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How to reach data maturity

by Team IA, June 24, 2021

Four stages of data maturity

Have you ever wondered with so much data around us, when is it that we can actually say that our organization has achieved data excellence? With all the data we are surrounded by, there is still a dearth of clean and accurate data. An organization’s data maturity can be measured by the extent to which it is using data or in other words the advancement of their data analysis. 95% of the data as we know it today was generated over the past five years. We all know how organizations used data in decision-making in the past year with the onset of the pandemic. They had to literally start afresh, get new customers on-board and even make some tough decisions including that of shutting operations altogether. All these decisions paved the way for more data-forward businesses. 

Data maturity can be measured in four stages:

Data Gathering or Explorer Stage: This is where businesses are in the initial stage vis-a-vis data. They are collecting data and do not have a particular data plan in place to integrate this data into their daily work.They may still be using it for some purposes such as for reports but data has not required a full-fledged and crucial role in their functioning. They may also be using only internal data in this stage and not using external sources. In other words they might be overlooking some vital information from worthy sources. Data collection can both be manual or automated depending on the resources of the business and the amount of data at hand.

User Stage: When businesses accept the importance of data quality in their journey they reach this stage of insight consumption. Decision-making is done by leveraging data here. Data use is standardized across the business and data sets are added to aid internal data sources when needed.

Leader: Just like the users, the leaders use data beyond just helping the business. They leverage data for competitive intelligence as well. This is where third party data is also used in addition to internal data. This is also the stage where data is woven in as an intrinsic thread of the culture of the business. The business uses data repeatedly as a natural part of its everyday functioning. For any business to be in this stage, it must invest in people (data team such as developers, analysts etc) and technology. This can lead to reaching the data maturity stage in a targeted manner using machine learning, predictive analysis etc along the way.

Innovator: When you start using data beyond mere observations and analysis, you reach the innovator stage. This is also a stage when you use data to gain a competitive edge and stay ahead in the curve. Innovators, then, can be defined as those businesses which repeatedly use data to adapt and change to face whatever the future holds. If you want help in measuring the data maturity of your business or want to set up a plan to reach this stage and need help or guidance, do reach out to us at contactus@infiniteanalytics.com

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