Enterprise Data World is the business world’s most comprehensive vendor-neutral educational event about data and information management.I am honored to be invited to speak on Trends in Business Intelligence. Please join me wednesday, March 17th at 11:00 am in San Francisco, USA. Information is crucial to fight challenges but also in trying to identify chances and possibilities. What are the major trends in Business Intelligence and how is it impacting your organization? Capgemini explains how you can make use of data in order to make the necessary decisions under these fast changing circumstances.

A new book on BI will be published on January 26th during the Heliview Business Intelligence conference in FIGI ZEIST for which I wrote one chapter (On BI in Retail).

See also  http://bi.heliview.nl/

The title of the book is: Over business intelligence. Data is zilver, informatie is goud (About Business Intelligence. Data is silver, information is gold). 

The book can also be ordered for € 26,50 (excl. € 2,60 postage and packing) on www.uitgeverijtiem.nl.

You can also view the index and some summaries on this website.

Do you remember the 1995 movie Seven where Detectives Mills and Somerset jointly investigate a series of ritualistic murders inspired by the seven deadly sins? I vividly remember a library scene where Morgan Freeman goes through a set of books related to the seven deadly sins, like Dante’s Inferno (or hell). The seven deadly sins were: lust, gluttony, greed, sloth, wrath, envy and pride. Today I suddenly wondered, are there seven deadly sins for Business Intelligence? And if so, what are they? Inertia:The potential of BI is unbelievable. It allows companies to make smarter and faster decisions and simply outperform the competition. Lack of relevant information may even lead to a loss of market share, drop in profit or even bankruptcy.  There are numerous examples to support this claim. This is why BI is always in the top 5 of any CIO or CFO. However there are still companies that do not have an (official) BI initiative in their organization or lack focus on the information function. In today’s economy something that one simply cannot afford. So the first and most deadly sin must be something which has to do with the lack of relevant information or slow time to information. The use of BI must be stimulated at all times and no barriers should prevent the adaption of BI within any company. Costly:BI is often considered to be expensive. We all heard people say things like: “Why does it take 3 months to build a few simple reports”. In some cases these people are right. If BI is not organized in an efficient way it will lead to higher costs. For example if there are many local initiatives or an IT organization that does not understand business needs. For me, the second deadly sin has to do with the fixation on costs instead of thinking about return on intelligence. BI can have a hard dollar (or euro) return but the business case can also be qualitative or based on vision or innovation. Off course, we must always look for smart and cost effective solution. Lowering the TCO can be done, for example by standardization of tools and processes. Another possibility is outsourcing. However that can lead to new challenges. This brings us to deadly sin number three.  Complexity:BI is no rocket science but it is also not a trifle undertaking. BI has both a technological as well as a business component. This makes it neither business nor IT. This creates a possibility of increased complexity in the development of BI solutions but also in the final product itself. The result may be a BI environment that is not used. It is important to keep the BI solutions simple. By taking small and simple steps and making sure that business and IT keep aligned. We must also be aware that there are different types of users and that they use BI differently. Manager need dashboards and aggregated numbers while financial experts need detailed number in spreadsheet like form.  Technology:The fourth deadly sin is that BI is often also the number one deadly sin. In my experience it is one of the main reasons why so many BI projects fail. It has to do with the tendency to focus on tools and techniques. BI delivery is often within IT where the understanding of the business can be absent. Realization of the technical solution, like a data warehouse, is the objective instead of fixing the business need (where the data warehouse is just part of the solution). Let’s remember that IT is just an enabler for doing better business (intelligence). So why are 9 out of 10 BI blogs only about technology? Ignorance:Let’s say that we have found a company that believes in BI, focuses on ROI and with a not all too complex solution in mind. Even better they also focus on business results and not technology. Sounds like all ingredients for a successful BI solution are in place. So they start this great project to improve their call center effectiveness or increased sales force performance. And in the back of the room there is this little geek from IT that always talks about the importance of data quality and Master Data Management. Don’t you wish they would have listened to that guy then in stead off afterwards when their reports have the wrong numbers? Or when they spend days or even weeks discussing about a difference in definitions? The fifth deadly sin is that the most important fundaments of BI are often ignored as they are not sexy enough. MDM and DQ are essential for acceptance of BI.  Deviation:Sometimes a BI initiative just starts. Not because there is a business need. Not because somebody has a vision. Only because the company needs to have a BI system. There is no time spend on thinking which business problem is helped or solved with this solution. All other people have BI so we want it too. The sixth deadly sin is to build something without knowing where to use if for or having no sense of direction. Organizations should never develop a BI environment before they have a clear BI strategy. Halting:The seventh and final sin is that after a BI project is finished or a 1^st increment is delivered no follow up is given and BI is not integrated in daily business. The real business value in BI will only emerge if you keep on investing in your BI environment and adapt for changing circumstances. Something like a BICC should solve this. I am not sure if these above mentioned seven deadly sins are in fact the only ones or in the right order. But I do think they contain elements that hinder the proper use of the BI function within many companies today. I would really appreciate your feedback on this. Perhaps you have some deadly sins to add to this list. Please do not hesitate to react.

