What is Data-driven Decision Making

by Ramesh Panuganty, Founder & CEO

What is Data-driven Decision Making

by Ramesh Panuganty, Founder & CEO

“If we have data, let’s look at data. If all we have are opinions, let’s go with mine.”

This famous quote by former CEO of Netscape Jim Barksdale clearly highlights the difference between decisions based on data and those based on opinions. Without any facts or numbers to back decisions, we are only left with our opinions, experience, or personal bias to interpret situations, arrive at decisions, and implement actions.

What is data-driven decision making?

Decisions such as what to wear to work today, or where and what to have lunch are simple, low impact, and most of the time based on factors such as personal likes, past experiences, and opinions, either ours or others. However, decisions such as where to invest profits, which channel to select for maximum reach, when to launch a new product, or which new region to venture into require a thorough study of the situation, a detailed examination of facts and numbers, comparison of current and past events, and correlation with influencing factors.

When a decision is arrived at after taking into account all available data that is analyzed from all possible perspectives, then we can say it is truly a data-driven decision. Data-driven decision making is the process of using data and insights to enhance the quality and improve the accuracy of decisions, instead of relying on guesswork, intuition, or hearsay. Using this process, decisions are made based on supporting data and facts, thus ensuring better outcomes and minimizing the chances of failure.

Why is data-driven decision making important for business?

While making high-impact decisions, business decision-makers need to interpret market situations correctly, identify all available solutions or options, evaluate each of them carefully, and take calculated risks to implement their decision. In high-pressure make-or-break situations, where the stakes are high and extensive manual analysis is not feasible, a data-driven decision-making approach helps decision-makers make fast, confident, and accurate decisions.

The benefits of data-driven decision-making include improved visibility and access to data, increased agility and productivity, better protection from risks, an empowered workforce, and cost savings in terms of better resource allocation and operational efficiency.

6 key steps for effective data-driven decision-making process

1. Identify decisions that require data-driven insights

Business decisions can be routine or unconventional, low impact or high impact, and regular or critical. Identify the decision-making processes that are complex, time-consuming, recurrent, and need the latest data. Consider adopting data-driven decision making for such processes to expedite actions, minimize risk, and reduce delays.

2. Uncover data sources for every business function

Different departments use different stacks for collecting and storing data. Decisions made based on incomplete and outdated data can lead to incorrect actions and disastrous outcomes. Perform a thorough inventory of all the structured data sources. This provides clear visibility of available data and uncovers silos for consolidating all data.

3. Ensure availability of high-quality data

Once you have consolidated all the data, the next important step is to measure its quality. Check the data for any missing or incomplete values, inconsistencies, and errors. If the data itself is incorrect, has duplicate or missing values, and is not consistent in nature, it loses its credibility to provide accurate insights. Decision makersneed reliable and relevant data to make accurate business decisions. So verifying the quality of data is a must to get accurate insights.

4. Democratize access to data

Don’t restrict data-driven decision-making abilities only to high-level executives. Consider enabling it for the larger frontline workforce too such as account associates, sales representatives, marketing teams, customer success teams, or retail store managers. This ensures better decisions and actions at all levels within an organization. Put in place clear data governance policies to ensure that the teams get access to relevant data based on their roles, work, or geography. This helps bring transparency and accountability while democratizing data and insights for everyone in the organization.

5. Remove barriers to adopting analytics

Data analytics tools, especially the traditional ones, can be complex and intimidating. They require users to use syntax and SQL for querying, leading to a steep learning curve, especially for non-technical business users. Analytics feels like an overhead task and business users shy from using it for their daily decisions. Modern analytics platforms remove these technical barriers by offering natural language search, conversational user interfaces, and decision intelligence, thus making users self-reliant in adopting analytics.

6. Choose a modern data analytics platform that offers decision intelligence

When evaluating a modern data analytics platform, look for abilities such as easy data integrations, self-service analytics, customizable machine learning models, configurable AI algorithms, and natural language processing. Additionally, a simple and intuitive user interface that enables business users to interact with data naturally ensures that they can do their own analysis without learning new skills or depending on analysts.

Make smarter decisions with MachEye’s self-service analytics platform

What today’s business users need is a modern analytics platform that encourages data-driven decision making. MachEye’s decision intelligence software offers an intuitive search interface and personalized insights to help every decision-maker across organizations make fast and confident decisions. With its intelligent search, actionable insights, and interactive audio-visuals, MachEye makes the insight discovery process not only faster but also engaging and interactive. It acts as a trusted personal business companion who finds performs root cause analysis, identifies key drivers, and explains the what-why-how of business events in just a single search. With actionable recommendations and upfront business headlines, MachEye provides support in every step of decision-making.