The architecture ensures that the processes run smoothly and that they are properly aligned. The Business Intelligence architecture forms the link between the processes we described earlier and the applications and Business Intelligence tools. Without a well thought out architecture, we cannot properly organise the processes of the Intelligent Organisation and consequently, we cannot apply information and knowledge in the way we should.

The Business Intelligence architecture applies to all processes: from registering and collecting to distributing and responding. It should ensure coherence between financial and non-financial information, between internal and external information, between KPIs, viewpoints and processes, and between applications and tools.

It is – among other things – this holistic approach that makes that Business Intelligence can deeply integrate in the business operations and that the organisation can perform better persistently. It is therefore important to both develop and maintain a Business Intelligence architecture, which perfectly fits the organisation and its business processes as well as the existing IT infrastructure and which is based on the desired indicators and viewpoints.

An architecture is necessary to ensure that both the Business Intelligence system and the Business Intelligence applications are (and remain) easily expandable, maintainable and flexible and that they do not cause major delays during expansion. The architecture should also prevent the system from instability. We should be able to easily add new indicators, reports, sources, instruments and data. After all, in today’s dynamic times, our information needs change much faster than before.

Definition of (software) architecture (IEEE 1471-2000) “Architecture is the fundamental organisation of a system embodied in its components, their relationships to each other, and to the environment, and the principles guiding its design and evolution.”

A proper architecture can also ensure that information and knowledge are in fact reliable, for example through automatically checking the quality of data according to a fixed pattern and then – if possible – choose to either correct or reject the data. Designing a good architecture is an art in itself: thought and actions should go hand in hand. After all, we cannot simply think of everything on paper. We also need to go about things pragmatically in order to verify our assumptions in practice at an early stage.

We will look at the basic principles (successively) that rule the Business Intelligence architecture. We will also discuss the main pillars of the ideal architecture of the Intelligence Organisation. These are:

• Data warehouses and ETL: collect, filter, cleanse, integrate and aggregate data in order to increase our chances to actually find information and knowledge.
• Portals and reflex BI: provide the possibility to directly apply and actually use information and knowledge in both the business processes and the systems supporting the business processes.
• Metadata: can be considered as the glue that holds all the Business Intelligence processes, applications and tools together allowing us to obtain an integral and reliable picture of business operations, at any given moment.

Metadata ensures that the ideal architecture can in fact support the Intelligent Organisation from A to Z: from integral observation to automatic knowledge-driven responses. Although we speak of an ideal architecture, in practice a data warehouse is not always an option due to the costs involved.

A collection of information cubes may also suffice during the initial stage of developing an architecture. Although this is not ideal with regard to maintainability, response times and accuracy, what matters is that the management information is actually put into use by both managers and employees. Note that when we speak of data warehouses, these may also be considered as a coherent collection of information cubes.

The world of Business Intelligence houses many different viewpoints with regard to architecture and the methods of data modelling the data warehouse (Inmon, 1996; Kimball and Ross, 2002; Kelly, 1997; Van der Lek, 2003). Many of the differences in opinion concerning the architecture of data warehouses turn out to be theoretical though and unfortunately, there still seem to be organisations are guided (strongly) by one specific theory in this field. These organisations go after some guru without knowing exactly what is at stake.

For that reason, we still regularly come across Business Intelligence systems and data warehouses that were designed by the book but hardly provide any meaningful reports. Worse even is the fact that some organisations seem to be proud of this – not so much of the reports, but of the fact that they did things by the book. Passionned Group covers the architecture from a practical point of view and provides basic answers to how and why. It also describes the purpose of the various elements of the architecture. In this way, it is up to you (the reader) to judge what is applicable for your specific situation and organisation.

Testimonials of the delegates

In New York, March 2013: average score 4.8 out of  5

“Enjoyed the interactiveness of the master class, good level for my understanding, we are just getting started”

“The training met the objectives defined, I learned new insights of Business Intelligence that I previously did not know. Very informative. Thank you.”

“Very organized, good pace, calm/cool delivery, instructor is very “thoughtful” and encouraged participation, would be pleased to attend again.”

