Components of an effective

Business Intelligence System

To be effective, a business intelligence system typically consists of a number of components that together can be used to create a complete and integrated system. For simplicity, let’s consider a typical business intelligence system as comprising of six elements as follows:

1. Data Access

Business intelligence systems need data and lots of it. This requires gathering it electronically from a variety of sources that will be in different formats and storage schemes, which are both internal and external to the organization. To do this, a business intelligence system will need to be able to ‘understand’ how to read those sources and ‘select’ the data that is required. This will require support for a range of software platforms and some kind of ‘intelligent’ table that describes how data is stored and can be retrieved.

2. Data Model

Once data can be accessed, it will need to be integrated so that it can be compared with other data sets and processed to create summaries, sub totals along with new calculations such as ratios and percentages. This requires the business intelligence system to include a data model that can support business calculations and a way of ‘matching up’ the source data with that model.

Business intelligence models are multi-dimensional in nature. “Multidimensional” describes the way in which numerical information can be categorized and viewed. For example, consider the number 57. The number must be defined to have meaning. In this case it is revenue. It could be further described as having occurred in the West region in the month of June for the year 2008. To define it further, 57 could be described as an actual result for product X.

This example describes six aspects of the number 57. These are known as “dimensions”. The values of each dimension – e.g. east, west, south, north - are known as “members” of the relevant dimension.

The business intelligence data model will be multidimensional; that is each piece of information held by the model is qualified in terms its dimensions and the appropriate member of those dimensions. Advantages of multidimensional systems include simple maintenance - to modify a structure only requires the changing of the appropriate member; and users can view results from any valid perspective – e.g. by product, by unit, by time.

The model will support the generation of new data by either summarising data through the defined dimension hierarchies or through calculations that may go across dimension members.

This capability allows the setting up of allocation rules that, for example, spread the total cost of the marketing department across all sales cost centres, based on the volume of product that was sold by each. Another use of this capability allows the setting up of central drivers that can be used by budget holders – for example, the calculation of revenue by taking the volume sold by each sales department and multiplying it by the price entered by the marketing department.

To evaluate these kinds of rules correctly, the model for the business intelligence system must be able to perform multiple passes of the model. In the previous allocation example, the model must first calculate the total cost of the marketing department before it can allocate the cost, which will then require a second consolidation. These rules can be recursive: that is, the result of a rule may be used by itself in a second pass of the same rule. Without this capability, the business intelligence system model would not be able to cope with allocations, the calculation of minority interests, and the generation of cash flow statements.

Finally the business intelligence system model understands the concept of time. For example, budgets may be entered monthly, cash flows generated quarterly, and actual results reported weekly. Where time matches between versions of data, the model will allow direct comparisons.

A BI model can hold data for any length of time both in the past and in future years, to enable historical comparisons and trend analysis.

3. Data Presentation

This component connects the user with the business intelligence system to display results and to draw their attention to those that are ‘unexpected’. There is no single way in which this can be achieved and so business intelligence systems need to support a number of different presentation methods. These are usually ‘launched’ from a user specific ‘home page’ that lets the user view data in a number of pre-set formats.

The most common reporting methods include:

• Data Grids with colour coded exceptions

• Data sorting to show the top/bottom values

• Charts and graphs – some include more advanced displays such as mind maps to show relationships

• Dashboards where data is shown as a dial or gauge

• Scorecards which convert trend information into colour-coded icons and tokens

• Alerts that trigger when a particular criteria has been met, for example when sales are under budget by more than 10% and at the same time production is over budget by more than 5%. These can surface within a report, on an alert page, sent to the user via email or delivered to a connected PDA device.

• These presentation methods are typically surfaced in a web-browser for easy access by multiple users, with the better ones allowing reports to be surfaced in personal productivity tools such as spreadsheets, word processors and presentation packages, where users can add additional formatting and combine them with ancillary information such as commentaries.