One definition of Business Intelligence is the collection and structuring of corporate data in order to gain information for further control and management of a process, target or strategy. The return on intelligence (ROI) is achieved by doing better business. BI is therefore often part of a project or sometimes even a project in its own right.  Many corporation start a project by putting together a business case. All possible costs and benefits are taken into calculation. Only the projects with a sound or positive business case get the green light. But the economic downfall has changed all this. Not only are we starting with less projects, even those that have a positive business case to begin with, many project have been cancelled, delayed or re-scoped. In order to make reasoned decisions an answer must be given to questions such as: How will this project contribute to our business objectives, are we doing the right projects, are there better ways of using our resources, is the business case still valid? Portfolio management gives corporations the change to have a clear understanding of the contribution of an existing or potential initiative. This way a corporation can make sure that it only invests in projects that add value. The corporation is doing the right things.  But just as important is Portfolio management information. Monitoring the current portfolio enables corporations to get an early warning on possible risks but also the possibility for action taking if the value of certain projects decrease or even get negative. The corporation is doing things right. 

I see to many companies limiting their selves by building one single business case only at the start of the project. This way they will not get the maximal return on their investments.

These corporations might be doing the right things, but they are not doing things right.

“But it wasn’t because I didn’t know enough. I just knew too much”. Gnarls Barkley – Crazy

The market is volatile. Your customers are volatile. Maybe if you look in the mirror you will see a volatile person. But volatility is something we – in general - tend to dislike. Therefore we strive to regain control. Control of our finances, of our customer even of our future. Management Information seems to help us with this. But the way we use management information or business intelligence is not always up to par. Most of the time we use historical data or performance to make decisions. But many answers, smart moves, right decisions are hidden in the near future. That’s why we want to be proactive. Beat the other guys. Advanced Analytics seems to work. It combines techniques like datamining and statistics with business knowledge to create predictive models. But even in advanced analytics we seems to focus too much on using our own data. Some argue that the most valuable information is not found inside your company but outside. If this is true I don’t know. What I do know is that external data can help you improve your performance. But how do you regain control of external – often unstructured – data. And even better. How can you make this process repeatable? The most obvious three problems that arise are: [1] too much data, [2] data too late and [3] poor data quality.

The problem with having too much data is that you need to come to a selection. The data in the world keeps growing and growing in mind boggling amounts. But the majority of this increase is not relevant. Pictures on flickr are great but aren’t much help when figuring out your supply chain strategy for 2010. But it is not so much the amount of data that is the problem. It is the structure. If you find a way to effectively structure any increase can be handled without too much effort. Therefore I would suggest to start structuring your data for relevance.

Another problem is that the relevant structured data is often received too late. After the fact has already happened. This means that no proactive behavior but reactive behavior. So how can we improve on that? One solution could be to set up early warning signs. Maybe there are some early indicators that can warn us about things to come. For more information on this I would like to suggest the work of Ben Gilad (http://knol.google.com/k/ben-gilad/competitive-intelligence/1o41pnd9hgmyg/2#). Please make sure you know what early warning systems are crucial for your organization.

Finally, good old data quality. In our pursuit for perfect data we tend to forget the reason why? Do we really need perfect flawless data ? If we have one piece of the puzzle that is wrong it might causes a problem. But if we have 1000 pieces of the puzzle – some right some wrong – we have enough information to make our decisions. So forget about data quality and start focusing on relationships between the data elements that make for the big picture.

