Data, a gold mine within your company

Do you want to understand your customers, increase your sales and anticipate market trends? Data analysis is key! Discover in this blog the different types of data analysis available: descriptive, diagnostic, predictive and prescriptive. Each of them has its own use and can provide valuable insights to improve your business. We'll also give you real-world examples to help you understand how each type of analysis can be used in different industries. Don’t miss this opportunity to discover how data analysis can boost your business!

I. Types of data analysis projects

Often, people will mistakenly believe that all data is the same and that analysis projects all have the same result. Within data analysis, we find several types of analysis, in this blog we will talk about the 4 main objectives for data analysis within companies.

Descriptive analysis is the process of synthesizing and describing data to understand your customer base, your sales, trends and so on. This type of analysis is used to answer questions such as “What happened?”» or to have a “screenshot” of the current and past situation. For example, a retail business can use descriptive analytics to understand which products are selling well and which are not, in order to readjust their inventory and marketing strategy.

Diagnostic analysis is the process of investigating problems or more specifically, problems in data. This type of analysis is used to answer questions such as “Why did this happen?”» or “How to solve this problem?”". For example, a transportation company can use diagnostic analytics to understand the reasons for declining customer satisfaction by using their vehicle performance tracking data and customer feedback to identify key drivers of poor performance. experience.

Predictive analytics uses statistical models and machine learning algorithms to predict future outcomes. This type of analysis is used to answer questions such as “What will happen?”» or “How can I anticipate trends?”» For example, a telecommunications company can use predictive analytics to forecast future bandwidth demand by using past bandwidth consumption data to train an artificial intelligence-based forecasting model.

Lately, prescriptive analytics is the process of recommending actions to optimize outcomes based on predictions. This type of analysis is used to answer questions such as “What should I do?”» or “How can I improve my results?”» For example, a finance company can use prescriptive analytics to optimize investments by using data on past investment performance and economic forecasts to identify the best investment options.

II. Benefits of Data Analytics for Business

In the next two sections, we will discuss some of the benefits of using data analytics for your business.

Informed decision making: Data analytics allows businesses to make better decisions by providing insights that would be difficult or impossible to discover through other means. For example, a restaurant can use data analysis to identify which meals sell well, which evenings are busiest, and customer trends, all in order to adjust their inventory and marketing strategy. .

Increased efficiency and productivity: Data analytics helps businesses identify inefficiencies in their operations and take steps to address them. For example, a manufacturing company can use data analytics to identify which machines or processes are causing the most downtime, and take steps to make its machines more efficient.

Increased competitiveness: Data analytics helps businesses gain insights into their industry and identify new opportunities, allowing them to stay ahead of their competitors. For example, a company can use data analytics to track industry trends and anticipate future customer needs, allowing it to offer innovative products or services before competitors.

III. Return on Investment (ROI) for Data Analytics

Implementing data analysis solutions obviously generates costs. These costs include software and hardware, as well as the cost of hiring data analysts or data scientists. Costs for such data analytics projects can vary widely depending on the scope and complexity of the project, as well as the size of the company. According to a 2020 report from Dresner Advisory Services, the average cost for a small to medium-sized data analytics project is around $150,000, while the average cost for a large-scale project can range from $500,000. $ to $1 million or more. Here it is important to understand that this cost is called average, so this includes smaller projects of $10,000 and much higher projects. Additionally, this includes projects where the hiring of analysts may be required.

Potential savings and revenue increases resulting from making informed decisions and increasing efficiency: One of the common uses of data analytics is to identify inefficiencies in their operations and take steps to remedy them. This approach allows companies to save money and thus increase revenue. This efficiency is crucial for any company that wants to innovate and grow in our hyperconnected world. For example, a retail business can use data analytics to identify which products are selling well and which are not, and adjust their inventory and marketing strategy accordingly, leading to increased sales. You can visit our blog (AI for Business: The Thompson Sampling Case Study to Maximize Revenue) to see an example of the power of data and artificial intelligence to increase revenue.

Examples of businesses that have seen significant ROI from data analytics: Many businesses have seen significant ROI from data analytics. For example, Walmart uses data analytics to optimize its supply chain, which has resulted in savings and increased efficiency. According to a case study from the MIT Center for Digital Business, the use of data analytics at Walmart resulted in an increase of more than $1 billion per year in efficiency. Another example is Amazon, which uses data analytics to optimize its recommendations for customers, leading to a 35% increase in sales.

It is clear that the benefits of data analysis for businesses are numerous and can have a significant impact on financial results, on the retention of your staff, but above all on the satisfaction of your customers.

IV. And at Innovation Kapital K?

At Innovation Kapital K, we can help your business unlock the true value of your data with our comprehensive data analytics service offering. We combine our expertise in data analysis with our service ecosystem in innovation, strategy/business development and marketing to help your business make informed decisions, increase your efficiency, reduce costs, stay competitive, but above all to innovate.

Wondering how you can maximize the ROI of your data? We have the answer. Contact us now to learn more about how we can help you unlock the true value of your data and give your business a competitive advantage.

2020 Data and Analytics Market Study, Dresner Advisory Services

“Unlocking the value of data in retail” McKinsey & Company

“How Walmart is using big data to drive e-commerce and in-store sales” MIT Center for Digital Business