How Can “Data-Driven” Become More than a Buzzword in the Workplace?

How Can

Many companies now characterize themselves as “data-driven,” and it’s easy to understand why: they are producing more data than ever before, and they have access to it. It is regarded as a competitive advantage, and many customers expect it.

Artificial intelligence (AI) and machine learning (ML) are becoming more widely available to aid in the interpretation of this vast amount of data and the improvement of business processes and functions such as customer experience (CX).

But, exactly, what does it mean to be a data-driven company? Because it’s being used to describe even the most basic data activities, the term “data-driven” has become marketing jargon to some extent. However, just because a company collects data does not imply that it is data-driven.

The bottom line-being a data-driven corporation entails intelligent analysis of the data at hand and making smart business decisions based on the insights.

Here are some of the initial steps to successfully leveraging data, extracting insights, and, as a result, maximizing ROI, in order to get to a situation where enterprises can proudly call themselves data-driven.

Also Read: 3 Truths About Hybrid Work that CIOs Can’t Ignore

From data-creation to data-driven decision-making

Businesses are dealing with an increasing volume of unstructured data as the world becomes more connected and digitized. Organizations attempting to improve business processes and innovations will need to be able to efficiently manage and analyze them.

To successfully leverage unstructured data, the first and most important step is to organize it, which can be difficult. With data stored in a number of repositories and formats, it’s critical to first understand what the data is and how useful it is to the business.

As the understanding of data grows, businesses will need to create a data map and a lexicon of what goes where. Data organization can be a time-consuming process, but by starting with the most important data and moving down, the business can swiftly acquire well-defined and trusted data.

Companies should move that data from the “swamp” of messy data to a clean data lake where it can be saved and stored – a trusted location where the data is ready and available for analysis after it is clean and defined.

Experimenting with the data is a great option as well as using it in existing processes, and conducting analysis to make new business decisions, as soon as it is formatted. However, businesses should avoid swinging for the fences right away. Understanding the linkages in clean, organized data takes time, and it’s better to prevent excessive expenditures and cycles by taking too many risks in the beginning.

This is where AI and Machine Learning come into play. Data that is well defined and understood can be utilized to train various algorithms and expedite or automate processes and innovations.

It’s critical to keep in mind the inescapable newly discovered data gaps as the business extends its data-driven initiatives. As organizations define and organize data, they frequently discover that outdated systems are rejecting relevant or highly beneficial data.

Also Read: Data Professionals Are Overwhelmed With the Rising Need for Data Products

Customer experience can be improved by utilizing data

The most useful information comes from sources that are now dark or chaotic. In customer engagements, this is one of the most compelling instances. This is valuable information that many businesses ignore because they don’t know how to obtain or arrange it. Interactions are recorded, filed away on a dusty shelf in cold storage, and eventually erased.

What good does it do to businesses to know what their customers are saying? What are their thoughts on products and services? Why did they choose a particular product or service?

Many organizations believe they have most of the data they need to boost customer loyalty and brand affinity when it comes to customer experience, but this strangely does not include the actual voice of the customer. The key to uncovering these answers is to listen to and truly understand what customers are saying across all channels. Customer conversations have an impact on more than just customer service. It has the ability to inform and transform businesses at all levels.

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Umme Sutarwala is a Global News Correspondent with OnDot Media. She is a media graduate with 2+ years of experience in content creation and management. Previously, she has worked with MNCs in the E-commerce and Finance domain