4. End User Analysis

In addition to presenting data in pre-defined formats, a business intelligence system also support end-users who want to investigate a particular trend or variance. This will include interacting with any of the above reporting methods though:

• Rotate/Nest – where the user can ‘swap’ the rows and columns of the report. For example the display may show accounts down the page with time going across, but the user can swap these around at will. They can also ‘nest’ dimensions – for example to have the columns show versions (e.g. actual, budget) within month, or vice versa. Similarly, the rows ay show a particular account. E.g. sales, by product and region.

• Slice and dice – where users can ‘drill-down’ from a summary level to the details that made up the summary.

• Filtering – enabling the user to ‘hide’ some of the detail on the report so they can focus on particular issues

• Drill-through – allows users to go beyond the data model back to the data that came from the source system. This could even be to the source system itself.

• Ad-hoc calculations – where users can define their own calculations. Some systems will automatically handle the distinction between a good or bad variance. For example being 5% under expenses is good and should be colour-coded green, while 5% under the sales target is bad and should be colour-coded red.

• Charting of new data created by an ad-hoc calculation

• Sorting of data to show top and bottom performance values

Many business intelligence systems allow the saving of user driven investigations, sometimes known as ‘personal views’, so they can be re-called at a later time.

5. Security

Due to the type of data held and the numbers of potential users, a powerful security system is vital to control what data users can access and what processes they can perform with that data. Security will typically be set up centrally and then ‘overlaid’ upon existing reports and processes. The security system then ‘filters out’ those things a user is not allowed to access.

This means that when building a business intelligence system, an administrator need not worry about building specific reports/processes for each user as this would make the task of setting up an enterprise wide system extremely complex. Instead they only have to build one set of reports and processes and then let the security system worry about what individual users see.

6. Web Architecture

Finally, business intelligence systems employ a web architecture that allows simple, intuitive access that is independent of machine, location or the technology being used. A web architecture means more than just accessing the system via a web browser. Technologies such as Microsoft’s .Net initiative means that the same protocols used in the web can also be used for other user interfaces – e.g. PDA devices, Spreadsheets – bringing the benefits of a central database and ‘anywhere, anytime’ access to users in the most appropriate form.

The benefits of a web architecture are many and include eliminating the need to maintain end-user software. The web allows enterprise-wide applications that are easy to maintain.

The architecture of a business intelligence system is often hidden from end-users, but it will have an impact on the maintenance of a business intelligence solution and the type of analyses that can be effectively supported.

It is not sufficient for business intelligence systems to have most of the features discussed above because the benefits of one feature may not be fully realized unless it is accompanied by others. For example, the web by itself will not make a system easier to support unless it is also accompanied by a central database and end-user analysis.

It is only by taking all these capabilities together that make a business intelligence system easier to set up, maintain, and able to cope with the on-going needs of end-users.

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Business intelligence vendors often portray their solutions as being an elixir that will solve a whole range of organization woes from helping them to identify ‘gaps’ in the market place through to helping them to sell more. But like the elixirs of the Dickensian age, software by itself isn’t the solution although it can be a catalyst that will help organizations think more rationally about the challenges they want to address.

One business intelligence vendor claims its products as ‘Making sense of data’ but this too is naïve at best and misleading at worst. For data to make sense it has to be placed in context, which means it needs to be fully qualified with nothing missing.

For example 42 by itself is just a number, which we can qualify by saying it represents $42 profit against a budget of $40. But this too can be very misleading even though it sounds like a good performance. For this data to ‘make sense’ in an organizational context, it has to be further qualified by comparing it to, for example:

• How much profit competitors made in the same product/market/location
• The size of the market opportunity
• Whether the time and assets employed by the organization in generating this performance would have been better placed elsewhere,

It’s only when management have all the facts about the drivers of performance that they can begin to ‘make sense’ of the data presented. And once sense has been made, to use this data for making business decisions, organizations need to know about the future of the market, competitor actions, and their own capability to address that market and whether it’s where they want to go.