“This Business Intelligence training exceeded my expectations. I was concerned it would be too technical for me, but it was broad foundational enough and I learned a lot. I wish I would have registered a few more of the leaders of my team.”

“Excellent. It provided me with an understanding & best practices and approaches that help me feel that a Business Intelligence strategy + a DWH are within reach.”

“It is very informative, knowledgable and insightful”

“Well presented with targeted focus”

Register for the Business Intelligence training in London or Amsterdam (India and Australia are yet to come).

In Amsterdam, September 2012: average score 4.2 out of 5

“Training was good. It gave me a good insight into what I should look for in terms of expanding BI within my organization.”

“It was a very good Business Intelligence training. I like the way that the teacher incentive to all attendees to participate.”

In Singapore, April 2013: average score 4.3 out of 5

“Good overview with focus”

“Excellent step-by-step guide in building a sustainable BI framework”

“Would like to attend to other training in detail on the same topics”

“Good sharing with industry peers and from the trainer”

“Very good to understand & I will use examples from the course to apply to our business scenario”

Register for the Business Intelligence-training in London or Amsterdam (India and Australia are yet to come).

Business Intelligence is used throughout the company

Business Intelligence is used throughout the company at all management levels and by almost all humon ‘processors’. A good example: store managers check their state of affairs every single morning. Ahold’s differentiation strategy also leans heavily on Business Intelligence.

Albert Heijn, a Dutch supermarket chain, for example, follows a differentiation strategy whereby customers are approached in different ways: from the large XL store format with over 3000 m2 of retail space to the smaller AH to go with 200m2 space at the most. This strategy is reflected in the product range decisions – often made almost fully automated – whereby suppliers are the ones that ‘pull the strings’ operationally.

Ahold learns from its customers

Ahold learns from its customers and structurally shares that information with suppliers. Suppliers are directly connected to Ahold’s data warehouse and so have access to information about completed cash register transactions.

Based on that information vendors can take immediate action for example through refilling stocks at Ahold’s central distribution centre. Involvement of supermarket staff is not even needed then. This far-reaching form of collaboration within the supply chain based on a complete Business Intelligence system is unique and earns the company a lot of money.

The way in which Ahold has adopted Business Intelligence is rather impressive. “Our retail formula is in fact about the customer being able to find the right product at the right time and place. The figures in our Business Intelligence environment confirm this. Our operational process is managed by facts. The good thing is that today we can for example also report the number of ‘no-sales’ due to empty stocks, without having to register this separately”, said Egbert Dijkstra, former Business Intelligence director at Ahold.

Ahold can be seen as a highly ‘BI mature’ organisation

Governmental organisations sometimes take advantage of the system too: a few years ago for example a police unit rang Ahold – in the context of a serious crime case – to ask if they could look up if anyone in a certain period had bought twenty garbage bags on one and the same day. In short: the information within the Business Intelligence system is priceless for many employees and managers. Ahold can be seen as a highly ‘BI mature’ organisation both in terms of their Business Intelligence strategy and the execution there of.

The market-driven approach consists of two steps:

• Market research and tool selection: analytical applications that are available in the market are being reviewed based on a number of (technical) selection criteria. The main criterion regarding the mapping of information needs is to see whether both the application and its indicators sufficiently match the organisation’s business operations and critical processes.
• Choosing and modifying: once an organisation decides on which industry specific application to use, the indicators often need modification as they should be tailored to organisation-specific needs.

The market-driven approach can be costly but only when the application does not fit with business operations properly, or when it proves to be rather difficult to modify the key performance indicators – and the required data connections to the proprietary source systems. If this is the case, the organisation will probably need to identify its information needs in other ways to then implement this in customized Business Intelligence solutions.

Another risk is that the organisation becomes too fixated on the functionality the application offers and consequently rather blindly trusts the KPIs without giving thought to how they should be used and implemented in the business processes.

Ultimately, information needs to be used in some way. It is therefore sensible not to use analytical applications blindly without modifying them first, especially since competitors may be focusing on similar indicators already. It is thus important for an organisation to differentiate itself from its competitors by ensuring that the application is completely in line with both the strategy and the key processes.

