In competitive business dynamics, informed decision-making appears as the fundamental axis that drives the success of any organization. While 50% of companies worldwide are already data driven, only 43% are monetizing their data and insights with products and services.
By making data-driven decisions, these organizations realize benefits such as*:
Knowing these percentages, an obligatory question arises: is your company already making its data profitable?
The absence of a robust data analytics strategy can place businesses in an uncomfortable maze of uncertainty and wrong decisions. From oversized purchases to unfinished projects, the repercussions of operating without a clear vision backed by a data-driven model can be costly.
First Things First: Avoiding the Wrong Route
All current, past, and future decisions in an organization are based on data that is naturally obtained from experience, systems, documents, and even external sources such as news, articles, or colleagues. However, making decisions in this way becomes imprecise, causing:
The Power of Data Driven
Data is currently the most powerful tool in business and, in that sense, the most valuable thing in the entire organization. Precisely to exploit the gold mine represented by the data, it is important to know that they are concentrated in:
Data Analysis: 360 Strategy
Data analytics refers to the process of understanding, analyzing, cleaning, cross-referencing the right information to know, improve and make sound decisions in all areas of business. Any business activity generates data and, therefore, any tool is a source of information. This is how data analytics helps define the business responses that are of interest to your organization, that is, its objectives in a business intelligence context.
More than a technological tool, we are talking about a complete transformation of the business. A different way of operating that will have an impressively favorable impact on the organization, so first of all you must define what you want to know about your business. Ask yourself what decisions you’d like to make and how they would impact the business.
The objectives will be SMART:
The use cases in which data analysis will be applied must also be defined, which can be business, technology or organizational. To do this, all areas (such as purchasing, finance, marketing, sales, manufacturing) must be involved to know what is currently being done and why not go back to evaluate how the results of the decisions that have been made without data analysis have been and what it would be like if we obtained accurate answers about customers, purchasing, production, etc. improvements, etc.
Towards Data Driven: Knowing the Sources of Information
The inventory must be known without discrimination of all the places that yield or safeguard data, all sources are important because answers can be obtained from all of them. For this reason, the exceptional thing about analytics is not the data itself, it is what you do with it.
In addition, it is necessary to know what information is in each of the places, how often it changes, how sensitive the information is, what it is used for, how the sources relate to each other and who manipulates that information.
Understanding Current Data Governance as Part of Business Intelligence
In relation to the previous point, where we asked who manipulates the information, this provides visibility about how reliable it is. It is also necessary to know who has access to it, what they use it for and how they manipulate it, since the quality of the reports that are currently issued depends to a large extent on this.
The less information is touched by a human, the better, since in order to do a data analysis we must have controls, policies and guidelines that protect the integrity of the information.
There is no point in extracting, transforming and loading processes, if the information can be changed or touched by a human without prior control or notification.
This is possibly where many companies stop, because current and future data governance can generate millions in losses if neglected. And this negative impact on the business will be reflected not only in data analysis, but also in information security.
Therefore, the root of data analysis is defined based on technological tools that control and preserve the integrity of the data, as well as the personnel who can define and monitor these policies or principles.
Data Analytics to Drive Business Intelligence
As a last point and to promote the approval of a data analysis project, the entire organization must define its analytical advantage. By understanding a unique benefit in this project, you will make it executable as it is not only about getting answers or KPIs, but about boosting your company with the advantage that can only be achieved through data analysis.
See You in the Cloud!
On the journey to a data-driven enterprise, the key lies in understanding that data is the driving force behind every action, every goal achieved, and every competitive advantage. Data analytics isn’t simply a technological tool; It’s a complete transformation that redefines the way organizations operate and thrive in a business intelligence environment.
At Itera, through a comprehensive approach to cloud data analytics solutions, we not only address the inherent problem of the lack of accurate data, but also unlock unprecedented potential.
From identifying sources of information to establishing robust data governance, our specialists guide organizations to the pinnacle of business intelligence, delivering an analytical advantage that not only improves decision-making, but also translates into tangible economic results.
We invite organizations to discover the transformative power of data analytics and define a future where data-driven is the compass that leads to the sustainable success that business intelligence represents.
Contact us for more information!
*Source: https://www.capgemini.com/wp-content/uploads/2020/11/Data-powered-enterprise-report.pdf
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