What is Business Analytics? Process, tools, benefits and examples
17/06/2021 • 5 min
Business analytics is one of the factors that determines companies’ competitive position. It provides management with access to information that allows them to properly assess the situation and make informed decisions.
Why is business analytics so important for running a business, what determines its quality, and what are its types?
Those who have access to information win. This is a simple rule that has applied for centuries in virtually every area of life, including business. If we distinguish between companies that effectively provide their decision-makers with various types of information and those that do not, it turns out that companies in the former group have significantly better business indicators – in every important area of activity. As a result, over time, companies in the first group develop faster and gain market share, while those in the second group systematically worsen their situation and weaken their position.
Progressive digitalization increases the appetite for business analytics
One of the consequences of the digital revolution that has taken place over the last dozen years is the exponential growth of data that enterprises want to process and analyze. The amount of data that needs to be processed due to applicable regulations is also growing.
For companies, this brings challenges related to digitalization and, at the same time, the threat of rising costs.
To properly understand the business need related to information processing, it is worth realizing how many data sources companies currently use. For example, in the market area covering sales, marketing, and customer service, businesses currently use on average 4-5 times more data sources than ten years ago. The days when managers primarily asked what customers actually bought are long gone.
Currently, dozens of other pieces of information are equally important – such as product search history online, competitor price comparisons, social media behavior, customer geolocation, their expressed opinions, statistics and scenarios of visits to individual website tabs, histories and courses of contact with company representatives, etc. Similar challenges related to the need for effective information processing can be found in every other area of company operations – from purchasing, through production, to logistics, HR, and financial management. Practically everywhere, managers’ appetite for information is rapidly growing each year, and the sources of this information are constantly increasing.
Read also: Cloud solutions for organizations interested in business analytics
Business analytics requires support from IT and artificial intelligence
It should be remembered that while the demand for information in companies is constantly increasing, processing data for decision-makers is becoming an increasingly complex process. If appropriate analytical tools are not implemented as the company develops, information management most often begins to generate increasing costs, and the quality of information available in the company depreciates. The game is also about ensuring that relevant information reaches decision-makers as quickly as possible. Without proper business analytics based on IT analytical tools, the time challenge becomes critical. In extremely negative cases, organizations not only incur huge costs associated with preparing information for internal use, but additionally, these statements are riddled with errors, and the data contained therein is no longer current, as it has become outdated by the time reports are prepared.
IT companies, which daily deal with implementing various analytical models and tools in enterprises, are well aware of the importance of challenges related to business analytics.
In our projects, we rely on Qlik Sense and QlikView analytical tools. We know the situation of companies before implementation and after project completion. We see how much potential organizations unleash by eliminating burdens and how much more efficiently they begin to manage. Decision-makers obtain required information online, and available reports are based on real-time data. Moreover, most, if not all, analyses are generated on demand, without involving people who previously dealt with data collection and presentation. This is a great saving on one hand. However, perhaps an even greater benefit is the opening of various previously unavailable opportunities within the company, associated with effective information analysis in contexts important to decision-makers.
Essentially, wherever analytical solutions are implemented that integrate information to quickly and conveniently make it available to users, the common denominator is the high comfort of managers’ work. In such companies, management unanimously emphasizes that they feel they are basing decisions on reliable data. In business, this is very important because it allows for designing changes, improving processes, and simultaneously motivating every move. A manager does not manage because they ‘think so,’ but because they ‘know.’
Where to start implementing analytical tools?
Currently, practically every operating company uses IT solutions in its work. Usually, systems and applications are equipped with certain functionalities whose task is to provide information from the areas they support. In many cases, these are sufficient. Often, however, managers have analytical needs that go beyond the standards offered by the systems. In such situations, the company should implement tools to support information management. Apart from domain-specific systems for handling specific areas of activity, such as ERP, SCM, CRM, or MES, in larger organizations, analytical needs are usually met by a properly implemented Business Intelligence solution, whose task is to integrate multi-source data, mainly from systems and applications used by the company.
To verify the extent to which a company needs business analytics, managers in the enterprise should define as precisely as possible whether the information they possess for management is sufficient (scope, data reliability), whether they have convenient access to it, and whether its preparation does not consume too many resources (time, financial means). If the answer to one of these questions is negative, it is a sign that the area of business analytics should be optimized. In some cases, it is enough to better utilize the functionalities available in the company’s existing systems and applications. Often, however, it turns out that the company requires analytical tools.
Read more: Data analysis tools
Types of business analytics
Business analytics is divided depending on the purpose for which information is sought, its nature, and how it is obtained. In professional literature, several ways of categorizing business analytics can be found. One of them is the division into:
predictive analytics – deals with modeling the future and forecasting,
prescriptive analytics – defines possible scenarios, options, and consequences of potential decisions,
diagnostic analytics – answers the question of causes (of phenomena, events) based on historical data,
descriptive analytics – processes historical data to describe phenomena, results, facts from the past,
cognitive analytics, which uses advanced artificial intelligence and machine learning technologies to
process large amounts of data, often of an atypical nature, to support managers’ decisions or automate decision-making.
In addition to the above, there is also a division into various types of analytical tools designed to support the work of managers in different areas of the company’s operations. It is worth emphasizing that managers have different information needs depending on their role in the organization. The board and financial department primarily rely on Business Intelligence solutions. Sales uses CRM solutions and selected modules of the ERP system. In the area of production and logistics, in addition to ERP, MES (Manufacturing Execution System) can be an invaluable solution, which, among other things, supports machine park management, schedules production, and monitors machine operation on production floors in real time.
The diversity of dedicated IT solutions responsible for data processing shows how crucial analytics is in business. Every time decision-makers think about optimizing their business, it is worth paying attention to this issue – whether the organization effectively manages the data it processes. This can be a starting point for implementing positive changes.
IT companies, which daily deal with implementing various analytical models and tools in enterprises, are well aware of the importance of challenges related to business analytics.
In our projects, we rely on Qlik Sense and QlikView analytical tools. We know the situation of companies before implementation and after project completion. We see how much potential organizations unleash by eliminating burdens and how much more efficiently they begin to manage. Decision-makers obtain required information online, and available reports are based on real-time data. Moreover, most, if not all, analyses are generated on demand, without involving people who previously dealt with data collection and presentation. This is a great saving on one hand. However, perhaps an even greater benefit is the opening of various previously unavailable opportunities within the company, associated with effective information analysis in contexts important to decision-makers.
Essentially, wherever analytical solutions are implemented that integrate information to quickly and conveniently make it available to users, the common denominator is the high comfort of managers’ work. In such companies, management unanimously emphasizes that they feel they are basing decisions on reliable data. In business, this is very important because it allows for designing changes, improving processes, and simultaneously motivating every move. A manager does not manage because they ‘think so,’ but because they ‘know.’