BI alone is not enough
Business Intelligence has much in common with a number of other sciences and knowledge areas that, in order for BI / Analytics to reach its full growth, must work together very well (see figure below):
This ensures that an organization carries out its (strategic) activities according to a certain plan. Business Intelligence shows organizations whether that plan also works (out) in practice. The feedback that Business Intelligence provides with regard to the business operations may encourage the strategic managers, as you will see in the first chapter of our book ‘The Intelligent organization’.
Change Management aims to increase the adaptive capacity of organizations so that adjustments can be realised quick and effective. Changing (or adjusting) in general terms is also part of change management. Business Intelligence is an important tool for this: it provides information that proves whether the business operations need changing and whether implemented adjustments are indeed effective.
Moreover, without actions and changes, Business Intelligence is rather useless. Both BI and change management thus aim to increase the adaptability of organizations. Business Intelligence does this through reliable information that is rapidly applicable, whereas change management also uses – besides BI – other disciplines, such as HRM: employees are taught new skills or new employees are recruited.
Innovation is a discontinuous renewal within a process or a product or a service. Innovation management consists of four components: product, process, structure and technology. Through innovation, organizations wish to develop new products for existing or new markets (product component); improve business processes (process component) and ensure lasting anchoring of innovative capacity within the organization (structural component). The organization often encourages all this through the use of new technology – sometimes necessarily – combined with new competences.
Knowledge of products, trends in society, customer needs, new technology and raw materials is essential. In order to achieve lasting innovation, the organization must create, combine and distribute the above knowledge efficiently and methodical. The relationship between Business Intelligence and innovation management is two fold:
- Firstly, BI both delivers information as a source for the knowledge we need to be able to innovate and stimulates employees to use the information to come up with ideas on how to improve processes and products.
- Secondly, the applications of BI may serve as an innovation in itself: we may for example use BI applications to share information online – paid or free of charge – with suppliers, customers and other business partners.
Knowledge management aims to optimally organize and evaluate knowledge within organizations in order to develop, combine, disclose, distribute, share and apply knowledge. Knowledge management is also about creating an environment in which people are both encouraged and invited to cleverly combine their own knowledge with the insights of others in order to improve performance. Business Intelligence aims to convert raw data into information and (new) knowledge. See also: The future of Business Intelligence.
An example: when we combine the specific sales data of a car importer with general demographic data, we may find out that besides wealthy two-income families, also single men who are older than 45 and who earn above average are potential buyers of sporty SUVs, particularly in urban areas. Subsequently, we can actively distribute this (new) knowledge within the organization so that employees can take targeted action. In a joint effort, the marketing and the innovation departments may, for example, decide upon the development and production of a ‘light’ version of the SUV, specifically for people with an income that is slightly above average.
Imagination is more important than knowledge
Knowledge management is often associated with innovation: after all, knowledge is the basis for generating new products and for process optimisation. Besides that, good managers must be open for imagination: the creative basis for smart innovations and ideas. Einstein once said: “Imagination is more important than knowledge” and “logic will get you from A to B. Imagination will take you everywhere.” We use our knowledge to assess the feasibility of our ideas – thus after the imagination – and to implement them. organizations that wish to innovate thus require both elements (Drucker, 2002).
Information management is about controlling and effectively implementing information (and communication) technology (IT) in organizations or between organizations. This involves both the design and the infrastructure of operational, tactical and strategic information supplies. On the tactical and strategic levels (look also at the tool MicroStrategy), information management shows large overlaps with Business Intelligence, however with the latter the emphasis is not only on the question how – and with what data and information – IT can best support the business processes, but also on how we can proactively use IT for solving – not yet detected – ‘problems’.
Data Management & ETL
Lastly, Business Intelligence is to a large extent dependent on data management: the way in which the organization defines, interprets, registers, stores, integrates, distributes and discloses data and monitors the quality of those data. The better an organization manages its data, the greater the chance of Business Intelligence reaching its full growth.
Business Intelligence is most effective when all the above-mentioned disciplines start to collaborate closely. This enables organizations to change and improve based on well-founded strategies and decisions and allows for an organizational culture with room for knowledge exchange and for innovation processes that are supported by both professional data management and by Business Intelligence.