If business intelligence can improve by adding external data, why is it that a lot of companies keep looking inward for their management information? One explanation could be that compliance is often the reason why they have a BI environment anyway. For some reason they have to report their performance to stakeholders. This mandatory reporting is often focus on (financial) internal data. Or  somebody started with improving a process by making it measurable with the use of BI. Or even more simplw. It is easier to start with your own system, company or IT department.

In conclusion I would like to argue that we need to structure and combine internal and external data in order to really gain any competitive value.

On a Dutch website

( http://www.computable.nl/artikel/ict_topics/business_intelligence/2844877/1277145/bi-betaalt-zich-bijna-nooit-terug.html#2853949)

there has been some discussion about the return on investement for BI. I reacted (in Dutch). Follow the link for the reaction from myself and others.

 Two important announcements came from Microsoft recently. One was that Microsoft is firing people. A move that was inevitable after analysts said that Microsoft had to lay off at least 10% op their workforce to remain healthy. Another one was an update of their BI product roadmap. Performance Point Server scorecard, dashboard, and analytical capabilities will be consolidated into Sharepoint Server Enterprise. This means that they will not continue with their Performance Point Planning solution. In their words: after PPS Service Pack 3 (expected mid calendar year 2009) no further investments will be made in planning and stand alone versions of PPS.  Are these two facts related? Maybe not but it helps them on their way to this tough 10% target. Is this update of their BI products roadmap unexpected? In my opinion it is not. There are several reasons for this. PPS Planning has never been very successful and I have seen a limited number of implementations. When competing with other planning products (Hyperion(Oracle), Outlooksoft(SAP) or Cognos Plannings(IBM)) they often lost the battle. One could also argue that they are their own biggest competitor with MS Excel as the number 1 planning tool in the world or BI tool for that matter. Also this product does not fit their BI for the masses strategy. Planning has always been the domain of a limited number of (financial) people. But this is not only a defensive move. Integrating PPS with Sharepoint also allows for a ‘marriage’ between structured and unstructured data which is promoted by many BI experts of late.  It will be interesting to see if other BI vendors are going to reposition their planning capabilities.

Earlier this week I was driving home from work listening to the radio. It was around 6 P.M. so I was waiting for the six o’clock news while absently listening to the commercials in the background. One of the commercials caught my ear. The narrator asked us the listeners the following question: How is the performance of your network?  What would your first reaction be to such a question? I bet you were thinking about some kind of telecommunications service product with circuits and packets. Is this where we separate the geeks from the rest? The first thing I think about when I hear network is People. Or better even stakeholders (mind you that is much broader term than shareholders).  So this question about network performance made me wonder.  How can my stakeholders help me improve my performance?  The answer of course would be by sharing relevant information. This raises a bunch of other questions, such as:How would they know what is relevant to me?How can I even know what is relevant to me?Why would they share information in the first place (what’s in it for them)? If you look at the traditional knowledge pyramid – data, information, knowledge, action – one of the answers could be just to share data and let the recipient transform this further. Let them filter for relevance. This would allow for a SOA like architecture where data is provided in the form of messages and the BI solution just ‘mashes this up’. The benefit would be that the senders would expect the same in return. This is a relatively straightforward business model that has been around since EDI. At the same time we see a major trend which I labeled “increase”. We see an increase in (volume of) data, an increase in the speed we want to consume this data (even real time) and an increase in the impact of business decisions. We want smart and relevant decisions now! Not after we have loaded the data in our datawarehouses or datamarts. Not after we viewed it using reports or cubes. Not after we have come to some decision based on our implicit knowledge. This would allow for a architecture where no longer the data is provided but where decision is provided. The relevancy is determined by smart algorithms,  business rules or some other smart solution. Obviously this is more difficult but it would help me improve my performance. But what would be the benefit for the sender? Probably they will charge me money for adding analysis and actions on top of this data. So what do you think? Are we going towards a business model where information brokers are collecting data, making analyses and supplying decisions and actions to their clients (in fact take BI outside your company) or do we stick to the traditional model (where BI resides inside your company)?