Business Intelligence goes beyond that: ultimately, the information must contribute to a range of aspects such as a higher profitability, better products or faster processing times, all depending on the goals and ambitions. What can or must organisations do in order to actually reap the fruits of their investments in Business Intelligence?

As evidenced by the Business Intelligence cycle (see picture above) organisations must not only register, collect and analyse initial signals, they must also adequately respond to those signals. Exactly that is still lacking in many organisations: informed decisiveness and inspiring leadership.

In today’s economy (and society) the ability to respond quickly and qualitatively is vital. With the aim of well functioning sensors and processors organisations may be able to know very quickly (within a day or even faster) that change is needed (sensitivity) but knowing alone is not sufficient if it then takes the organisation another six months to actually change (adaptive capacity). Let us define these two notions in more detail:

• Sensitivity: the extent to which an organisation and its employees are sensitive to signals that are relevant to the business and the degree in which they consciously notice these signals and where possible keep them in sight using all senses. Sensitivity is the intrinsic (sensitive) collective organisational capacity to quickly notice relevant signals on a structural basis.
• Adaptability: the extent to which an organisation and its employees are capable of quickly adjusting to environmental changes or necessary changes within the organisation, based on the observed signals. Adaptability is the intrinsic (adaptive) collective organisational capacity to quickly implement desired changes in a structural manner.

If the organisation’s sensitivity and its adaptability are not properly aligned this may lead to employees unintentionally developing a certain laxity towards using the relevant information made available by Business Intelligence simply because the organisation takes too long to actually adjust. Moreover, the necessary change might come too late because rivals have long continued or have shifted their focus on other things.

In short: properly oriented sensors (KPIs), reliable processors (data warehouse, OLAP and people) and effectors – allowing quick responses – together form the inextricable trinity of the Intelligent Organisation.

It is thus crucial that Business Intelligence integrates with business operations. If this is not the case, many initiatives and investments in Business Intelligence will turn out to have been worthless.

The Intelligent Organisation should use Business Intelligence to ensure that information can easily – as a smoothly running continuing process – lead to improved performance and development of the organisation. In this chapter, we briefly examine the most important preconditions for the adaptive customer and process-oriented organisation:

• Necessity: first of all an organisation should examine whether it is indeed necessary to put effort in becoming an adaptive organisation.
• Expertise: the processors within the Intelligent Organisation need to be experts. They should have very good knowledge of business operations, business processes, customers, mission and strategy, the range of products and services and of the markets in which the organisation operates or intends to operate. This answers the question as to where the organisation can quickly adapt in order to permanently perform better.
• Organisational structure: the organisational structure should increasingly support collaboration between competent employees allowing the organisation to quickly and properly adapt. Information technology often plays a decisive role in facilitating an adaptive customer and process-oriented structure.
• Social infrastructure: we must impose new (or different) requirements on both managers and employees so to enable them to actually use information and knowledge to improve performance.

Besides cultural and behavioural changes the so-called Plan Do Check Act (PDCA) cycle plays an important role in achieving this. Both managers and employees should start acting differently: more goal-oriented thinking and reflection (plan, act), communicate with each other about figures (check) and act in accordance with the figures (do).

With Business Intelligence, the people within an organisation can – and must – often work more autonomously. However simultaneously collaboration should improve too.

This is easier said than done, especially since it is often thought that an Intelligent Organisation simply is the sum of the intelligence of its employees. “Sometimes it seems as if the number of intelligent employees is inversely proportional to the intelligence of the organisation” says Egbert Philips, former director of strategy of a large dairy company.

The social infrastructure of a smart organisation should ensure that the whole is much greater than the sum of its parts. This could mean that there proves to be little if any synergy between those parts and that it is desirable to dispose of them.

Creating an adaptive organisation does not have to involve purchasing all sorts of new tools. To the contrary: it is about the ability to smartly and logically merge, organise and combine existing resources, about unlearning certain behaviour and about dismantling rigid structures in order to enable the organisation to become agile and to respond faster. The ultimate goal is to develop a customer and process-oriented organisation with a capacity to quickly respond to changing market conditions.

