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What Is Data Maturity? Why Is It Essential for Businesses?

Data is important for businesses and this makes data conversion service a valuable consideration. Read about data maturity and its value for businesses.<br>

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What Is Data Maturity? Why Is It Essential for Businesses?

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  1. What Is Data What Is Data Maturity? Why Is Maturity? Why Is It Essential for It Essential for Businesses? Businesses? Data is important for businesses and this makes data conversion service a valuable consideration. Read about data maturity and its value for businesses. Managed Outsource Solutions 8596 E. 101st Street, Suite H Tulsa, OK 74133 www.managedoutsource.com (800) 670 2809

  2. Business leaders rely on different types of data to run their business, gather valuable insights, and make good business decisions. The importance data has in a business organization makes data conversion service a very valuable consideration. Data may be primary (interviews, surveys, focus groups, social media marketing) or secondary (government statistics, industry association, trade publications, company websites, market research reports). The data is collected and analyzed to study customer behavior and market trends. Tracking and reviewing data from business processes helps you pinpoint performance breakdowns, better understand each part of the process and know which steps need to be optimized, and which are performing well. This shows that data is becoming more and more powerful and data becomes an asset only when it is used well. This is where data maturity comes to play. Data maturity is the extent to which organizations utilize their data to get the most out of it. For example, in financial processes, the more advanced analytical techniques used to analyse data, the more data-mature the organization is. Data maturity is important for financial professionals who manage financial data, and have a real understanding of the power that data has to provide improved strategic advantage. The following are some of the advantages a higher data maturity and adoption of analytics offer financial professionals. Better predictions: For any financial organization, predicting future revenue, profits and cost is crucial. With predictive analytics, these predictions can be drawn accurately. Historical data gives an opportunity to anticipate what will happen in the future. Advanced analytics techniques give you the ability to set up various model scenario to see how potential decisions impact finance without committing to any course of action. Data maturity helps to make good decisions and also makes the employees aware of potential consequences of their actions. Good financial planning: Proper financial planning is essential for any business. Traditional business leaders relied on manual input of data, which could be time- consuming and inaccurate. Moreover, spreadsheets are highly prone to error, and this may hinder the processes of identifying useful insights and drawing meaningful conclusions. In data maturity, this process is streamlined and there is the opportunity to visualize your data in real time. It helps to track even a small financial change and automates your financial planning. Data analytics allows you to align your financial plan with many activities and widens your organization’s strategic goals. Minimize financial risk: Data maturity can minimize risk to a great extent. It helps you calculate financial risk at a granular level, optimize your resources and www.managedoutsource.com (800) 670 2809

  3. ensure that they are being used in the best manner. Analyzing data with the help of digital technologies can help highlight issues and address them effectively. Enhanced profitability: Optimum handling of an organization’s financial data is important to identify future growth opportunities. Research shows that organizations that use analytics to evaluate their data get excellent return on their investment. Analytics can also increase your organization’s profitability by giving you a better insight into investment opportunities, forecasting financial performance, and key financial drivers. Streamlined process: Data becomes effective when silos are removed and a more connected working system is introduced. Financial plans are synced with all areas of the business to eliminate silos. Putting all of your organization’s financial data in one centralized analytics system and establishing defined data standards allows you to become instrumental in promoting collaboration across your organisation. Low BI and Data Maturity and How to Improve According to Gartner, 87 percent of organizations have low BI (Business Intelligence) and low data maturity. This is a major obstruction for businesses that wish to increase the value of their data assets and exploit emerging analytics technologies such as machine learning. Organizations with poor maturity fall into “basic” or “opportunistic” levels on Gartner’s IT Score for Data and Analytics. Organizations at the basic level have BI capabilities that are largely spreadsheet-based analyses and personal data extracts. Poor business intelligence could constrain analytics that is used to modernize the business. The following are some steps to improve data maturity. • Create holistic data and analytics strategies with a clear vision: Data and analytics leaders should coordinate with IT and business leaders to develop a holistic BI strategy and view the strategy as a continuous and dynamic process. • Businesses should have people, skills and key structures and develop capabilities: It helps to anticipate the upcoming needs and ensure that the organization has the proper skills, talent and resources to support the work. • A formal data governance program is vital: Most organizations with low BI maturity do not have a formal data governance program in place. Governance is also a framework that describes the decision rights and authority models that must be imposed on data and analytics. • Poor BI and data maturity organizations have primitive IT infrastructure: To improve their analytics maturity, data and analytics leaders should consider integrated analytics platforms that can extend their current infrastructure to include modern analytics technologies. www.managedoutsource.com (800) 670 2809

  4. For implementing data analytics, businesses should first convert data into digital format. This can be efficiently done with the help of data conversion company. Once the data is digitized, it can be more easily and professionally analyzed and managed. www.managedoutsource.com (800) 670 2809

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