Today we started with the keynote from Ben Klein. Some people might remember him as the teacher from Ferris Buelers Day off (Great movie btw). His speech was funny but very American. His basic theme was that the American Youth is getting more stupid by the hour. The focus is on material things, money i.s.o. taking care of eachother. This was folowed by a plantinum sponsor panel discussion with guys from accenture, Dell, HP, Hitachi and profit base. First take aways are. BI in the next 10 years is going to be more about social networking, instant information, even more data, integration, visibility of data, 90% on 3 or 4 platforms, role driven and less adhoc. There will be a gap between BI solutions and its users due to cultural differences, skills and so on. Perhaps this will create a new role of the information architect (iso the data architect) with more focus on business than on SQL. Understanding then underlying model is key for enduser buy in. There will be an ERP world (with focus on capturing the information) and an IRP world (with focus on delivering the information). Right now they are going into commercials so it is time for a cup of coffee.

Everybody deals with data all day long, from the board room down to the order entry department. Most of the time we do this without even thinking about the quality of the data. But when we do think about Data Quality (DQ) it often already has become an issue. Therefore our approach towards DQ is often negative (Garbage In, Garbage out). And also our approach is often technical (Field X in Interface Y is alphanumeric with 9 positions instead of numeric 8). So what happens? The IT department hurries towards the business owner with their negative technical problem often followed with an even more technical solution. Nine out of ten times this involves a tool from some vendor that promises a magic data laundry machine that cleans your dirty data. Let me tell you, there are not many business users that become enthusiastic after a negative technical speech. A more smart approach would be to make a simple business case. Bad DQ costs money, therefore good DQ makes money (or at least saves you some). That should be simple enough for any business user to understand.  As BI becomes more operational (do I dare to say real time) the chance that the data is polluted (or not yet cleaned in the ETL process) increases. Another trend is the combination of structured and unstructured data. Combination means coupling of two or more entities, also know as data integration. This is again an area where the DQ is crucial. In order to deal with DQ under these circumstances there are two options. Option 1: increase the performance by adding more of everything (CPU, memory, tuning IO and so on). Option 2: increase the performance by doing things smarter. This means creating some kind of solution that involves metadata or business rules. Also using a profiler tool to filter out the usual suspects is a smart way to go. Whatever you do, try to take a proactive approach instead of solving it after the ‘laundry is already dirty’. What can be the result of bad DQ? It can lead toward making the wrong decision (when based on incorrect data), it can cost money from an operational point of view (double mailings) or even lead to damage to the corporate image. It is safe to conclude that DQ is important for everyone. But by making it every ones responsibility it at the same time becomes no ones responsibility. There is always someone else that owns the problem, needs to fund the solution and so on. An at the end of the day still nothing happens to solve the DQ issues, leading to wrong decisions and more waste of money.  Let me explain what I mean using a real example. Department A has a customer database where customer A is known as Mr. A. Department B also has a customer database where customer A is know as Mr. B. During the data integration process Mr.A. and Mr.B. are seen as two different persons while in fact they are not. Should department A fix this? Why should they as this registration in their database of Mr.A. suits the purpose. The same applies for department B. Should the IT department fix it during data integration? If so, do they choose Mr.A. or Mr.B. in their Master Data approach? And by the way, who is going to fund this? It is not a problem for IT so they are not going to open their wallet. It is not a problem for department A or department B so they are not going to fund it. We have talked about the data delivery and the data integration, now enter the data subscriber. Department C uses the central data warehouse for their management decisions, corporate mailings and so on. They have problem with this whole Mr.A. and Mr.B. stuff but do not consider it their fault. So why should they pay for fixing this? This is what I mean. The whole DQ (and metadata issue for that matter) problem keeps being pushed from one desk to another and no one is going to solve it.  The central questions are: 1. Who owns the problem? 2. Who is going to solve it? 3. Who is going to pay for it? All the IT department can do is to identify the problem and facilitate the solution.  I would love to hear what you think about this. Please let me know and write your comments. Perhaps together we can find a suitable solution. In the meantime we keep our fingers crossed and hope for the magic laundry machine.

