.
8. Organisation Size
(ACW) Some organisations bypass Business Intelligence, in the belief
that their smaller size or lower staff count will not benefit from
business intelligence. They assume that BI is only relevant for
government or fortune 500 companies. What is you take on this?
(Glen Rabie)
Well BI is for everyone. Running a large business or a small business
is the same. If you do not have total visibility of all your key
metrics then you may miss those critical opportunities or risks for
your business. Sure you budgets to implementing BI are going to
differ - but so then will the complexity of your business. For
example a small business is not going to have 100 different data
sources, which means getting something up and running will be a much
lower cost - and the benefits to the business almost instantaneous.
9. Data security and management.
(ACW) Business groups may desire greater freedom of access to company
data. However, IT just see's the problems. Suddenly with the data
aggregation, comes the issues of data cleaning, data partitioning,
extraction from disparate stores and keeping the sensitive data access
controlled.
(Glen Rabie)
Any BI project will come across security issues. If you have a robust
BI platform in place then security should not be a headache. My
number one advice in this area is to make sure that whatever tool you
use it must have row level security infrastructure. You have to be
able to write a single report and share that with many users in the
confidence that they will only see the data that is relevant to them.
10. Data Confidence
(ACW) IT having rolled out the enterprise wide BI project, now
discovers that it must manage the ongoing problem of data trust,
people are making decisions that affect the business daily and those
decisions are being driven / supported by the business intelligence
tools. How will IT guarantee that the reports and dashboard elements,
can be trusted?
(Glen Rabie)
And now for the bombshell - data quality really gets to way much
airplay. It's good for buy-in but really you do not need 100%
accurate data. That is not the role of BI. BI is about trends and
overviews, not transactional accuracy. If your sales trends are
heading south - but a couple of records are inaccurate by 5 or 10% -
what should the exec worry about? Care about the trend of your
business not the quality outliers! However, we all know it is an
issue, and I did touch on this earlier - there are a multitude of
applications out in the business world that allow users to enter junk
data. The options are: one, to educate users on data entry. Make
accurate data entry a KPI so that data is cleaned over time. Use your
BI tool to highlight poor quality data and fix it at the source. Two,
for those with a bigger budget - change your applications so that more
data validation takes place at the front end. Again this is about
fixing it at the source - do not try and clean data continually at the
BI layer. There are better methods for that.
Permission for open release (ACW)
Introducing Business Intelligence appliances across the enterprise
promises a whole new level of data awareness for the staff base, which
can promote new efficiencies, transparencies and open new ways to
target and serve customers. But it still scares some.
Rolling out a quality BI product through the enterprise is not a task
that can be just assigned to a single silo group, it requires
management and work groups to commit to a long term project, it
requires cross group co-operation, data cleaning, data sharing and
most importantly education. Resistance groups can appear during the
project when people feel the challenges out way the benefits to them
or that better reporting may threaten their own jobs; while others may
believe that company data should not be openly available.
To address these blocks and help get BI implementations off the ground
more quickly we have compiled a list of the top ten most common
cultural issues with BI project rollouts. We then asked the CEO of
"Yellowfin Business Intelligence", Glen Rabie, to detail some of his
own company's frontline experiences with enterprise BI and provide
some solutions to alleviate the anxiety.
1. Complexity
(ACW) BI projects bring with them a new set of problems, company data
is generally is disparate systems that must now be linked, data is
often duplicated, data archiving and cleaning become more important,
there are political issues to solve, different hardware and opsys to
consider, which appliance to use and then the massive problem of
educating people. What is it about BI projects that make them so
complex?
(Glen Rabie)
To be honest I do not actually think BI is that hard. The true
complexity lies in a number of items - one, actually defining the
reports and data that people want. Business analysis and really
engaging the end users is critical. Two, data cleansing - many
applications allow users to enter junk - and the BI tool by exposing
data makes this data visible. Now you have to go back and clean all
that up! Lastly, you have the big bang approach. To many companies
feel they have only one shot at a BI project. In my view this is the
wrong approach. Start small and develop an incremental framework for
delivering BI over time. Let you users see what they are getting in
stages and allow them to learn what they actually need. And yes -
give people time to improve business processes to clean up that data.
2. Change
(ACW) This single issue can stall an IT project at any point, people
fear change or perceiving a threat to themselves, whether it results
in more work for them personally, greater scrutiny or worst case make
their jobs irrelevant/obsolete. Business Intelligence tools can result
in a great deal of change - what are the cultural impacts of this
change?
(Glen Rabie)
Like any project there are always a bunch of people that just like
doing it the old way. Their power is derived from being the gate
keeper to data - take that away with a BI tool and you do change their
working lives. The problem with the BI project is that the gate
keepers are critical to success. If they block or attempt to de-rail
the project then there is little chance of delivering a great
outcome.
There has been a tonne of articles written on the blocker so I will
not delve to deeply. However, another more subtle failure occurs when
key users do not get involved in a project due to other higher
priority tasks. For BI to be successful a series of sign-off steps
need to occur to ensure data accuracy and that what will be delivered
will be of business value. If the key internal users do not get
involved and are just waiting for the delivery of the BI project - the
project will fail. And as usual the project team is held
accountable. Drive the change management and really make sure that
all stakeholders are involved and sign-off on every step within the
project.
3. Investment
(ACW) Like any IT project, BI projects require investment in time,
money and human effort. The investment can seem too steep for the
payoff for some.
Why do BI projects suffer from a perceived lack of ROI?
