Being Data Driven: A Comprehensive Guide

In the modern industry today, data plays a vital role in every company. Most companies, especially large enterprises, are investing heavily in the collection, storage, and analysis of data. In other words, these companies have a”Data Driven” approach.

Companies that have become Data Driven have understood the importance of data in any type of business. It is because of this that companies have decided to use data in the most useful ways to gather valuable insights. Research has shown that companies that are more Data Driven are able to retain their customers 6 times better than companies that are not Data Driven. This has also had a direct impact on the profits of the companies and has shown that profits are directly proportional to being Data Driven.

This article talks about the importance of being Data-Driven and also addresses the prerequisites that companies need to have before adopting the approach. It also explains the cycle to become Data-Driven.

Table of Contents

• What is Data-Driven Approach?
• Benefits of Being Data-Driven
• 9 Key Prerequisites for the Data Driven Approach
  • Collectibility
  • Sharing Capabilities
  • Queryable
  • Presentable
  • Inquisitive and Investigative
  • Discernable
  • Future Ready & Far-Sighted
  • Choosing the Appropriate Simulation Techniques & Models
  • Self Correcting & Incorporating an Adaptable Approach
• Understanding the Cycle to Become More Data Driven
• Conclusion

What is Data-Driven Approach?

When a company is Data Driven, it simply means that the company takes decisions based on facts and figures, and not on emotions. This way the company makes strategic decisions based on data analysis and interpretation. Data is considered an asset and is actively collected, curated, and properly stored to be used later.

A Data-Driven approach enables companies to examine and organize their data with the goal of better serving their customers, vendors, and employees. By using data to drive its actions, an organization can contextualize and/or personalize its messaging to its prospects for a more customer-centric approach. 

The Data Driven mindset will collect the right data, process it intelligently to gather insights that lead to decisive action. Being Data driven is a culture that knows the significance of trustworthy data, identifies the right tools to process it, and nurtures the ability to act on it. 

The diagram below depicts the basic idea every Data Driven company/organization follows:

In order to understand the applications of the Data-Driven Approach in detail, click this link.

Benefits of Being Data-Driven

Uncertaintinities are part of life, and being a little certain gives you an edge over others because it helps you make better decisions. Being data-driven allows you to get more certainty over some topics because Analytics tools consume large chunks of data to generate insights based on Mathematical calculations, historical data, analyzing past events, and much more. Being data-driven has many benefits as it provides insights on Customer behavior, Marketing performance, competitive landscape, etc.

9 Key Prerequisites for the Data Driven Approach

The important prerequisites to incorporate the Data Driven Approach that companies must acquire are given below:

• Collectibility
• Sharing Capabilities
• Queryable
• Presentable
• Inquisitive & Investigative
• Discernable
• Future Ready & Far-Sighted
• Choosing the Appropriate Simulation Techniques & Models
• Self Correcting & Incorporating an Adaptable Approach

1) Collectibility

Collectibility is the process of recording the transactions around your business and translating them into numbers. It’s the ability to assign numbers to any event in the business, capturing the details at the required granularity and storing them in an appropriate format. 

2) Sharing Capabilities

All the employees and departments must be willing to share their data with co-workers and provide inputs on how to better use their data. When data is considered an organizational asset and not a departmental property, and there are firm policies in shape for sharing and updating it, then an organization achieves, what we call, Data Democratisation.

3) Queryable

Queryable is a property of the data that ensures that it can undergo any transformation. Such transformations include aggregation, filtering, grouping, searching and verification.

4) Presentable

Unless the facts are presented in an easily comprehensible manner, the decision-makers will have a hard time understanding them to formulate strategies for growth. The correct tools must be used to represent facts and graphs and correlated metrics must be shown together. Wherever possible, people must be able to zoom in to get all the details.

For example, ratios are best represented in the form of Pie Charts or Spider Charts, whereas any number series is represented in the form of Bar Graphs or Histograms.

The images below show the representations of ratios and number series in the Pie Chart and Bar Graph form.

5) Inquisitive & Investigative

It is important to note that the employees that will consume the final reports must be competent enough to ask the right questions, look for the appropriate insights and investigate the correct leads. The people who query the data must have the right skills to formulate queries, extract the right metrics and present them in an easily understandable manner. 

There must be a process to identify, list, and track the right metrics, and update this list from time to time.

6) Discernable

Discernibility is the property of data that helps employees differentiate the data from trends and spikes.

For example, let us consider a hypothetical case of a flower-selling E-Commerce website. The data tells you that there has been a rise in sales in the last week. This may be due to some particular event coming up, e.g. Mother’s Day or Valentine’s Day. It could be attributed to a temporary non-availability of some other product which has resulted in buyers being diverted to your offering.

Hence, all facts and numbers must be understood in the right context. You must develop the ability to discern why something happened, what is good or bad in it, and how to better it and/or make the best use of it. 

7) Future Ready & Far-Sighted

This is the property of data to ensure that data can be used for prediction. All the facts are based on the past but, a Data Driven Organisation would also be prudent enough to try and predict what could happen in the future, and be prepared for it. 

The data should be able to give testable predictions and help in formulating pre-emptive strategies and judicious plans.

8) Choosing the Appropriate Simulation Techniques & Models

The data models chosen must lead to facts and actionable insights from the data being analyzed. It must also be able to experiment and simulate results; such that different plans of action can be hypothesized, virtually driven and their likely results are known. This leads to choosing the most optimal solution even in the most difficult circumstances and functional environment.

9) Self Correcting & Incorporating an Adaptable Approach

Once an approach is taken up or a mode of action implemented, one must gather more data as the plan of the action unfolds. This is important because channels back the feedback and errors in the data models and try to improve them.

The outcome of a strategy will help you in bettering your future models and courses of action. A Data Driven Organisation may be continuously testing sometimes in parallel or multiple times in a day. Overall, to manage a Data Driven Organisation, you must have a mindset to rely on facts, processes to find the right data and act upon it, trust your insights and be ready to accept mistakes, and commit to continuous improvement. 

Once the above prerequisites are taken care of, the company is ready for incorporating a Data-Driven approach in its activities.

The evolution of a company to become Data Driven is shown in the figure below:

Understanding the Cycle to Become More Data Driven

The Data-Driven Approach has 3 steps:

• Tech-Savvy (Data Creation and Integration): The first step into the Data-Driven Approach ensures that the organization must be able to create and collect all relevant digital data, and then integrate and structure the data into information.
• Data Fluency (Business Intelligence and Analytics): The second step involves getting the company to extract insights and intelligence from data and information.
• Data Literacy (Decision Management): The final step ensures that the organization must be able to make decisions and take actions based on insights and intelligence extracted from data. 

The above 3 steps of the cycle can be summarised through the figure given below:

To learn more about how to make data-based decisions, click this link.

Conclusion

This article gave a comprehensive guide on the importance of becoming Data Driven. It also explained that a Data Driven Organisation must be committed to continuous improvement; inclined to learn, unlearn and relearn; and take pride in their approach. It also gave companies a look at the prerequisites and cycle to help them take their first steps into a Data-Driven Approach. Overall, incorporating a Data-Driven Approach is critical to any company no matter the service it provides because it ensures that the company is able to meet the customer goals and also gather valuable insights from them.

If you are planning to make your organization Data Driven, then Hevo Data is the right choice for you! It will help simplify the ETL process and management process of both the data sources and the data destinations.

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