To meet his need, business intelligence companies must supply software tools that work with good quality data that is timely and in context – otherwise their tools will mislead those who use them and the way they interpret results coming from them.

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The outlook for companies operating in the business intelligence market (BI market) over the coming years is very positive.

According to Gartner, sales of BI systems will continue to grow from an estimated $5.8billion in 2008 rising to $7.7 billion in 2012. They also reported from a survey of 1,500 CIO’s that business intelligence, or BI ,is their top priority and has been for the last 3 years. Dan Sommer, senior research analyst at Gartner, commented that BI seems to be “recession proof”.

The main reasons for this growth are:

• Organizations have massive amounts of data stored in transaction systems that they want their managers to utilise in decision-making. It is estimated that only 20% of those who would benefit from BI have access to it.

• Typical reporting systems in use are still seen as being too inflexible

• There is recognition that BI is a key factor in driving business effectiveness by allowing managers to see what factors drive performance

• More people within an organization are making decisions so BI can’t just be for a select band of managers – it’s required for users at all levels.

• Organizations want a consistent, standardized way of analyzing data, however BI has typically been implemented as a departmental applications. To make truly effective business decisions requires data from all aspects of the business and the market place to be integrated and presented in the right context and in a common format.

So it seems that BI has a solid future – but what is the best way to use it, how do find out it’s true worth, and how does an organization go about developing a BI strategy? These are questions that we shall address in this sequence of postings on this web site and blog.

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The number of business intelligence (BI) companies that could be considered key players has significantly reduced in recent years. This is primarily due to market consolidation.

By 2005 the consolidation of BI and corporate performance management (CPM) companies had started. Over the next few years there would be a dramatic change in the BI/CPM vendor landscape with the typically larger ERP/Database vendors buying the smaller niche BI / CPM players.

The reasons for this consolidation are:

• BI, enterprise resource planning (ERP) and databases are complementary products. As the ERP/Database market reaches saturation, these vendors are looking for something to sell to their large installed customer base. Incremental sales are much easier and more profitable than selling to new customers.

• BI/CPM market place is growing faster than the database/ERP market. However, the sales of BI products from the ERP/Database vendors had not been as good as the niche vendors. There was a growing recognition from some of them that the BI market prefers ‘Best of Breed’ than ‘Home Grown’ business intelligence companies

• Niche vendors are much smaller and can’t afford the investment needed to stay on top as business intelligence companies in the BI/CPM market. In comparison, the ERP/Database vendors have plenty of resources making the smaller niche vendors attractive investments.

In the period 2005 - 2006:

• Geac, an ERP vendor, acquired Comshare, one of the pioneers of EIS and CPM systems, who was then acquired by Infor, a private equity firm specializing in ERP systems.

• Microsoft acquired ProClarity a niche business intelligence reporting tools company

• SAP, the largest ERP company acquired Business Objects a leading business intelligence company that had only just acquired SRC a niche CPM vendor. SAP then bought Ourtlooksoft, a relatively new but fast growing CPM company, along with Cartesis a niche CPM company, ALG a leading ABC/ABM software company and Pilot a niche BI company

• Oracle one of the largest database companies acquired Hyperion who at the time was the leading BI application company and Siebel who dominated the CRM market place

• Cognos a leading business intelligence company acquired Applix a niche OLAP company but was then itself acquired by giant IBM.

By Mid 2008 the landscape had changed so that the top four ERP/Database vendors (SAP, Oracle, Microsoft and IBM) now virtually owned 2/3rds of the BI market, compared with 1/3rd three years earlier. From a customer’s point of view, the allure of this consolidation is seeing business intelligence companies and vendors who can (supposedly) provide truly integrated applications for all their Performance Management needs. However, the reality is somewhat different as integration of these very different products will be a major challenge for these vendors for many years to come.

