The World is continuously in motion and freezing an existing situation is therefore not smart as the value of information decreases directly. Above mentioned steps are therefore not suggested as a well managed linearly process. Especially for social media controlling information can only be done up and until the process of interpretation. For classical BI the process might be a bit more linear and controlled but still some phases will melt together just like a cloud. Locate: Where is it? Business Intelligence (BI) is still very traditional in retrieving or finding information. Most information comes from the organizations own systems. In every organization IT systems are being used for capturing data, such as ERP systems, Cash Registers or HR. This data capture is needed to support the operational process. For example, in HR we need to know what the employees name is, how long he has been working for the company and so on. Also we need to know how much we have sold and to who or where. All this data is being stored in the operational systems. But the data can also change in time or even be deleted. Historically this is why we have built datawarehouses. It allows us to capture all the data in time and create a historical view of facts and dimensions. For BI the datawarehouse is often the information or data source of choice. Its limitation is that it often offers only internal data. The type of data is also often static, meaning that is consists of number, tables. Retrieving information from a datawarehouse can be done with BI tools which build reports or list. Often these reports are developed by the IT department based on user requirements. All and all it takes a lot of steps before information can be retrieved. Locating data or information on the internet is not necessary anymore. Any which way you use the net, you are constantly surrounded with information, coming from WebPages or our own social network. The internet is like an array of millions of datawarehouses that all can possibly contribute to your information supply. For example, this is the first year that computer generate more data than people do. Every minute, ten hours of video is added to Youtube. Every week over ten billion pieces of content are added to facebook. Service like lazyfeed and DailyPerfect can, based on some criteria (or topics), retrieve all the information that can be of relevance. They can do this much faster and more elaborate than any human could have done. Data is everywhere when you are on the web. It is on websites, in RSS feeds, in your social network or hidden within a simple Google query. Data is more than available, rich in content, from many sources and better still, easy to find. Where BI is focused on retrieving structured data from corporate systems or datawarehouses, social media do not need to focus on data retrieval. The information is just there. This makes BI very internally focused and Social Media externally focused. The internet is just an array of datawarehouses filled with an inexhaustible amount of information. But where to find the relevant information? Search engines can help here, just as web services or having a network of trusted people and websites. Both worlds (BI & Social Media) are complementary. By combining BI and Social Media both structured as well as unstructured data is captured. But it is also a combination of internal and external data. The real value is in taking either an inside out approach of better still an outside in approach to enrich already existing information. Finding the right combinations is the final challenge. Control: What is it? Controlling the information from datawarehouses is done with a BI tool in the form or reports, list. Sometimes even OLAP cubes are introduced. These are larger datasets where the facts or measures can be analyzed from different dimensions like date, customer or product. It looks a bit like a pivot table in Excel. Modeling information in a datawarehouse is difficult and often a challenge. Reproducing this data in reports or cubes is even more difficult. The biggest challenge here is getting the definitions right and the same across the whole organization. If this is not done everybody can interpret the data the way they want it. That way there will always be multiple versions of the truth. Too many meeting have been spent on discussing the validity of the figures instead of using them. Controlling internal data might remain difficult, but when done correctly offers a multi dimensional view across the entire organization. With this one version of the truth comes a great return on intelligence. Controlling data is also a big issue for Social Media. There is so much data, that if you want to read it all, this is impossible. So you need to filter and make choices in what you need. This is often done by working with trusted feeds, people and topics. By selecting a number of websites, data feeds or subscriptions to trusted source you can easily control your dataset. You can also use your social network to get information. Some people are part of your network because you trust them or because they can add value. You can also choose to subscribe to certain topics. Services like Google Alert of Lazyfeed scramble the internet for you. This way you can create a controllable dataset, without drowning in the sea of information that is available online. Also by working with trusted feeds, people and topics you know that the information you receive probably hold value for you. It is not just static or a waste of time. In order to control the information BI uses data models. Data is captured, clarified and distributed using reports or cubes. The information is there, relevant or not. But it does provide one stable version of the truth. BI often models this information in line with the organization operational processes (finance, sales, and logistics). This makes these processes explicit and the supporting data known. The added value of this that you can create insight into your own performance: it is looking inside. Controlling information in Social Media is impossible. This means that you have to filter. By using trusted feeds, people, sources or topics. It is about limiting the dataset. If it is not relevant it does not exist. Therefore a dynamic version of the truth exists. The social media often model the information based on trust. This is done based on your gut feeling, so often implicit. The added value of this is that you can create insight into the performance of others: it is looking outside. BI and Social Media are complementary as they allow for looking inside and outside. BI on its own is not enough. The same applies for Social Media. But together they offer a 360 view. Just think about the sales director that explained a decline in sales for Region X based on a newspaper clipping he found on the internet that a megastore was opened b y the competition. Value: Can I use it? The gap between business and IT seems to grow every day. This makes sense as each party has its own tasks, responsibilities and interests. But at the same time this causes problems, because as long as business and IT do not work together, the BI competence will face many challenges. A BI Competence Center where business and IT work together and align their activities is still considered to be the best practice. So why does this gap still exist? IT is focusing on operational excellence. Their aim is to get a minimum of changes, defects or incidents. In their struggle with a declining budget they are constantly striving to reduce the total cost of ownership. But how can we reduce the costs of BI? The simplest solution is reduce the amount of changes. That means less resources and releases. The result of this is a decline in the information supply. On the other hand business is focusing on a concept we call business excellence. They are confronted on a daily basis with many questions and they need answers fast. They need to reduce the amount of uncertainty by increasing the amount of information. If IT cannot supply this to them they