RT: There is a slowdown in the BI market (I think). The reason for this is that most organizations have some kind of BI solution in place. The next challenge will be information management. The problem is that we need a business case for this. IT is at a deadend if they cannot translate their house keeping in some kind of revenue versus costs calculation.  JH: I don’t know if there will be a slow down. BI is a slowly evolving system that needs constant attention and a incremental updates. RT: Organization need a BI house keeper. JH: New BI initiatives will probably slow down in the medium & large segment. Mainstream IT is on its way to be a commodity (like furniture). But BI is still such a specific type of IT with a lot of business involvement that it will remain a hot topic. Perhaps in a different shape than cubes and reports.  RT: Best in class companies can focus on tooling and information but all others have a data problem. JH: competing on data is tge nr1 challenge.  RT: We need a new subject at school! JH: Out with the CIO – long live the Chief Data Officer RT: Information Logistics RT: (CDO, see Yahoo)  JH: Are they doing this?  Smart of them to listen to the guru  JH: However if they are taken over by MS they are not as smart as I expected.  RT: lol, nice fight with NewsCorp, AOL, Yahoo, MS, Google … JH: Have to go – talk to you later RT: CU.

There is much talk about the impact of the (feared) recession on Business Intelligence. Most analysts are expecting a slowdown in customer spending and vendor revenues. I see their point and I am somewhat inclined to agree but there is another side to this. There is an expression that goes something like: you have to repair the roof when it’s not raining. In other words IT spending is obviously up during financial upturns. BI tends to benefit from this as well. But as the economic weather gets rough there is even more need for information. As the budget is cut back people are looking at smart things to save costs, recognize trends early, and identify the most valuable customers and so on. This is exactly what BI enables you to do. So my expectations are that an economic downturn will hit the general IT market much harder than it will impact BI.

In a move that turns the heat up on Microsoft Excel, Google is partnering with business intelligence firm Panorama Software to develop a software-as-a-service (SaaS) analytics, reporting and data visualization tool for its free online Google Docs applications suite. The BI firm that handed Microsoft the original OLAP technology that’s now included in SQL Server database management system, is working with Google to push BI and data visualisation capabilities into Google’s Docs applications suite which mimics Microsoft Office with free online word processing, spreadsheet and presentation applications. At the same time rumors are surfacing that Microsoft in experimenting with an online office suite with codename Albany. This in an attempt to fend off competition like Google docs. The Panorama software, which has been released as a beta version this week, is offered as a free desktop gadget that works with Google Spreadsheets. It draws on analysis, reporting, dashboard, visualisation (charting) and data modelling tools that are part of Panorama’s NovaView BI suite. These elements combine to create Panorama Pivot Tables that can be embedded and manipulated in applications like Google Spreadsheets. This Google initiative perfectly fits into one of the BI megatrends for 2008: Integration. We have seen that Business Intelligence continues to integrate with operational processes. The preferred tool of choice in operations is still the spreadsheet (Excel). Microsofts ‘BI for the masses approach’ also boosts excel as their BI frontend. If Google wants to compete with Microsoft (in the BI area) then targeting the spreadsheet sounds like a well thought strategy. But if you compare the installed base of MS Office and Google Docs there is still a long way to go before somebody in Redmond looses sleep over this. Also we have seen a consolidation of BI vendors in 2007. This means that small(er) BI vendors will be looking for partners to survive (or create niche solutions). Again also sound strategy thinking by the guys and girls at Panorama. That they have been in bed with Microsoft before makes it even more exciting.  Finally the Vendor consolidation has created an renewed interest in open source software. Clients are afraid to be ‘owned’ by one mega vendor. Google may be perceived as a alternative. In conclusion, we could argue that the BI vendor consolidation has made the BI market more volatile by creating new chances for innovative parties even from a non traditional BI background.

I was asked by an IT magazine in the Netherlands to come up with a couple of practical tips on BI service delivery. In my opinion the most important element in service delivery is creating a optimal mix of all crucial elements. My submitted three practical tips cover design, build and implementation. However it is just a start. Please join me to create a top 10 in BI service delivery.  [1] When designing a Business Intelligence environment always consider target groups and type of usage.Target groups: Some users such as managers often have the need for a high level dashboards with little detail. However other users like analysts need lot of detail and powerful analysis tools. Every target group needs their own environment in form, function and frequency (of data refresh). Usage: There should be a mix of fast (ad hoc) and structural (more long term) BI solutions and products for the end user of a BI environment. [2] Excellent BI specialists are a scarce resource but are crucial for the success of the BI environment. Do not cut back on quality. Make sure you have a proper mix of ‘hardcore’ geeks as well as business architects or BI visionaries. In order to make the costs controllable consider outsourcing parts of your BI environment. A good starting point would be technical realization (build) and application maintenance.  [3] Don’t stop when it’s finished. After the technical realization of the BI environment the real work just starts. A critical success factor for this is the BI Competence Center. This center should mix IT and business components to ensure the optimal use of BI within the organization. It should be the BICC that pro actively supports the users in their daily work. In this phase it is no longer about high level sponsorship but more about working floor thought leadership.