The post following this one discusses the current market status and outlook for business intelligence companies.

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As hardware costs plummeted and storage capacity improved during the 1990’s, there was an explosion of BI software solutions. They all claimed to provide ‘Business Intelligence’ that would help organizations be more profitable, more efficient, that would increase sales and beat competitors.

Of course those claims don’t add up if your competitors were to also use the same solution, as someone, by definition, would be the loser. But this didn’t seem to matter, as the take-up of systems became big business.

As with any tool, end-users will always find ways of breaking the design limits such as the volume of data that can be held, the number of people wanting concurrent access, or the kinds of queries they want to perform.

While developing System W, one of the leading OLAP technologies of the 1980s, Comshare surveyed potential users who said that the maximum number of records they would want to analyse would be around 1 million. So they designed the product to handle 10 million records, but within one year of release due to the increasing availability of data, users were regularly analysing 100 million records!

This was caused in part by the introduction of ERP systems that generated colossal amounts of data. Users also recognised that to make sensible decisions they had to combine GL data with a plethora of other internal systems ranging from HR through to sales and production forecasts. To cope with these large volumes of data, data warehousing technologies were developed to collect and re-organise data into a format acceptable to BI technologies.

As the cost of computing came down and the introduction of low-cost, high-volume networks became more widespread, the number of users (and the subsequent volume and complexity of queries) dramatically increased which again challenged the capabilities of BI systems.
(Interestingly, in the last Very Large Database Survey carried out in 2003, the amount of data available for decision-making exceeds that consumed by transaction processing. France Telecom users were reported to have access to over 29 terabytes of data to make a decision. Try analysing that in a spreadsheet!)

It wasn’t only the technology systems that found this explosion of data difficult. Users were also overwhelmed by more data than they could handle and reporting tools that simply regurgitated the data that was entered into them, were no longer good enough.

To make sense of this data, EIS solutions (now meaning “Everybody’s Information System”) were developed to access the new storage schemes to summarise and produce meaningful results from massive amounts of data in ‘seconds’. At the same time, the adoption of world-wide network capabilities such as the internet, freed users from their location and their workstations. But to take advantage of these developments, older generation systems had to be replaced by newer ones, which were then distributed to more users, thereby greatly increasing the cost of IT to an organization.

By the year 2000, BI had been transformed from a niche, analytical tool used by a few people within large companies, to the generally accepted way for management of any organization to review operations and support business decisions. However, its use in supporting decisions was just as varied as the number of vendors, and the true value that users were obtaining was in doubt. It doesn’t matter how good a tool set is, if the person using it doesn’t know how and/or the quality of the material being used is poor. Similarly, the best craftsman with the best materials can still fail to produce a good product if the toolset is blunt, broken or incomplete.

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The term ‘Business Intelligence’ (BI for short) is an established business term that sounds important and yet most people would find it hard to define. In common with many other acronyms, BI can mean different things to different people, with the result that its meaning is often vague and uncertain.

BI was first used the 1980’s by Howard Dresner, Director of Research for IT analyst organisation Gartner, who defined it as:
“The systems that help decision-makers throughout the organization understand the state of their company’s world”

“A set of methods that support sophisticated analytical decision-making aimed at improving business performance”

In a later white paper entitled “BI: Making data make sense’“, he went on to say:

“Ignorance is the greatest threat to modern business. The risk of not knowing is immense. Now is the time for all enterprises to raise BI (Business Intelligence) to the level of a strategic initiative.

The value to business is proven. With the right mindset, methodology and technologies, success is likely”

From this we can gather that BI is not a product or a definable method but more of an umbrella term for the way an organisation understands and makes business decisions.

Those that do this well will have a business advantage over those that do not. Although BI is not a technology, computer systems perform a crucial role as it is only they that can perform the analyses of large data volumes that then underpin a business decision.

