How to Make Better Data-Driven Decisions - Top 10 Tips

DATA Analytics

May 2, 2022

There was a time people made decisions based on their gut feelings and instincts. While sometimes it led to a better opportunity, other times it resulted in an organizational crash landing. It is no more the same today as the era of technology has taken over everything. Additionally, setting your organization based on mere flukes does not sound logical. Hence, leveraging data assets and extracting exceptional insights from them (generally known as Data analytics) has become a crucial step in your path to success.


What is Data-driven Decision-making?

Decision-making is crucial, but when we choose data as its driving force, then it brings wonders. Data-driven decision-making means understanding the real value of your data and utilizing it to enhance your business functionalities. Moreover, adopting a data-driven culture comes with a lot of plus points. Apart from helping to increase business revenues, people at every position begin to incorporate critical thinking and data skills through Data-driven decision-making.


What is Data-driven Decision-making?

It is one valid question to ask while transitioning your workplace culture and thought process. With the humungous data production in our era, it is a big challenge to analyze it and extract actionable insights. Hence, it is not easy to transform into a data-driven business. Instead, it requires a lot of effort from the team and the business owners. Well, do not get freaked out, as we have the top tips and strategies for you which will help you:

  • Make better products

  • Acquire full work potential

  • Increase sales and revenues

  • And even more!

Top 10 tips to help you make better decisions


1.  Set your Goals / Objectives

The primary thing to do for adopting a data-driven mindset is to determine and set your goals and objectives straight. Diving headfirst into analysis without knowing about your business goals will prove futile, as, without clear and concise objectives, you will not know what you aim to achieve. You can go as specific about the objectives as you like. 


2.  High Data Accessibility

Among the other factors, the primary thing that keeps us from making quick decisions is inaccessible data. Most of our problems will get sorted out if we would enable data access to all relevant authorities and get it working. So, after brainstorming about your goals, the next step should be easier data access. Moreover, making it accessible to various team members will also cut down costs for you. 


3.  Collect Data Properly

Now, you have acquired access to all the data, so the next step will be to gather the relevant data. On the other hand, the relevancy parameters can get set according to your functional aspects. Moreover, to maintain relevancy, set priorities for your data assets, as it will intensify your impact.


4.  Clean Data Properly

In data analytics, one cannot start data organization and evaluation without first cleaning it. Hence you must ensure that you are working on clean data because data inaccuracy will impact your decision accuracy directly. Take this step critically and ensure 100% clean data to acquire authentic results. Everybody knows that there are tons of data available today, so narrowing it down is mandatory to get clarity into your decisions. 


5.  Structure Data

While you collect and clean your data for its relevancy and connectivity, you must also organize data into proper structures. Having messy data before running analysis and evaluation will lead to confusion and inaccuracy. 


6.  Conduct Data Analysis

Even though every other thing like data mining, cleaning, and prioritization is significant, analyzing your data still surpasses the rest. Once you fix your data assets for each scenario, you need to conduct a thorough and in-depth analysis to evaluate the possible outcomes. These conclusions, which get driven out of your precious data, are what will help you reach conclusive decisions.


7.  Seek Patterns & Trends

For any product or service to work, it is necessary to follow some trends. Your data analytics team must pick up on the trends after each analysis so you can make your decisions while keeping these trends in mind. For example, the pattern each customer follows for each product, (it comes under product analytics)can help you modify and customize your product accordingly. The result will generate increased revenues and better customer satisfaction. Cool, right?


8.  Visualize Data

Not everybody in your organization understands tons of numerical and factual data. The good part is that they do not even have to. Data visualization is an integral part of a data-driven culture, as having a clear image of your escalation graph will help you get clarity in your understanding and comprehension. Encourage better data grasping and meaningfulness among your team members by promoting visual data representation. 


9.  Re-evaluation is the Key

It is not right to perceive that one analysis is enough and then your data becomes useless to you. You must reevaluate and analyze your data from time to time, as it will be your key to accurate decisions.


10.  Tools

While keeping your goals in perspective, making better decisions is possible by utilizing the right tools. Any data analytics expert working in the domain is familiar with the popular tools and practices. Hence, make sure your data science team invests in the right tools fit for each scenario for the maximum data-centric approach. 


The aim to become a more data-driven and data-directed organization can be acquired by having a systematic approach towards it. For your business and organization to flourish at a higher rate making data-based decisions will get you there. Moreover, if you seek a data analytics team to do it all for you while you sit back and handle other things, then exploring Sudofy is mandatory!


Sundus Shiraz

Sundus is a Junior Software Engineer at Sudofy. As a tech enthusiast, she turns her findings into informative articles.