Business Analytics: how to implement in your company
In a world where Artificial Intelligence is already the new normal, no company can ignore the Business Analytics philosophy. Do you know what it is? Is this already a mindset applied to your business?
In this article, we will take you to a deep reflection on this topic.
Keep reading to understand what is Business Analytics, what impact it will have on your business and how to implement it!
Welcome to the “Data Age”
First and foremost, a contextualization: we do not live what experts are calling the “Data Age”. What they want to synthesize is the fact that the world has changed before our eyes, transforming into a universe of digital data of the most varied formats (text, video, audio, image, etc.).
In the “Data Age,” the volume of information produced and shared every second has become so large that the traditional methods used to process them are no longer adequate. So there is a real rush in the IT industry to develop methods and tools that can turn that sea of data into useful insights.
It is in this new scenario that the concepts of Big Data, Analytics, Internet of Things, etc. have appeared. All of these are terms to describe phenomena, methodologies, tools, and services related to this new era.
In this context, the most competitive organizations are those that are data oriented and therefore treat their information as assets – use them to understand their stakeholders, improve processes, create products and services, communicate better, and so on.
Artificial Intelligence is the new normal
In the “Data Age”, Artificial Intelligence ceases to be something futuristic, background for science fiction films. It is now a reality present in the lives of ordinary people and within reach of companies of all sizes and in the most varied market segments.
According to Gartner, Artificial Intelligence “is a technology that seems to simulate human performance typically learning, coming to its own conclusions, pretending to understand complex content, engaging in natural dialogues with people, improving human cognitive performance (also known as computation cognitive) or replacing people with non-routine tasks.”
In short, Artificial Intelligence consists of programming computers and other devices to, among other things:
- knowledge / recognition of standards – or lack thereof;
- logical “quick” reasoning;
- solution of time-consuming problems of human labor;
- perception of movement, of actions, of statistical alterations, etc.;
- strategic planning – with automated predictive analysis, for example;
- ability to manipulate and move objects, among others.
Within this, increasing the capacity to make intelligent systems and equipment also creates many possibilities – and in many cases, needs – of expanding the analytical power of data of organizations. This is where the concept of Business Analytics gains strength.
What is Business Analytics
We can define Business analytics as the practice of iterative and methodical exploration of an organization’s data, with an emphasis on statistical analysis. It involves the use of advanced technologies and methods of information analysis of the most varied formats, especially in large volumes.
With regard to Big Analytics techniques, we can divide them into two major large areas: a more basic and a deeper one.
Basic Business Intelligence
It involves examining historical data to get a sense of how a department, team, or team member got results over a certain period of time, for example. This is a mature practice that most companies already make use of.
Deeper statistical analysis
It can mean making predictive analyzes by applying statistical algorithms to historical data to make a prediction about the future performance of a product, service or site design change, for example.
It may also mean using other advanced analytical techniques, such as cluster analysis, to group clients based on similarities across multiple data points. This practice is often very useful in targeted marketing campaigns, among others.
Three key Business Analytics methods
With regard to the methods of analysis under the umbrella of a Business Analytics strategy, we have three highlights:
- Descriptive analysis, which tracks key performance indicators to understand the current state of a business;
- Predictive analysis, which analyzes trend data to evaluate the probability of future results;
- Prescriptive analysis, which uses past performance to generate recommendations on how to deal with similar situations in the future.
The most innovative companies today have a Business Analytics strategy for insights that inform business decisions and can be used to automate and optimize processes.
It’s also important to know that a successful Business Analytics strategy depends on data quality, on qualified analysts who understand technology and business, and on an organizational commitment to informed decision-making.
The difference between Business Analytics and Business Intelligence
A lot of people confuse Business Analytics with Business Intelligence, this is an older concept and more rooted in common sense. However, there are substantial differences between these two approaches.
Since we’ve already seen the concept of Business Analytics, we need to understand what Business Intelligence is before we move forward.
Overall, a Business Intelligence strategy is more focused on “what” and “how” – not so much on “why”. For this, the company needs to have a Business Intelligence software (also called BI system).
