Within the field of Business Intelligence and Analytics, the following developments will gradually take shape and gain momentum:
Less ‘technology push’ as Business Intelligence matures
In recent years, Business Intelligence has proved to be highly technology-driven. It was all about snazzy reporting tools with all sorts of bells and whistles, performance, technical debates about the most suitable data modeling method, and advanced drill-down possibilities. These ‘toys’ diverted our attention from the real purpose of Business Intelligence, namely creating a truly intelligent organization. Fortunately, today we see that Business Intelligence is increasingly driven by the business, and that the attention is shifting to the behavioral side. Many organizations today prepare a business case in advance in order to assess whether the payback period of data warehouses and Business Intelligence applications is in line with current economic and business standards. Business Intelligence becomes increasingly business-driven and permeates the organization more easily. Business Intelligence gradually matures and technology becomes secondary to the processes and applications.
The advance of BI governance
An increasing number of organizations no longer regard Business Intelligence as an isolated concept, but rather as a strategic weapon that goes hand in hand with knowledge management, strategic management, innovation management and change management. “Information, used in the right way, is particularly suitable for achieving competitive advantage –particularly because many Business Intelligence solutions today are (as yet) unsuccessful .” The focus no longer merely lies on the processing process of the BI cycle, but is increasingly equally divided between all three basic processes of the BI cycle. Thanks to Business Intelligence, information and knowledge are embedded in the business processes better and faster, enabling organizations to respond more quickly. Due to the advance of BI governance, the organization of Business Intelligence will be formalized in the form of a BI competence center or a shared service center in which all Business Intelligence skills are coordinated.
Good metadata becomes increasingly important
Business Intelligence tools will become more and more integrated, allowing us to go through both the decision-making cycle and the Business Intelligence cycle in one go. This requires proper storing and exchanging of metadata. Additionally, the wide acceptance of data warehouses – in which metadata is also stored – stresses the necessity to organize the metadata in the organization properly. The same applies to the increasing importance of both supply chain management and the provision of digital services. After all, external data is increasingly viewed as crucial information for effective Business Intelligence. Presently, this data is mostly unstructured and without metadata, and therefore causes various connection problems. All good reasons for organizations to get serious about metadata.
All kinds of integration grow closer
In the future, these three technologies will converge and integrate. Particularly, the steady advance of portals whereby these technologies often merge in the context of the pivoting of the organization and the provision of electronic services. Already, suppliers of ETL tools also offer various EAI possibilities, and vice versa. Although these tools partly overlap, ETL and EAI remain two separate worlds with fundamentally different natures that will not simply converge on a technical level. In other words: ETL tools and EAI tools will not replace one another easily. What we do see is that some organizations use EAI tools for the filling of staging areas with a straightforward extraction. However, both the major bulk processing of data and the more complex transformations will remain the domain of ETL.
Business Analytics competes with Knowledge Management
While Business Analytics gains importance, both the importance and the status of KM within organizations diminishes. Business Intelligence is eating up major parts of the ‘KM-pie’, as it were. Fortunately, through this, KM is being integrated into Business Intelligence. There has always been some common ground; data mining, for example, can be positioned under both disciplines. However, the methods and basic principles of the two disciplines are essentially very different. Where KM takes knowledge as its starting point, BI takes the signals and data that underpin information and knowledge as its starting point. The better we set up the registration of data, the more likely it is that we create and discover the information and knowledge we require (using BI). It is then no longer necessary to rely solely on the existing knowledge of (our) people, because that same knowledge also exists – although still hidden – in the data sets belonging to the registration systems. Therefore, we see that the area of attention of KM shifts, because we need to focus less on existing knowledge within the organization. Instead, in order to maintain distinctive quality, we increasingly need to focus on creating new knowledge – this is already happening – and thus on innovation processes. People play a crucial role in this creative process. In the meantime, Business Intelligence has gained importance as a discipline and plays an increasingly important role when it comes to defining existing knowledge in organizations. The knowledge that is gained with Business Intelligence, however, still needs to be combined, distributed and applied. Moreover, it is dangerous to ignore the knowledge that people provide. That knowledge should also be combined, distributed, and applied. The point here is that the market seems to make a clear choice in favor of Business Analytics.
Business Intelligence is maturing rapidly
The world of Business Intelligence is still in flux, but the turbulent early years are over. The essence of Business Intelligence is increasingly understood, and Business Intelligence is maturing rapidly. This is not only because it is increasingly business-driven – which is of course also due to the improving technology – but more because various standards and applicable models are (being) developed that contribute to improve management and governance of Business Intelligence in the organization.