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Data is like fuel, an important element without which running a successful business is next to impossible. Organizations use data to implement critical business decisions that are necessary for scaling the length of operations and maintaining a competitive edge. 

However, leveraging the data is a great idea only if it is accurate, precise, and trustworthy. Manipulated or ambiguous data is a gateway to making poorly informed decisions that are often irreversible and directly dent the operations and financial health of a business.

EXAMPLE: To understand the implications of inaccurate data, let’s consider an example where a supplier enters incorrect information with respect to the packaging dimension of a lot of medium-sized items. Instead of entering 105 inches as width, the wrong entry of 110 inches is made in the database. This leads to a series of events. First, the item will be classified into a new class. It will be now treated as a large-sized item and will need oversized flatbed trucks rather than normal flatbed trucks for transportation. Second, the paperwork related to transit will need to be changed based on the new class. The revised taxation and other duties will also follow. All of these will be multiplied based on the quantity of the items

While businesses make investments in Business Intelligence tools that generate a transformed view of data with multiple visualization options, it is also important to advocate the technology and organizational culture that fosters data accuracy at all different levels so that the data can be trusted and better decision making can prevail. 

In this blog post, we have uncovered four important reasons to make decisions based on trusted data driven by accuracy and precision. 

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#1 Better End Results

The decisions based on trusted data mean that they are based on accurate and high-quality information that leads to elevated confidence, improved efficiency, reduced costs, and most importantly- better end results. 

Data sharing and collaboration are one of the best practices to render the data trustworthy. 

Furthermore, having a standard process and rules can also help to strengthen the data’s accuracy and quality. For example, all the databases should follow the same date format. If one database has the data organized in MM/DD/YYYY format and the other database has the data organized in DD/MM/YYYY, then this can threaten the data accuracy. 

#2 Reduced Cost & Overheads

Trusted data is accurate data and using the same in the decision-making process saves an organization from heavy expenditures and overheads that would otherwise be incurred to fix and optimize the data which is of poor quality.  

According to research from Gartner, the average financial impact on organizations resulting from poor data quality is $9.7 million per year. In addition to the financial burden, the poor data quality also leads to a wastage of time as a lot of manual efforts are invested to fix the errors in datasets. 

#3 Compliance-Friendly Decisions

Following the regulations, guidelines, and privacy policies underlined in the legal framework is of utmost importance for any business to maintain a healthy relationship with its stakeholders. However, to ensure that the compliance requirements are duly met, it is important to implement decisions based on trustworthy and accurate data. 

The inaccurate data can land an organization into a pile of hefty fines, penalties, reputational damage, additional audits, and even a company shut down in some cases. Hence, decisions need to be compliance-friendly and trusted data plays a pivotal role in it. 

#4 Enhanced Productivity

Accurate and trustworthy data is directly associated with enhanced productivity. Trusted data does not need to come across the “data wrangling”, a process that forces the data scientists to invest too much manual effort in mapping out the useful data. 

The workforce can focus on more important tasks rather than killing time by fixing the errors in datasets. Hence, the importance of trustworthy data goes beyond the ideology of decision-making and helps in making the best use of human resources. 

Wrapping it Up

Without trustworthy data, there is no scope for business expansion and development. Trustworthy data is accurate and precise and provides an organization with benefits including but not limited to improved productivity, better decision making, rock solid credibility, smooth compliance, AI integration, and much more. 

To make the data trustworthy and credible, changing your CRM or requesting the IT team to come up with a solution is not the best way. The focus should be narrowed down to conducting a data quality audit, opting out for an automated solution, measuring the estimated impact, and measuring the workforce required to fix the broken data.   

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