BI enables you to apply selected metrics to potentially huge, unstructured datasets and covers queries, data mining, online analytical processing and reporting, as well as business performance monitoring, predictive and prescriptive analysis.
In the “Data Age” we could say without fear of making a mistake: Business Intelligence is old school! What really raises the competitive power of a business is its ability to look to the future and act on what is expected.
Where is the difference?
Business Intelligence is a worried approach to what happened or what is happening now in your business. For this, BI platforms deal with historical data that lead to the present, and what you do with that information is up to you.
A Business Analytics strategy predicts what will happen in the future. A Business Analytics platform combines advanced statistical analysis and predictive modeling to give you an idea of what to expect, so you can anticipate developments or make changes now to improve results.
So both approaches are valuable, only in different ways.
Impacts of Business Analytics in your business
Here are four of the key impacts a Business Analytics strategy can have on your business.
Business Analytics helps you quantify company values
Most companies have a mission statement and train employees on the core values that lead to success. What many fail on, however, is to quantify these values.
With a Business Analytics strategy, organizations can measure how these values translate into numbers. Using quantifiable data, broad values, and mission statements, they take control of the interpretation of their values. So they can focus on working with processes that stay in line with what really matters.
For example, a company can identify its return measures, both tangible returns (such as profits) and intangible returns (such as returning to the community). These can be quantified to clearly define expectations for employees. This should improve the processes, because everyone will be working towards the same clear goal.
Encourages smart decision-making in corporate culture
With more information at your fingertips, it is easier to empower the team to make quick decisions. Rapid movement and development are important to a business that wants to stay ahead of the competition. Equally important is the careful consideration of each decision.
Nothing can derail a business faster than going the wrong way. Making quick decisions is easy, but the most important thing is to make smart decisions in a short amount of time.
With so much data available, it is possible for everyone – not just leaders – to make informed decisions. That’s why every department needs access to the various modules of a Business Analytics system. The practice should be rooted in corporate culture.
Provides a wider one in a timely manner
Have you ever heard the expression “a picture is worth a thousand words”? Words and numbers are great when you need to delve into detail, but visualizing data can be a better and faster way to distinguish clear trends.
Using visual data can make companies more agile, help them find faster insights, and make decisions without having to spend so much time to understand what’s really going on in the marketplace.
With graphics and other visuals, decision makers make faster choices; in a timely manner.
Helps the company not to be left behind
Today’s world moves faster than ever. The way people buy consumer goods is changing. The way companies communicate is changing. The way organizations reach customers is changing.
With so many changes happening at such a fast pace, it’s easy even for the biggest and smartest companies to be left behind.
A good Business Analytics strategy can prevent business obsolescence. Using analytics allows the company to create continuous business and market forecasts.
Keeping abreast of the latest forecasts can spark innovative ideas, bringing more depth to the brand. Improving processes paves the way for launching innovative products and services.
Implementing the Business Analytics mindset in your business
Now, all of this may simply not happen if the mindset, i.e. the corporate mindset does not change. It’s no use implementing the most powerful Business Analytics platform if leaders and key employees continue to act as they once did.
Therefore, you need to create a “Business Analytics culture. Here are some tips to make it happen.
Update IT capabilities
Traditional / legacy IT structures can prevent new types of data provision, storage, and analysis; can hinder the integration of information, among other obstacles.
The total resolution of these problems usually takes years. However, business leaders can meet the needs of large volumes of short-term data by deploying more modern and up-to-date applications.
It is not always possible to do this without outside help. So it is recommended to get help from a consulting firm specializing in Business Analytics.
Prepare people for data-driven management
Both the technology team and the users (from business managers to operations professionals) need to be sensitized to the “Data Age”. You have to show people that the company deals with your data as important assets.
In this effort, it is worth promoting lectures, encouraging the realization of training courses, conducting internal competitions to capture ideas and to know new systems and methods, etc.
Expand the analytical power of leadership
In the same way, leaders must update their analytical skills. This means exploring Business Analytics applications without difficulty interpreting graphics and other visual formats.
In many cases, it is necessary to take courses. Look for skills that do not focus so much on the technical details and are more applicable to executives’ daily routines. Thus, they will enter much faster in the new climate.
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