In the last few years, more and more companies have started paying attention to data quality management. You might have heard the new proverb- ‘data is the new oil’! There is a belief that data quality management is something that has taken place in recent decades. Especially after the advent of all these SaaS-based companies.
However, man has been using and consuming data from time immemorial. Sales and Marketing executives have been using a rudimentary form of data management for a very long time. The biggest change that has happened in recent years involves the systematic and strategic study of data to achieve certain ends.
In this article, we will briefly look at what do we mean by Data Quality Management. We will also look at the top three things that brands, agencies, and individuals must note about it.
Data Quality Management: Meaning and Definition
Data Quality Management refers to the collection, management, and execution of data-based learnings to improve performance. This performance can range from helping Marketing and Sales to drive exposure and revenues as well as using it to help the Relationship Management team and forge long-term relationships with clients.
Over the years, the major companies have concerned themselves with three major elements of Data Analysis-
- Acquisition of Data
- Implementation of Data
- Distribution of Data
For every company that wants to succeed in 2019 and the future, data analysis needs to become an integral part of its company ecosystem. Effective Data Analysis not only helps chart future courses of commercial activity, but it also helps to shed light on past performances and efforts. Briefly, it is an effective mechanism to grow not only economically but also saves wasteful expenditure in several ways.
3 Things to Know about Data Quality Management:
1. Data Analysis can be used multilaterally across different teams:
The best thing about data is that is never unilateral. In other words, data always has a multidimensional approach to it. A brand or company needs to use data across different verticals and teams. For example, the same framework data collection and formulation can help the Sales, Marketing, CRM, and HR teams.
2. Data Analysis should be used to analyze the Past as well:
Brands think of data management as something that can help them when it comes to future planning and execution. However, data analysis can also help understand the past of a company’s performance sheet. You can use it to study how various campaigns could have been optimized and how wasteful expenditure could have been saved.
3. Data Quality Management is governed by Local and International Laws:
The power of data has meant that it can be used for both productive as well as counter-productive mechanisms. This is why there are stringent laws and regulations in place which direct companies how they should use data and which boundaries they cannot overstep. This has been done to protect the interests of the consumers.
There is a misconception that only the big companies can utilize data quality management in its full glory. However, that is not the case. A small company can learn more from Facebook Data and Reporting than a big company can from employing SaaS agencies. Again, it is all about understanding which data is relevant to your brand. It is also, about how you would want to leverage the same.
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