Learn how to succeed with Business Intelligence in our unique Business Intelligence Training which is organised in New York, London, Amsterdam, Singapore, India and Australia.

Reliability of data and calculations

The reliability of information largely depends on the quality of the underlying data and more specifically on the accuracy of the calculations that are stored in the Business Intelligence system. If those are accurate, we may assume that the information is correct too. The phenomenon of internal duplicates is a good example of such problems with data quality: details for one and the same customer, for instance, have been registered in the source system more than once with slightly different spelling.

When we start using Business Intelligence such duplicates will come to surface – it might take a while before the actual scope of the problem becomes visible – and can then be removed from the source system.

Preventing errors

We should also take into account the errors people tend to make while interpreting and internalising data and information. Business Intelligence tools can ease this pain in several ways (Isenberg, 1984; Van Beek, 1999) for instance through showing the same information from different angles or perspectives, or by designing the system in such a way that searching for ‘proof to the contrary’ is encouraged. Furthermore, Business Intelligence often provides an integral picture of business operations and indicators are interrelated.

By enabling the system to include those interconnected key performance indicators in a single report, users can immediately check whether these relations are correct, for example through combining market share figures with their own sales figures and with information on sales figures of competitors. Through imposing strict requirements on the quality, actuality, tempo, coherence and visualisation of information, Business Intelligence contributes to preventing errors in other areas as well.

Above all this, people should be aware of the potential errors they can make and therefore should proactively revise, reassess and check information in order to create (more) reliable information and better knowledge.

Actuality and refresh rate of information

Stakeholders can be ‘on top of’ information if its refresh rate is optimal. Both Business Intelligence and learning processes work most efficiently when the time span between the action itself and measuring its performance as well as adjusting the action is as short as possible (Den Hertog and Huizinga, 2000). This principle is more effective if feedback about their performance is directly addressed to the employees – and Business Intelligence facilitates this – instead of via executives.

To avoid unpleasant surprises, the refresh rate and timing of reports must match the frequency and duration of activities within the business processes. An organisation, which handles hundreds of orders per hour, does well to refresh sales reports on a daily basis (or even more frequent) and to display these daily or even hourly. However, there is no need for an account manager who visits four or five customers per week on average, to monitor the number of visits daily.

Fast response times of Business Intelligence tools

The Business Intelligence tools must ensure that information is quickly and timely available to processors within the organisation. The system’s response time is of particular importance for managers since they often have little time and like action and liveliness. Three particular actions are associated with the requirement of rapidly retrievable information: finding the report, finding information, and interpreting information.

We leave out the phenomenon of interactive analysis (OLAP) whereby users can browse through data and casually surf the data ocean even though for these activities a rapid response time is often a necessity. A report that contains the required information should be able to show that information within 2 to 3 seconds after its been clicked on, but that specific reports first needs to be located. Once the report has been read, it has to be interpreted.

Storing information

In some cases, information is not immediately ‘actionable’ because an organisation perhaps needs some additional information to be able to make a proper decision. If this is the case, the organisation should be equipped with a memory in which they can temporarily store the information so that later, when the additional information is received, the decision can be taken rapidly.

In many organisations, the explicit storage and sharing of (newly formed) knowledge for clear decision-making is not common practice yet. What we do see is (too) many static dashboards and reports that offer hardly any (if any) options to attach a story to the information. This is a missed opportunity because the story behind the figures is often much more interesting than the figures themselves.

Business Intelligence can facilitate this aspect by temporarily storing information, which indicates a certain problem but still awaits additional information, in specifically designed place within the Business Intelligence system. For this to be effective it is wise to create an option on the dashboard which allows for placing notes and doodles with the relevant indicator and so create a an action and decision log.

The health care group consists of ten care facilities, all of which have a considerable degree of autonomy, however more and more care processes now need to be standardised. A few years ago the group felt compelled to implement Business Intelligence-software to greatly improve sensitivity on both strategic and operational level.

In close consultation with its users, they developed ever-new combinations of data enabling for rapid analysis of the modernisation of the group as a whole and the care processes in particular. Some 700 users now had ready-to-use reports and analysis on cost price calculations, in and outflow of clients, medication usage, incidents and benchmark figures at their disposal.