The beginning of the year is always a period to look back but even more important to look forward. On the radio I hear a lot of commercials from different training institutes urging people to add their specific course, study or lecture to their 2008 curriculum. I expect that employees are now running towards their management requesting training in new features of tool XYZ and so on. Business Intelligence (BI) is a field of study that has been dominated by a strong technical driven focus. Business Intelligence supports better decisions, by making a strategy, objective or process – accountable, adjustable or adaptive. Shapiro has developed a knowledge management pyramid with three layers: data, information and knowledge. Unlocking data and transforming this into information will lead to more knowledge and insight. Professor Weggeman defines knowledge as: Information * Experience and Attitude (K=I * EVA). He states that hard facts, information or explicit knowledge can only lead to benefits when combined with implicit or tacit knowledge. Only when something is done with the information, such as sharing, comparing or merging with something else will lead to performance improvement. Choo adds another element to the mix. On top of explicit and tacit knowledge he adds cultural knowledge. Those are the beliefs and values that exist within an organization. Therefore it is safe to conclude that when it concerns performance improvement or strategy alignment the real barriers are: communication, culture and change management. BI from a technical point of view is just an enabler. So why is our community still so much focused on technology. Why is it that instead of subscribing to for example a course in business spirituality we choose the “database administration 2.1” or “Advanced SQL 3.2”?

Perhaps you can find some inspiration in these lyrics: http://www.oldielyrics.com/lyrics/supertramp/school.html

Times they are changing. Last year has been tumultuous for BI at best. We have seen the BI market consolidate into a few remaining mega vendors. But there was also room for niche players especially the ones focusing on speed, visualization or collaboration. So what will 2008 bring? To quote from Star Wars: “Impossible to see the future is”. But let’s give a try anyway. There are five mega trends that I foresee. Some have been around for quite some time and some are new. The first one is called: (1) Increase: Business Intelligence must be able to cope with considerable increase in both data (size) and speed (real time). The second one is (2) Integration: Business Intelligence will continue to integrate with operational processes but will also be more aligned with strategy. The integration of (un)structured data will increase. Finally, Business Intelligence will integrate with other business applications or ERP systems. Third, and my personal favorite, is (3) Insight: Business Intelligence will continue to become more intuitive (less end user involvement) showing an increase in advanced visualizations but also more analytic (more end user involvement).The fourth is (4) Interactive: Business Intelligence will be more reciprocal by nature; creating a dialogue between system and end users as well as sharing information and collaborating within performance networks. Finally, number five will be (5) Industrialization: Business Intelligence development will be characterized by a more industrialized approach using standard development frameworks opening up the possibility to outsource.  Increase will be mostly characterized by the need for real time information (partly due to the fact that BI becomes more operational). This will be supported by tools like Netezza and Teradata. They can also support the growing process of data retrieval from vast amounts of data. Integration of unstructured data (text, search, documents, agents) for example in a document warehouse (using tags) sitting next to the data warehouse will be the wave of the future. I expect Google or Attunity to take the lead here but the original BI vendors (Cognos, BusinessObjects) have also been investing in this. Although the market is more or less divided among a few remaining vendors it is still possible that we will see some more integration. This will be partly triggered by the fact that BI will be used on all levels: strategic, tactical and operational. This means BI tooling must support strategy development as well as pervasive BI (it’s everywhere). The renewed interest in open source Business Intelligence (Pentaho, Jaspersoft) is a clear counter reaction against the market domination due to vendor consolidation. Creating Insight today will be the one mega trend where I expect the most innovation to come from. It is a hot topic and fun to watch evolve. Here you will find things like intuitive intelligence (Strategy companion) or decision engines supporting your daily work (Fair Isaac). Also advanced visualization will help the end user get more grip (fractal edge) on things. Triggered by the success of “competing on analytics” or “super crunchers” we will see an rise in the use of analytics, strongly combining informatics, statistics and business knowledge. Perhaps here lies the opportunity for the long awaited promise of data mining? A clear and much appraised trend is the sharing of information with other people either inside or outside your own company to create mutual benefit. But it is more than just sharing the information it is also about sharing the reasoning behind it. How have we come to this conclusion and do you agree? It is asking feedback or contributions to your problem solving by your stake holders. All the characteristics of the web 2.0 can also apply here. This can also be done by using a trusted third party to solve your BI wishes by providing BI as a service. As BI is getting more mature by the minute I expect that we will see a standardization of best practices resulting in an industrialized approach in (standard) BI development. BI factories, often based in typical outsourcing countries, can provide high quality, low cost ready-to-use BI solutions. Some people say that after all the consolidating this will be a boring year for Business Intelligence. But if I look at these five mega trends I can’t wait. Happy new Year.   