It was, in part, Gartner’s use of the term supported by their many white papers that led to BI’s rapid adoption by both technology vendors and the marketplace. But in many ways it wasn’t anything new, as organisations had been increasingly trying out new technologies aimed at analysing and sifting through ever-increasing amounts of data that was becoming available.

For example, the late 1970’s saw the development of the first multi-dimensional database systems, now referred to as OLAP and a key component of any BI system, from pioneers Express (later acquired by Oracle) and Comshare (current owners Infor). These systems were aimed at end-users and allowed them to look at data from different perspectives such as by client, by time, by product. They also supported ‘slice and dice’ through different levels of data to create new views without having to involve programmers, and that allowed users to ‘drill down’ and ‘drill through’ to underlying detail. (There are many terms such as ‘drill down’, ‘drill through’ used in reference to BI).

At the same time as these developments in database technology, Executive Information Systems (EIS) with their graphical user interface became popular. Rather than having tabular reports for users to go through and glean information, data was presented as dials and gauges, as well as the more traditional charts and tables. They introduced the concept of ‘hot spots’ that allowed users to ‘jump’ to different reports and analyses, supported the sorting of data and even the generation of new information by allowing users to perform ad-hoc calculations between rows and columns. The more advanced systems introduced ‘alerting’ technologies that would sift through the underlying data and bring pre-defined exceptions to the users attention, but without them having to wade through enormous amounts of data.

Because of this flexibility, users were now more self-sufficient and didn’t need to go back to a hard pressed IT department and wait for them to create new reports. Well that was the theory, in reality it showed up two shortcomings: The first was that the data users wanted was either absent or incorrect, and second that users really didn’t know what to ask for in the first place. Despite this, EIS soon became the standard way of navigating through corporate performance data.

Software firms with an operational research background bias embraced these technological developments and started to apply statistical techniques to uncover relationships – a key component of data mining. This included time-series analysis to determine trends and seasonality, and regression analysis to reveal dependencies between variables. In this way data was used to predict future results and then delivered in the most appropriate ways so that management could make informed decisions.

BI was a natural way of combining these existing technologies along with ancillary capabilities such as data acquisition tools, into a single term that could be used to help managers ‘make sense of their companies world’.

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“What is business intelligence?” However, you define it, business intelligence (BI) promises a lot, but despite over 30 years of development, many organisations still struggle to fully support effective decision-making. Research conducted by the Hackett Group, the only organization that has a global benchmark on the way organisations use technology to support performance management, found:

“Most organizations face significant process challenges in delivering the right information to the right people at the right time. The focus is wrong, cycle times are too long, detail is overwhelming and analytical tools are weak.” Best Practices in Planning, Budgeting and Management Reporting by David Axson

Over the next month or so, the Business Intelligence area of this web site will explore just exactly what is business intelligence. We will aim at organizations who have either become disillusioned with BI, or who are not quite sure what BI is and whether it is worth the bother. Our aim is to help you decide when and where to use BI technology, its pitfalls as well as the potential benefits it can bring. We will also look past the marketing hype of BI software companies, and show you how to ensure that BI initiatives deliver real organizational value.

The best place to begin gaining a comprehensive understanding of what is business intelligence, is to first understand “Why business intelligence” by considering the evolution of BI.

On with What is Business Intelligence . . .

Back to main Business Intelligence Reporting page

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  SQL Business Intelligence Reporting

  like you’ve never seen before

RSVP Reporting Software for Visualization and Performance is a fully integrated, dynamic data visualization and business intelligence reporting tool for sql databases and other relational and OLAP data sources.

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Data visualization capabilities compliment and enhance the SQL server reporting and include a broad range of relational and OLAP presentation elements, such as the unique 3-D data representation allowing display of up to 4 items of data per business component.

SQL report publication and management is easy as RSVP is designed from the ground up as an integrated viewer, server and administration tool for sql business intelligence reporting.

