Advanced Business Intelligence through AI-driven decision-making
BI and AI are different technologies used in modern companies over the last decades to contribute to their development and growth. In addition, both can complement each other to enable companies to analyze and interpret large amounts of data to make consistent data-driven decisions and develop coherent strategies. But how exactly does it work?
This is what we will answer in this article by first explaining how each technology works.
What is BI and its goal?
Business Intelligence combines the methodologies and the use of tools with which a company's data are gathered and processed to generate indicative information, mainly reported in a dashboard, chart, graphs, spreadsheets, and performance metrics on which the head of the company can base his decision.
“Business Intelligence (BI): A tool to help companies to make operational and strategic decisions.”
However, BI tools are not intended to give specific instructions on how these data should be used in decision-making; instead, they can turn noisy and raw data into a meaningful picture and business insights. Professor of Business Analytics and Operations Management Michael F. Gorman stated that "BI doesn't tell you what to do; it informs you what was and what is."
For this, IT giants like Microsoft and Oracle developed BI tools whose primary function is to collect, organize, visualize and analyze the data accumulated in business operations to highlight trends and patterns for making decisions based on actionable data.
In the image below, you can see the result of data reporting with Power BI Desktop.
Examples of BI use cases in a company:
Businesses can track campaign KPIs from a central digital location with the use of business intelligence solutions. BI systems can offer real-time campaign tracking, evaluate the success of each attempt, and help with campaign planning. With the use of this data, marketing teams are better able to assess overall performance and provide contextual graphics with the business.
Key performance indicators (KPIs) and BI dashboards are frequently used by sales data analysts and operations managers to provide quick access to complex data including discount analysis, customer profitability, and customer lifetime value. Sales managers use dashboards with reports and data visualizations to track revenue targets, sales rep performance, and the state of the sales funnel.
Managers may access and evaluate data like supply chain analytics to find methods to enhance procedures, saving time and dollars. Additionally, business intelligence can help optimize distribution channels and guarantee that service level agreements are met.
What is AI and its goal?
Artificial Intelligence (AI) is a wide-ranging branch of computer science that aims to model human intelligence. The model or the algorithm can learn from company data and make rational decisions.
AI has the potential to allow computers to make business decisions on their own, in contrast to BI, which significantly simplifies the process of data analysis while leaving decision-making to humans. For instance, chatbots can respond to client inquiries devoid of human involvement. AI may provide human operators recommendations and can act on those recommendations independently, going beyond simply bringing clarity to a confusing sight.
“Artificial Intelligence (AI): AI can learn from data and provide business decisions by itself automatically.”
To create an AI model, businesses must either engage data scientists or, more affordably, use a platform like SmartPredict, a no-code low-code AI platform that automates the entire AI process up until the generation of data prediction.
The image below shows you the sales forecasts on the SmartPredict platform generated by the AI models that have learned from the data of SmartPredict's client companies.
How does AI enhance BI?
Making business users into data experts
AI is useful for BI in the way that it can extract meaningful, actionable insights from the data they analyze. AI-driven systems can precisely define the value and the significance of each data point and help business users to take comprehensive action on how data may be used to make actual business decisions.
“AI in BI: Companies can leverage vast amounts of data into coherent action plans by combining AI and BI.”
Helping you explore data
From the moment you make data available, the AI in the BI system does the heavy lifting by automatically classifying columns, tagging them, and joining matching data across sets. With AI-enabled BI solutions, users receive suggested and automated visualizations that best fit the answers to their questions.
Understanding the End-User
The more a user interacts with a business intelligence (BI) tool, the better it becomes at understanding what that user wants in their analysis and presentation. Machine learning can help BI systems customize and improve over time by cataloging and learning from the user's typical behaviors and questions.
Automatic Data Preparation and Cleaning
AI automation process always includes automatic data cleansing and preparation. With automated data processing, you can go from making data available to working with it in minutes. Future AI in BI functionality will allow users to input both structured and unstructured data without skipping a beat.
Getting an edge over competitors
Gartner predicts that by 2024, 75% of prebuilt reports will be replaced or augmented with automated insights. AI inBI saves time and provides actionable insights to increase profitability. Powerful AI in BI tools also offers improved accuracy for operational usage reporting.
Example of Application of AI in BI with SmartPredict platform
As mentioned above, AI can improve BI processes, making them faster and more accurate and providing actionable decisions based on accurate forecasts predictions or by generating accurate and actionable decisions.
In this section below I will describe to you some examples of AI applications in BI by using the SmartPredict platform.
In marketing: Predicting the outcome of prospecting
With SmartPredict, you can present your data on your historical lead to training a Machine Learning model that will predict whether prospecting on new leads will be negative or positive. It gives you a rational value of the success of your campaign on new leads so that it helps you in deciding to enhance your future marketing campaign.
In operation: Getting an automatic supply chain prediction
By running SmartPredict’s Sales Forecasting and Inventory Optimization use case you can
get an accurate planners forecasting of the demand, the right quantity required at the right time span, and inventory level management automation. By the end of the whole process, we can expect a scheduled ordering plan at the item level along with its optimal quantity to order.
In Sales: Getting accurate sales forecasting
With SmartPredict Autoflow, you can present your sales history and other data and parameters that may impact your sales to forecast and generate accurate sales forecasts. This will give you a rational idea of how your weekly, monthly or annual sales are evolving and help you make good decisions in managing your business.
Data is a resource like gold for companies to ensure their development in their business if it is exploited in an optimal way. AI in BI or combined AI in BI is an excellent methodology to harness it ideally and make advanced, rational decisions. The SmartPredict AI platform enables you to leverage AI in BI with its AI use cases and AI automation processes that allow anyone, regardless of their area of expertise, to perform an end-to-end AI project.
Feel free to visit the website and start your AI project for free.