Detailed insight into crucial data and events is a necessity for organizations that want to navigate a constantly changing, information-rich environment. Intelligent organizations are constantly reading, analyzing and reacting to information inside and far outside the companies’ boundaries. Information thus becomes a corporate asset, which infuses itself into all strategic and operational parts of the business. Traditionally BI enables business decisions through information access, by delivering the right information, at the right time, in the right way. However nowadays BI does much more than then decision making. It also monitors and supports, among other things, crucial business processes and is much more then ever embedded into daily business. Therefore it can be said that BI is crucial for the strategic, tactical but also the operational needs of an organization. Many companies have service level agreements (SLA) between (mostly internal) parties to formalize the process of data delivery or extraction from data sources and/or the publication of information to business stakeholders. With a traditional focus on decision making or decision support only those SLA have been created with just that scope in mind. This has resulted into a situation where a problem with data delivery or information publication had to be resolved within for example a timeframe of 24 hours or even more. In other words, due to it’s reactive or even reflective nature, the repair of the BI problems have not been the highest priority for many organizations. This makes sense if you compare this to critical business applications such as cash registers or ATM for banking. They support the crucial daily operation and should get top priority. But with the changing nature of BI, becoming more operational and supporting real time business processes, it is time to redraw the SLA and giving (almost) top priority to BI systems as well.

Almost all human beings, except for the blind or visually challenged, are by nature visually orientated. Our eyes constantly monitor our surroundings searching for things that are out of the ordinary. This real time interface between eyes and the visual cortex of the brain has helped the human race survive by quickly recognizing danger. The great thing about this is that we are also able to filter out all the noise. For example, if you want to mail a letter and during the trip from your home to the mailbox you see every little detail, you probably never get there. So we ignore the stuff that we already know or looks the same all of the time. Only the things that look different get our attention. At the present time this ability to quickly spot dangerous animals or other threats is most often used for other purposes: shopping! Store owners, website builders, they all try to grab our attention using visual stimuli. Recently I was at the new Starbucks coffee shop at Schiphol airport in the Netherlands. My eyes quickly spotted a new Ready To-Go coffee tumbler. It was different from the normal ones because it had some kind of holiday season appearance. Being a collector of Starbuck Coffee Tumbler (I know this is a bit geeky…) I bought it on the spot. For Business Intelligence it is not so much different. As we are confronted with an enormity of data we try to find ways to interpret it. We try to find the information or even knowledge in this overload of data. Therefore we use Business Intelligence. But this information is presented to us in more or less the same manner, shape or form. Therefore we are quickly bored with it. Knowing this and the fact that our eyes and brains have this great ability to recognize patterns and trends we need effective visual communication of data that changes its shape or form to grab our attention when needed and allows us to quickly asses if the information presented holds some kind of pattern of interest. We need visual business intelligence that makes use of our intuitive skills. Just take a look at the work of Stephen Few (http://www.perceptualedge.com/) one of the evangelists of visual Business Intelligence or tools like Gapminder (http://www.gapminder.org/) to see what I mean.