A wizard-driven Report Administrator allows the admin user to modify SQL server report layouts, security (who accesses what reports) and publication (method of retrieval). One-step publication ensures that all sql business intelligence reporting users view the same data at the same time and are always on the same page. One of three built-in SQL server report navigation mechanisms is assigned to SQL report viewing users based on personal preference. As a single software product RSVP is easy to deploy, maintain and use.

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  SQL business intelligence reporting

  designed to engage users

Designed specifically to engage users and ensure adoption across the entire enterprise, especially in a Microsoft SQL business intelligence reporting environment – SQL server 2005 reporting or SQL 2008 reporting - RSVP Reporting addresses the needs of information consumers such as executives and business managers, as well as information producers such as business analysts, IT analysts and data architects.

  SQL business intelligence reports

  in dramatically reduced design time

Provide SQL server reporting services in a fraction of the time it previously took. With pre-built objects including charts, gauges, dials, data connectors, you can create dashboards connected to live data in minutes rather than months, giving you stunning sql business intelligence reporting in a fraction of the time. You also have the added advantage of being able to present relational and OLAP data source data on the same reports.

RSVP includes built-in designer features such as report templates and styles. As an integrated solution, it ensures that the report elements are 100% compatible and consistent with your SQL server reporting.

Wizard driven SQL report creation, modification and publication all from a single tool interface allows both the rapid creation and deployment of reports.

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  Powerful SQL Report Deployment

Because RSVP has been designed from the ground up as an integrated report viewer, server and administration tool for sql business intelligence reporting, it permits the easy publishing of SQL reports.

RSVP reporting has three report navigation methods (Executive Console, One Touch Reporting and Tab and Tree). These choices allow the most suitable mechanism for navigation of reports to be assigned to individual users of your Microsoft SQL business intelligence reporting system.

RSVP also comes with an inbuilt Report Administrator that allows the administrative user to modify SQL report layout and data sources, as well as security (who has the right to view individual reports) and publication (how those with permission to view a report can navigate to it)

Reports are saved directly to the RSVP Report server when they are published. This means that as soon as the SQL business intelligence reporting designer publishes a report all SQL report viewing users will see the new report layout and data

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  SQL Report Navigation

Publishing SQL reports is easy. Making it easy for the user to find those reports is what RSVP does best. There are three built-in Report navigation mechanisms.

• Executive Console

• One Touch Reporting

• Tab and Tree

Each Report Viewing user is assigned one of these mechanisms to view reports. All three mechanisms are capable of presenting the same reports and a single report can be presented using one or more of the SQL report navigation mechanisms. Thus the report navigation mechanism assigned to an individual user is one of personal preference.

  SQL Server Report Security

RSVP uses windows integrated security to verify the identity of the user accessing the system.

Once authenticated the reports that a given user is permitted to view are collated and presented to the user.

The integrated security for both data access and report viewing ensures that restricted data stays restricted.

  SQL business intelligence reporting

RSVP Reporting for SQL brings the power of SQL Server 2005 reporting to the business user. From real time reporting to business intelligence reporting, from OLAP analysis and trend analysis to corporate performance management, RSVP compliments and SQL Server 2005 reporting as well as SQL 2008 reporting to deliver next generation applications.

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 NGM Coburn

IntelligenceBusiness.com

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RSVP’s Executive Console:

Browse key reports and with one click build a personalized newspaper of business headlines, analysis and financial reports.

Today every business and organization needs to be able to unlock the power and value of the data and information held within its business systems. Getting the right information, to the right people, in the right way and at the right time, has been the value proposition of Business Intelligence for many years. Companies are increasingly, looking to BI to provide them with the visibility and insight that can be a source of competitive advantage.

Yet despite such a strong business case for investing in Business Intelligence, it has not always lived up to expectations.

Why ? - Lower Usage, Less Value

Information only becomes valuable when people use it to understand, interpret, collaborate and make business decisions that improve performance. But often executives and business users can’t quickly and easily find the relevant information or reports they need to assess performance and make decisions.