These data are not isolated. Instead they are supplied from an organisation dashboard together with a set of coherent indicators. By continuously focussing on quality, performance improvement and the client (whom is being approached as a customer), the care group has proved that Business Intelligence can play an important role and has succeeded in Business Intelligence permeating the entire organisation.

It is now being used as a strategic ‘sales’ tool to attract new institutions (and customers). “The success of this Business Intelligence application is not so much due to the advanced technology”, said the CTO. “Instead we consider the promotion of a culture of openness about all ins and outs; the allocation of expectations and results to those responsible, and to the fact that the Business Intelligence system is actually focussed on providing care, as the most important success factors.”

The main reasons for this were increasing competition and ever evolving technological developments. The new system continuously scans the internet for news that is of relevance for the company, such as items about a vendor acquiring another vendor, or items about steel from China that is being introduced to the European market at favourable prices.

The reporting system has over a hundred active users who, through self-service (publish and subscribe) can indicate which topics are of interest to them. The reporting software sends email alerts with interesting information to the decision makers within the company. Managers regularly receive an aggregation of news at a strategic level: news that may lead to opportunities or threats to the organisation’s business or marketing plan.

As an illustration: news about a merger between two companies may be part of a general consolidation in the supplier market. “This offers opportunities (purchasing convenience) but threats too: suppliers gain more power. Based on these developments, we adjust our policy, for example by looking for new suppliers”, said the marketing analyst.

The Wholesaler that initially used Business Intelligence for optimising the internal organisation becomes immediately aware of relevant external opportunities and threats and can thus anticipate faster and easier.

As a 100% vendor independent research and consulting company, we have been examining these new product features thoroughly. We have adjusted the scores for Pentaho BI in our BI tools comparison matrix to reflect the new features. Our survey compares 16 Business Intelligence tools on 169 product features across 12 major categories.

This new version of Pentaho BI supports the analysis of Big Data in a user friendly manner: a process consisting of three simple steps:

1. Choose a data source;
2. Auto prepare Data for Analytics (embedded Data Integration);
3. Visualize and explore data.

In previous versions of Pentaho BI this functionality was also available, but it was not an easy tasks to accomplish, involving Pentaho Data Integration jobs to run manually. Now with the latest version of Pentaho BI the data integration part is somehow seamlessly integrated in the front-end tool. The user is probably even not aware that Pentaho Data Integration is involved. This ‘auto prepare’ approach encourages analysts and data engineers to analyse and visualize Big Data sources more often and gives them more time to explore Big Data. This functionality is packaged as ‘Instaview’, some kind of wizard on top of Pentaho BI and Pentaho Data Integration, orchestrating Big Data tasks.

Pentaho’s mobile Business Intelligence solution is now supporting native iPad gestures in HTML5 and ad hoc analysis, something we have not seen before.

If you want to compare the product features of Pentaho BI 4.8, both their strengths and weaknesses, with all the other major Business Intelligence tools in the market, consider buying our Business Intelligence Tools Survey 2013 which is available for download.

The company faces a number of real problems that affect the core of their customer processes. The company lacks insight into the relation between credit checks conducted at customer acceptance and subsequent payment behaviour. Also lacking is insight into the quality of new customers brought in through (retail) distribution channels. Additionally, the information supply on renewal of contracts leaves a lot to be desired.

The company decides to design a Business Intelligence system, which extracts both customer and product data from several sources and then processes the data into relevant information that ends up in reports in the form of indicators. Now that all relevant customer information – aggregated and visualised per customer segment – is available on one single sheet op ‘paper’, employees have a solid tool for improving both customer communication and customer acceptance.

Following the implementation of the Business Intelligence-tools, rejection rates of new contract requests steadily decreased and the number of incorrect rejections reduced by as much as 74%. The number of customer complaints about credit checks also sharply dropped. Within a time span of one year, over one million new contracts were accepted world wide, where as the number of poorly paying customers remained virtually unchanged and the acceptation process costs decreased by 23 million. In short: Business Intelligence very much served to benefit this company.