Detailed insight into crucial data and events is a necessity for organizations that want to navigate a constantly changing, information-rich environment. Organizations that know how to connect the use of data to their strategic objectives are more intelligent: they become ‘Intelligent enterprises’, constantly reading, analyzing and reacting to information inside and far outside the companies’ boundaries. Information thus becomes a corporate asset, which infuses itself into all strategic and operational parts of the business. As a result it’s only natural that more and more organizations want to start a Business Intelligence initiative.  However BI initiatives cost money. This is often an inhibiting factor for many companies. At the one hand they need BI to face the business challenges of today’s market but at the other hand they need some kind of justification before they can start. This justification can take two shapes or forms.  The first and most well known is the business case. Basically this is a quantitative analysis of all expected costs versus the expected yield or profit resulting into a return-on-investment. The business case involves calculations on lower costs, more effective processes or less manpower. Those are all very tangible and well defined attributes. Business cases are often made by business departments in order to obtain a budget.   The other is less known - probably far more difficult - but with a higher yield. It involves a non quantitative analysis based on vision. Driven by thought leadership an ideal or goal is formed. Unlike the business case there are no tangible attributes. The advantages or benefits can be things like qualitative better decisions or accessing unknown data sources. Often these initiatives are considered to be vague or soft. There is a promise of profit not a proof of profit or like I call it: return-on-intelligence. This vision based justification is often made on an organizational level in stead of departmental. In my opinion, in this day and age a company can not allow it self to remain without business intelligence and survive the increased competition. A BI environment is a necessity just as much as a LAN or transactional business applications. Therefore they need BI initiatives even without a cold business case. I encourage all companies to take this vision based approach. Not only will it lead to more commitment from your employees, it will also support the execution of your strategy. And in the long run – there is proof enough for that – it will also pay back on its investment.

This is the second part of my posts about the ‘universal truths in business intelligence’. Check out what Frank Buytendijk thinks at: http://blogs.oracle.com/frankbuytendijk/2007/12/04#a95 4. BI projects need high level sponsorship. The reason for this is that we want to introduce Business Intelligence in the organization. It is all about creating awareness and enthusiasm. So do we really need a high level sponsor or manager for this? Perhaps in a very rigid hierarchic organization you do. But we Dutch do not deal well with a top down approach. The real innovation comes from the work floor, we think. I think organization can benefit much more from a highly committed thought leader.  3. BI development should be done incrementally. What would be the opposite of that? Probably some kind of big bang approach where all the functionality can be delivered in one single release. That sounds nice but often this is not possible for BI. To start with I find that when users start to interact with the new BI system they come up with new insights followed by change requests. A successful incremental approach focuses on the identification and prioritization of the most beneficial increments or slices. This should be based on the priority of the objective (is this a key process, is it in line with our strategy?). Other qualifying criteria can be availability and quality of the data. Each slice should be a complete solution. BI projects – just as in real life – should have a first things first approach. Delivering incrementally – keeping the long term view in mind – allows for faster speed to value. So I agree with this truth.  2. BI projects require a business driven approach. Any BI project or program should have business value. Creating a business intelligence environment without a goal is a mission impossible. We do not need data warehouse projects. We need project that can create more sales or reduce churn. A data warehouse or business intelligence project can support this goal. However I do not think that it is should necessarily be the business user who initiates such a project. IT can play an important role in taking the lead by showing what is possible. Especially by creating a prototype. See also my other post on IT push or pull (http://www.biguru-online.com/2007/12/04/active-push-or-passive-pull-role-for-it/).   1. BI needs one version of the truth? Has anyone of you ever played bullshit bingo? It was one of the sources of inspiration for this post. You take 10 of the most used words and cross them out during a meeting when used. Single version would be on the top of that list. I hope that from this day forward no one will ever use this expression again. This was born out of fear for multiple version in spreadsheets across organization. And frankly, I cannot stand the expression anymore. Also I totally disagree with it. Understanding is always determined by its context! And all communication should differ for each target group. Creating a single version – let alone the office politics involved in that – is an utopia. Instead let us focus on a single version of the facts (data quality, lineage and so on). To me the focus should be on the definitions or meta data. As long as the definition is clear you can have different version per context. So are there any ‘truths’ that we missed in our top 10? We would appreciate your suggestions. Also if you disagree with what I said (or agree for that matter) please post a comment. Remember this blog is all about the possibility to be an online BI guru yourself. It is a platform for an open discussion about BI – not just a floorshow for my thoughts.