Executives and occasional users don’t have the time to develop specialist skills to use existing BI systems or see any benefit of spending the time to re-train and keep up with changes. As a result they quickly revert back to what they are familiar with – spreadsheets and charts. Traditionally BI solutions have not adequately engaged users and provided them with an experience that is significantly better than what they have had in the past.

It is no longer good enough to have easy to use Business Intelligence. People have to want to use their BI applications.

BI that People will Want to Use
RSVP Reporting delivers a next generation user experience that is more interactive, engaging and rewarding for your business users.

Adding Real Value to Information
RSVP Reporting uses animated, 3-dimensional objects for superior visualization and interaction, allowing users to better interpret information. This leads to greater understanding and insight that drives better decision-making.

Releasing the Power
RSVP Reporting releases the power of online, multi-dimensional analysis, but eliminates the complexity for the end user. Using the Query Builder’s drag & drop, point and click features, executives, managers and information consumers can slice, dice, pivot and query information and reports with ease.

Greater User Adoption
Getting people to want to use your BI applications and reports, adding value to the information through advanced visualization and providing powerful, yet simple to use analysis tools leads to higher rates of adoption right across your business.

Adaptable to Individual Needs
RSVP Reporting adapts to the individual needs of your users, offering the flexibility to create BI applications, online or printed reports that address specific line of business or industry vertical scenarios. Our Report Designer offers pre-defined objects, simple drag & drop features and preview editing for the rapid creation of reports, without the need for any specialist skills.

Next Generational Technology
Built on the .net Framework and Web Services, RSVP Reporting is a future proof solution, freeing your IT Department from backward capability issues, allowing them to quickly adapt to changing business priorities and needs.

Proven Supplier
IntelligenceBusiness.com’s RSVP Reporting is the culmination of 20 years of experience delivering business intelligence and financial analytical applications to corporate clients.

Hit the download button on the top right hand corner of this page to get a free license and begin reaping the benefits today.

NGM Coburn, IntelligenceBusiness.com

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So many business intelligence application implementations fail because people fail to avoid one or more of these red flags. As a wise person once said, all you require is “an uncommon degree of common sense”.

1. The front end user interface is just as important as data and data design. There’s no point in having a technically brilliant business intelligence system if nobody uses it.

2. Beware the spreadsheet look and feel trap. Some business intelligence applications are designed by power users who only think spreadsheets. The spreadsheet look and feel is not sufficient for many users on the web.

3. Simplicity and ease of use are key but not enough. Great looking formatting and easy navigation do not, of themselves, empower users to make better and faster decisions. Business intelligence applications must be engaging if they are to keep business users interested.

4. Everything changes. It is risky to assume that the business intelligence user knows what he or she wants. In the design phase, users define what reports they require and how they wish to access them. However, these requirements will rarely satisfy the user after six months of use. It is essential to plan for a more dynamic application allowing for growth and change.

5. One size doesn’t fit all. In business intelligence implementation, one view never fits all. It is important to allow for individual or group-specific Business Intelligence needs.

6. Reports should be easy to find. Do not assume that users will relate to report names. They won’t. Users remember reports and analysis visually and not by the name associated with them. Using a menu of report pictures is much more effective.  Also, it is a mistake to assume that users are prepared to hit a long sequence of buttons before finding their desired report or information. A typical senior business user only has patience for a few clicks (Rule of thumb: 3 strikes and the application is out!)

7. Don’t overuse the technology and be careful of chart and gauge overdose. A high level of user adoption won’t be achieved simply by adding charts and gauges to spreadsheet styled grids. The same applies to making the business intelligence application engaging.  Instead introduce highly visual guided analysis tools such as RSVP’s One Touch Reporting or 3D-City.

In summary, the top priority is not to get the technology right. The top priority is to implement a business intelligence application that will engage users in such a way that they will use it and will continue to derive value from it.

NGM Coburn

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