will take control themselves. The rise of all kind of (managed) self service reporting is exemplary. Information does not only reduce uncertainty it can also create competitive advantage. By knowing things first the competition is put at a disadvantage. This means that the demand for information will increase. In conclusion, data supply by IT is down and data demand by business is up. This will lead to higher value of the information. The problem here is how to value this information? Because it is not only the information but also the experiences of people using this information, their skills and attitude. BI can help structure data which leads to explicit information. However its real value is made possible through implicit interactions. Humans add value to the information, for example by making decisions or taking actions. But why limit something a powerful as that to only one person? And what is the value of information that you have retrieved from trusted feeds, people and topics. How do you determine which information is important to you? To determine the value is something very personal. What some people consider valuable others might throw away. All information you received is by definition subjective. The information differs in value based on the subject or source you retrieved your data from. Some sources are more valuable than others. This is based on past experiences, known expert knowledge of the sources or because the source was recommended by a trusted person. But there are also some semi-objective measures to rate the value of information. Semi-objective because every opinion is a group result and groups needs some conditions to come to a sound conclusion (diversity, independency, specialization and the ability to aggregate various opinions according to James Sorowiecki in his wonderful book Wisdom of the Crowds). Possible way to quantify the value of information is to look how many social bookmarking sites have acknowledged a certain website, how some article are rated on social news sites (like DIGG) or what the Google Pagerank is, or how many people subscribe to a certain RSS feed. Netflix Netflix is a company that rents out movies on DVD, Blueray as well as online streaming. Its customers can use a recommendation engine (relevant suggestions based on content) which was improved by using social media. Netflix published a set of anonymous data and ask ‘strangers’ if they could improve their recommendation engine by 1%. The person with the best improvement could earn one million dollar. The final result was an improvement of their engine of 10%. This leads to much higher revenue and the costs of the competition were easily compensated. Also these kinds of improvement if done by their own IT could not have been done or would have cost them more than the 1 million dollar. It was much cheaper to just give the data to the social network. In conclusion, it can be said that the value of information is increasing and it is the human being that decides the real value. Classical BI has a somewhat carefully, safe way of using data. It source is often trusted (own corporate system or datawarehouse). Social media are completely different. They use a multitude of sources. Also the safety or reliability cannot always be guaranteed. But in order to come to an optimal performance it is not always black or white. Business Intelligence can create a foundation for decision making, it can formulate a thesis, and social media can serve as some kind of standard deviation. They can make or break the thesis, confirm or reject it, but always enrich it. Interpretation: What do I use it for? The last part of the information cloud is interpretation. The IT role of BI is finished. The information is structured and distributed. BI can be of some assistance by presenting the data differently, by using smart or even advanced visualizations. Also mathematical models can help in creating what-if analyses. But in the end it is the end-user that decides what to do with the information. Some of his decisions can be automated. For example decisions that relates to ‘managed processes’. Those are simple, controllable processes where the cause effect relationship (if a than b) is simple to automate. An intelligent agent can support in this using business rules as a source for its actions. There have been many experiments to create more advanced expert systems where human thinking or experience was being used. But the map is not the territory. In other words, when it comes to implicit decisions based on experience, skills or attitude, the human being is still way ahead of the computer. Interpretation of data within social media is not very different than normal life. The only advantage that social media have over any conventional interpretation method is that you will use much more people in interpreting the data. Especially people that do not know you or your organization can still play an important role because they are in you network through other connections (see also Mark Granovetter, the Strength of weak ties) contributing with their own specific expertise. BI does not interpret. Its technology can support you by scoring the outcome in a model or visualizing the amount of data in an easy to understand graph. But in the end it is always the human being that formulates a thesis, an intellectual proposition. This applies even stronger to the social media. It not one people, it is the people (plural). On the internet everybody is an expert, with or without a certificate. That means that there is not only one interpretation but many truth and possibilities. An antithesis is being formulated. A reaction to the thesis from the BI process, leading towards a synthesis. The opposite opinions are being resolved resulting in a new thesis. A solution is being found. A decision is being made. An action is taken. BI is much more about analysis, but BI and Social Media combined work toward synthesis. For now social media are only supplementary to BI. But in the long term we expect that this will the opposite. It is not beyond our imagination that classical BI as we know it today will be replaced by a process where (anonymous) corporate data will be published on the internet for the crowd to interpret against lower costs. Goldcorp Goldcorp, a Canadian company, has published over 400 megabyte of geological data on the internet about a piece of land they owned in Red Lake, Ontario. They offered a reward of 575K for anyone who could analyze and interpret this data and come up with a suggestion where gold could be found. According to Goldcorp they received 110 locations and 80% Of these locations contained gold. They digged up more that 2 million kilos of gold with a value of over 3 billion dollar. The reward was won by a small consultancy form in Perth, called Fractal Graphics. Example An analysis of the corporate data showed that Sales has increased 10% for all baby clothes in their Eastern region. The sales manager has developed 3 scenarios: (1) push sales of baby clothes to 20% in east, (2) develop a toddler clothing line, (3) start selling baby clothes in region west. This sales manager shared his data with his network. His preference was scenario 2 but the ‘wisdom of crowds’ voted for scenario 3. Off course, he can still choose 2 but regional differentiation seems to be a smarter approach than product differentiation. Food for thought for our sales manager. Conclusion Information is becoming more important and is even an economic factor. But there is much more information available than needed. The challenge is in finding the relevant information. BI can do this by opening up the corporate data. Social Media do this by accessing external online information platforms. Central questions arise like: where is the information, what is it, can I use and what do I use it for? BI and Social media take a different approach but are also very complementary. BI can create a thesis based on internal trusted data and Social media can make or break this (anti thesis) but always enrich its value (synthesis).