Evolution of the Business Intelligence (BI) into business analytics?

Business Intelligence (BI) is a relatively wide-ranging concept, that has evolved during years. Put simply, it may be described as data acquisition from various sources with a view to processing it into valuable business information.

Often these systems are named, for example, Management Information System, Integrated Management Information System, Management Reporting System, Decision Support System, etc. Usually, they include reporting and management areas, sometimes in a strategic context.

The beginning

The term Business Intelligence (BI) was coined by Richard Millar Devens in 1865 in the context of a certain banker. The banker was rapidly maximizing profits thanks to decisions made based on information acquired in advance.

Until today, it has been considered the simplest and most accurate definition of how such a system should work. The term returned to prominence in 1958 in the article by Hans Peter Luhn and described an ability to understand relations between presented facts in a way that will lead to actions in order to reach a certain result.

Evolution: Business Intelligence (BI) systems of today

In a nutshell, the BI system is comprised of two basic elements: information stored in a database and the tools to visualize it. Obviously, data needs to be acquired, it does not materialize out of thin air. We are dealing here with the first important element of the whole system – the process of data extraction from source systems, data cleansing, and then uploading it to the database.

It is a process that is as important as it is marginalized during the implementation phase, despite the fact that the ability to acquire and consolidate data determines the value of Business Intelligence (BI). This is the stage at which we consider the method of data integration, historical data migration, as well as the method of merging historical data with new records (especially when we are changing systems).

Migrate or not to migrate, that is the question?

Often, due to high costs and the time-consuming process, companies decide not to migrate resources or migrate them without mapping the old data onto new structures. This contradicts, however, the very idea that made us in the first place implement the previous system and acquire data over many years. That way, it renders the data useless in the analytical context.

The absence of historical records limits the ability to make strategic decisions based on data spanning a long time frame. This brings us back to square one – to a blank sheet of paper.

In turn, this significantly delays the ROI of the new investment. Why? In order for the BI system to provide proper information, it needs to acquire a sufficient volume of information for analysis so it can step out of the existing range of generated reports.

Data quality is the foundation

High-quality data maintenance requires a disciplined, proficient, and experienced implementation team and a substantial initial workload. This results in long-term time and money savings. It does not mean that the high-quality source data model needs to be complicated and difficult to maintain.

Well-organized information provides more analytical options and full utilization of the investment potential. The ability to sort data transparently with respect to functions, as well as its organization to be clear to system users and beneficiaries, will always be an additional advantage.

Report or analytics – it is your choice!

A database as a system of tables storing data would be useless if the data was not organized based on the data model. Its transparency is a crucial feature determining future system use.

The key question is: are we investing in the Business Intelligence (BI) system so we can generate more reports to put in binders, just as our employees used to do? Or are we doing it to let them focus on more important tasks like data analysis and drawing conclusions enabling strategic decision making? (Does it sound familiar? Yes, it’s 1865 all over again!) It is tempting to say that this is the reason for any implementation. In many cases though, we lose our way in the project jungle and we forget the objectives we set ourselves at the very beginning. It’s crucial not to lose sight of them.

The last elements of our jigsaw puzzle are the reporting and analysis tools. Which ones to choose? All-in-one or portfolio? It is valuable to decide on tools with longer-term perspectives so that there is enough time for investment return. The market is full of appropriate tools, but any should be chosen to satisfy our requirements and needs and give ease of use, not just for reporting, but for analytical purposes.

Business Intelligence (BI), Business Analytics, or Big Data?

The market is bursting with an array of terms that may lead us astray and make us lose sight of the core problem in question. It is irrelevant whether we call our system BI or BA – it will still need to satisfy the criteria established in 1865.

New technology allows for the processing of an ever-growing amount of data increasingly generated by humans. At the same time, we use only a fraction of available data for analysis. The capabilities of various systems provide us for the first time in history with the ability to process all kinds of information – structured and unstructured; not only in traditional formats. We are currently on the verge of an age in which the “strategic reporting” term not so much gains new meaning as it finally has the chance to be fit for purpose.

Up until now, BI systems were associated with reports for management boards detailed for the purpose of strategic decision making. Batches were imported during the night, always from the day before, aggregated because detailed data is located in source systems and is unnecessary at management level.

If, however, we combine the number of decisions made each day by our employees, it turns out these decisions are strategic too: on a much lower scale, but their sum shapes the company. Is there a better method to support their tasks than providing them with the ability to explore data they deal with on a day-to-day basis more thoroughly?

Revolution or evolution of Business Intelligence?

The time has come for the phrase “analytics” to appear at every level of the organization, where the BI system can and should be available. But what for? It is not only to increase our company’s competitiveness in the world where everyone has “some kind of BI”, but it also puts emphasis on us, who have carefully selected our employee base to contribute to the organization further. In turn, and at the same time, this raises the competence level, and as a result, the market value of the company and its competitive advantage.

A company is made up of people and the sum total of their decisions: however small and big. In our fast-paced world there is no such thing as an insignificant solution since often, it can be the key factor contributing to success on the market. These are the reasons why employees should be equipped with the best tools to support these processes.

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