What have happened in the last twenty years in the Business Intelligence area? The term and technique with using fact-based support system was actually started already in the 1960s and developed thought the mid-1980s. The usage wasn’t widespread until late 1990s and organizations started to adopt the definitions and technology. When I comes to data warehouse there has been a lot of innovators during the establishment. The most famous Ralph Kimball and Bill Inmon has put the foundation that many organizations used to build up their data warehouses.
After following this as consultant and leading line roles for two decades I have seen a tremendous change. A change in term of needs, technique and especially how people work and adopt to changes. For these two decades we have focused a lot on building data warehouse and structuring information. Now we will start work on how can we use all that information in a more efficient way and the need for e.g. Data Scientists will be huge. From working with large set of standardized reports many times developed by IT to self-service Analytic tools, Cloud Solutions, Big Data, Machine Learning, Text Analytics, BI Automation, Predictive Analytics and Mobile Solutions. The list can be longer and you might wonder why all this tools and techniques? Can I continue work like I always have done?
Yes, you probably can. I work with a lot of organization that now are in transformation from “report factory” to “self-service” oriented way of working. So where does the business value comes from all these solutions? Are the users having right support for decision making today? Maybe they are waiting weeks or even months for a report. The self-service tools are extremely user-friendly today and they can easily extract the data by them self. Are your IT manager happy with having dedicated people or external consultants creating reports for the organization? Your amount of data might have increased or there is need for loading data from social media which affect your performance. Are you satisfied to see just what happen yesterday and no need for calculating how the future might look due to the history data? Now you thinking there is no tool that can predict the future. Maybe not to 100 percent but if 95-98 percent is enough the technique are here and many industries have been working with predictive solutions like ”R” for many years. What are your competitor or surrounding organizations do? You don’t want to lose business opportunities because lack of information.
So how should I orient myself in this jungle of tools, techniques and possible directions? Many organizations are not mature for loading their data or part of their data into cloud. Questions like is it safe will be discussed, even if the same organization have outsourced their servers. But even if you decide to stay with on premise data for a while there are a lot of solutions to provide a more effective decision making for the users. It’s also important to have in mind that all this new tools doesn’t solve the data access issue. Information Management and data quality are still something that you should spend time on. In many projects, the part which captures information the most time consuming.
So how do I get started? If you already have a common BI environment it’s a good idea is start in a minor scope for e.g. your controllers ask for a tool where they can analyze information by their own. Provide them with a self-service tool like SAP Lumira, MS Power BI etc. This implementation can be done without affecting other areas in BI environment. In general, I always suggest to start in a smaller scale. The same approach can be used if you want to try cloud solutions like SAP BusinessObjects Cloud or Microsoft Azure.
If you building this up from start there are a couple more questions to have in mind. I have seen successful projects delivered business value to the organization on time within budget, yes it’s actually true. But I have also seen less successful projects. So what did the one that succeed do that the other ones missed. There is of course no simple answer but one mistake are that BI project are driven at same manner as traditional IT projects. A very big difference are that BI project involve whole organization and not just a department. Another classical pitfall are the gap between IT, consultants and organizations. IT has to big influence in the project, where IT should support the project and not drive the project. People that drives against same direction makes successful project, not project methodologies or top management driven projects. Having a clear BI vision, Information Management, Project target, “think big make small” mindset and business driven projects and you have a good potential to succeed.