The 5 Biggest Benefits of Analytics

Managers are busy and often interrupted

Mintzberg (1973, 1975) observed a group of managers and came up with a set of job characteristics – also applicable to knowledge workers – that are highly relevant for Business Intelligence:

• they always have a lot of work to do;
• their work is varied, fragmented and dealt with quickly;
• they are often interrupted or disturbed during their work;
• they have a preference for liveliness and action;
• they thrive in a more or less chaotic environment;
• they seem to love “soft” information such as gossip, rumours and speculation;
• they regard problems as a network of interconnected relationships.

From these characteristics, we can draw at least one conclusion: managers (and knowledge workers) have little time and little desire to sit behind their desks and if they do find time, they are often interrupted. Business Intelligence can be a great help to managers but only if the Business Intelligence system complies with a number of requirements. In the following paragraphs, we describe these requirements thoroughly in relation to defining, processing and consuming information.

1. The output of knowledge workers can increase substantially

At the beginning of the twentieth century, the ratio of doers to thinkers was approximately nine to one. In the year 2000, management guru Peter Drucker forecasted that this ratio would be reversed by 2015. It is evident that one of the greatest challenges of organizations today lies in improving the thinker’s productivity. Without Business Analytics, these knowledge workers too often do relatively low-grade work.

Get ready-to-use management information

Processes in the area of data collection, data selection and data retrieval are usually highly labor intensive. Analytics principally focuses on this: to get ready-to-use management information to the right knowledge worker, at the right time and in the right form, whether employees, customers, shareholders, suppliers or information systems. This way the productivity of knowledge workers – who are often costly – inside and outside the organization can increase dramatically since Self-service Business Intelligence allows them to work autonomously.

All data comes from one source

With BI / Analytics, the knowledge worker gains access to various sorts of data and ready-to-use information, which they can combine, arrange and apply making their activities run much more smoothly and thus increasing productivity. All data comes from the same source, e.g. a data warehouse, and fits together, allowing knowledge workers to work seamlessly together. Article numbers, for example, are presented in one and the same format and can thus be easily linked to other data even when that data originates from a different source where article numbers are listed in another format. Because knowledge workers are enabled to execute their tasks more easily, they can spend more time communicating with colleagues, customers, suppliers or other business associates.

The knowledge worker will organize their information more efficiently

Thanks to Self-service Business Intelligence, the often costly knowledge worker will organize their information more efficiently, the costs of searching for information will reduce, the process of assessing and sharing information will accelerate and lastly, the collaboration between knowledge workers will increase.

2. Determined searches, better performance

Useful information, which encourages managers to further research and decision making, does not just happen. During the first phase of the decision making process, managers are mainly searching for information that demands a decision. This could be information about a sudden increase of absenteeism; a strong decrease in profit margin; a sharp growth of market share, or information about a competitor suddenly appearing in the market.

Scan a broad range of information sources

Interesting in this context is the fact that the performance of an organization increases when managers naturally look at a broad range of information sources (broad systematic scanning) and indicators. There is a strong indication that this is especially important for senior executives. The reverse is also true: ‘proof’ exists for a clear link between ‘broad systematic scanning’ and improved performance (Daft et al., 1988). These researchers concluded that senior executives of high performing organizations ‘scan’ more often and more frequently compared with senior managers leading organizations that perform poorly.

Which information is important?

With Business Intelligence, ‘scanning’ will turn out to be more effective as consideration is given in advance to which information is important – also in relation to other information – in order to realize targets and achieve ambitions. Using a KPI dashboard tool (for example Yellowfin) in combination with a sophisticated Business Intelligence system under the hood, more coherent and relevant information will reach the manager.

3. Better balance between intuition and brain

People make mistakes when they interpret data and try to familiarize themselves with information (Bacon, 1620; Borgman, 1994). The most well known and perhaps most common mistake is that people tend to make logical reconstructions of the whole even when pieces of information are missing. This may result in an incorrect overall picture. People often link non-objective conclusions to certain events or specific behavior simply because their own perceptions are often biased. Although intuition and instinct are highly desirable qualities for managers, they must be fed by reliable data and backed up by evidence (Mintzberg 2004; Isenberg, 1996).

Business Intelligence systems enable facts to be presented quickly and from different angles. This way Business Intelligence creates a better balance between gut feeling and reason. In chapters four and five of the BI book ‘Data Science for Decision Makers’ we will present a list of human errors and the “solutions” that Analytics offers.

4. One version of the truth

Organizations often use several ‘information systems’ upon which managers and knowledge workers base their decisions. If these ‘information systems’ do not rely on a common source or do not use the same definitions, this may – in many cases – lead to inaccurate communication about the reality of a situation and even worse, lead to incorrect decisions. Business Intelligence allows definitions to be integrated throughout the organization. For example, the service level for the inventory department is calculated using the same method the account manager uses. During the implementation of a Business Intelligence system, we often find that data forming the basis for definitions is not consistent.

BI creates a reliable and integrated picture

For example, certain product groups in the order system are not the same as the cost categories in the financial administration. For that reason, Business Intelligence cleanses the data, combines, and links it to ensure that information derived from this data becomes consistent. This creates a reliable and integrated picture of business processes and customers across the various departments in the organization.

5. Reduced information overload

In an ideal information society (and information economy) people know exactly what is relevant and what information they need in order to achieve their goals. However, due to digitalization and globalization, decision makers have such an overload of unnecessary “information” at their disposal that they cannot see the wood for the trees. This information overload may lead to certain forms of stress and in the worst case to a total standstill: one simply does not know what information is relevant to move forward.

The information paradox

This is also known as the information paradox: although more than enough “information” appears to be available, at the same time there is a serious lack of real information because nobody seems to know how to determine which information is relevant for their needs and subsequently how and where to find that information. Business Intelligence can solve this by reducing a number of selections, aggregations and visualization processes and help knowledge workers and managers to distinguish what is relevant and what is not. What management information and KPIs does a manager need to achieve his objectives? Based on that question, one determines which signals to catch and what data to capture in order to be able to respond adequately.