(Glen Rabie)
Well this is the recurring theme of BI. Business users want it, and
yes it does cost money and yet putting your finger on the value of
information and how that translates into accountable business benefits
is incredibly difficult. The way we like to think about it is simple
- imagine working without internet access - in the early days no
conceivable benefit but now, who could imagine a knowledge workers
life without it? Sure you can continue to use excel and cobbled
together processes and save money by not going out and doing that BI
project - but in the long term will your business grow and thrive
using that strategy? Probably not!
4. Just another Buzz phase
(ACW) Like many of the must have technologies that have propagated
through international corporations, from CASE tools in the 80's to
WEB2.0 today. IT managers fear Business Intelligence for the masses
will have limited usefulness and after the initial interest period
will gather dust as people get on with their established ways of
working. What is you view on this?
(Glen Rabie)
I think the opposite will occur. If we look at the history of
business computing the persistent trend is to making users self
sufficient. Lets take Excel as an example. In the early days there
were a handful of excel super heroes in an organisation - now it is
ubiquitous - everyone pretty much knows how to navigate a
spreadsheet. What is lacking from the spreadsheet, however, is the
centralised access to multiple data sources - and that is BI. People
now are starting to want direct access to their data without IT's
intervention. And that is a trend that will not stop.
5. What's wrong with Excel? attitude!
(ACW) Business and IT groups have become used to using the tools they
have at hand. Traditionally Excel is the application that people are
quite comfortable for most of their data manipulation and reporting.
Do IT managers believe it is sufficient for most staff?
(Glen Rabie)
Look it depends - I do not want to speak for all IT managers but I
suppose a large set would feel this way. There are a myriad of
problems about using excel - most of them not visible to management -
and so in that sense not a problem.
Some of my favourites - How did users get their data that they are
manipulating in the first place? How much time do they spend putting
it together and re-running each month? It's a great way to blow away
a few days every month. How accurate are their assumptions and
calculations - and on it goes. Sure excel is a great tool but it does
not deliver consistent, auditable and replicatible BI - end of story!
6. Measurement
(ACW) CIO's and business groups want to implement BI across the
organization to drive new efficiencies, but once that decision is
made. The next phase is to establish how to prove those efficiencies
are occurring and that people are embracing the technologies benefits.
(Glen Rabie)
As I mentioned earlier - measuring BI is incredibly hard to do. How
do you measure the value of email within a company? Why bother with
PCs. Simply put - BI tools are enablers - they will become critical
business infrastructure.
7. Executive expectations
(ACW) Often a key driver for a BI project is the executive team's
desire for a sexy (sic) business dashboard. Do many IT managers fear
that the BI rollout will not meet the lofty goals executive have
envisioned.
(Glen Rabie)
The needs of the executive team differ vastly from those of
operational users. In my view it is best to deliver operational
reporting first and then the executive dashboards - problem for the
guy paying the bills I know! However, the reason for this is that if
you deliver high level dashboards to the exec team if the data is
trending the wrong way they will want to drill down for answers from
their staff. If their staff do not have access to the same data at a
lower level - how will they respond? Well basically they will query
the data - the numbers can't be right - that tool is wrong! So it is
a fine line - our approach is to deliver less data initially but
deliver to all segments of the business, so that the executives get
sales data but so do the customer care people etc. That way everyone
has access to the same data; all be it from different views.
8. Organisation Size
(ACW) Some organisations bypass Business Intelligence, in the belief
that their smaller size or lower staff count will not benefit from
business intelligence. They assume that BI is only relevant for
government or fortune 500 companies. What is you take on this?
(Glen Rabie)
Well BI is for everyone. Running a large business or a small business
is the same. If you do not have total visibility of all your key
metrics then you may miss those critical opportunities or risks for
your business. Sure you budgets to implementing BI are going to
differ - but so then will the complexity of your business. For
example a small business is not going to have 100 different data
sources, which means getting something up and running will be a much
lower cost - and the benefits to the business almost instantaneous.
9. Data security and management.
(ACW) Business groups may desire greater freedom of access to company
data. However, IT just see's the problems. Suddenly with the data
aggregation, comes the issues of data cleaning, data partitioning,
extraction from disparate stores and keeping the sensitive data access
controlled.
(Glen Rabie)
Any BI project will come across security issues. If you have a robust
BI platform in place then security should not be a headache. My
number one advice in this area is to make sure that whatever tool you
use it must have row level security infrastructure. You have to be
able to write a single report and share that with many users in the
confidence that they will only see the data that is relevant to them.
10. Data Confidence
(ACW) IT having rolled out the enterprise wide BI project, now
discovers that it must manage the ongoing problem of data trust,
people are making decisions that affect the business daily and those
decisions are being driven / supported by the business intelligence
tools. How will IT guarantee that the reports and dashboard elements,
can be trusted?
(Glen Rabie)
And now for the bombshell - data quality really gets to way much
airplay. It's good for buy-in but really you do not need 100%
accurate data. That is not the role of BI. BI is about trends and
overviews, not transactional accuracy. If your sales trends are
heading south - but a couple of records are inaccurate by 5 or 10% -
what should the exec worry about? Care about the trend of your
business not the quality outliers! However, we all know it is an
issue, and I did touch on this earlier - there are a multitude of
applications out in the business world that allow users to enter junk
data. The options are: one, to educate users on data entry. Make
accurate data entry a KPI so that data is cleaned over time. Use your
BI tool to highlight poor quality data and fix it at the source. Two,
for those with a bigger budget - change your applications so that more
data validation takes place at the front end. Again this is about
fixing it at the source - do not try and clean data continually at the
BI layer. There are better methods for that.
Permission for open release (ACW)