Skip to main content
Page Tittle
Data-driven Decision Making: Essential Five-step Guide For Any Business
Images
5-Step Guide To Data-Driven Decision Making

Introduction: Data is ruling our lives, from what we wear to how we travel, everything is influenced by data. This new era of data is redefining consumer behavior and business practices. Companies are using data to analyze user habits, predict sales trends, and develop new products and services. Today, data-driven organizations are outperforming their peers in terms of revenue, customer loyalty, and market share. They are more confident about their chosen strategies, as they use evidence-based data to decide.

Data is an asset

Over a period of time, data has proved itself as an asset. An asset that grows in value with use. Any business that is underutilizing its data is mismanaging its asset. It's missing out on growth opportunities and potential revenue streams. Data is a goldmine for businesses that, if properly utilized, can give them a competitive advantage and keep the company operations streamlined. A data-driven business is bound to outsmart its competitors, better serve its customers, improve operations, and increase profits.

However, despite data-driven approaches being highly effective, 68% of data teams struggle to extract insights from their data. For many organizations, data continues to sit on their dashboard and in silos, without little application. It is imperative for organizations to find ways to analyze the data and use the output to drive business decisions and achieve organizational goals.

Here is a five-step guide to unleash the power of your data and boost business decisions and growth:

  1. Define objectives and set priorities: First and foremost, clearly define your business objectives. Your data scrutinizing process requires direction, and goal setting and prioritizing are the key to it. You don't want to get caught up in analyzing data that may not align with your organizational goals. Looking for data without a business context is like looking for a needle in a haystack. To leverage most of the data, it is imperative to set objectives and establish KPIs and metrics.
  2. Identify Data Source(s): The next step is to sift through your data and identify the source that is reliable and complements the business goals. Identifying credible data sources can be a tedious process, but it's vital, as it is going to decide the quality of the data. A low-quality data source can have grave consequences. If poor-quality data is fed into the decision-making, then it could cause costly mistakes, including damage to the organization's reputation and loss of customers.
  3. Refine and analyze data: Data without context is just numbers. It is valuable only when we combine it for the right purpose. Once you have a pool of credible data, the next step is to put them into a data analytics platform and homogenize and categorize them to infer meaningful insights and locate discrepancies.
    When large quantities of data inundate your system, use Business Intelligence tools to cleanse and shape them. BI combines business analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations make better data-driven decisions.
  4. Draw conclusions: The goals are set, data is refined, and insights are derived. Now comes the time to apply the insights and draw conclusions. The goal is to frame the right questions and use insights to answer them. This stage validates or contradicts the original hypothesis formed based on research, experimentation, and business intuition. The conclusions drawn from the data set the tone of the business decision and help stakeholders understand the rationale behind it.
  5. Act: A data-driven decision is not final until it is implemented. After covering the distance from the data to the decision, the decision-maker must meticulously weave it into actionable policies. Present data visualizations, conclusions, and clear recommendations to stakeholders for their consideration. You must share your findings with the rest of the team so they can draw inspiration from it in the future. If possible, also draft reports and presentations as a handy reference.

Conclusion

Intuition has dominated decision-making for centuries. It is the most natural way of thinking where the gut feeling is brought to the forefront of the decision-making process. Several reports suggest more than half of Americans base their decisions on their gut instinct (even after contending with scientific pieces of evidence).

While the concept of intuition-based decision-making has been romanticized by many, it is not without its drawbacks. Intuition is a widely misunderstood concept. Your gut feeling also relies on the data available in your cognitive brain to form a conclusion. It's a rational recognition that comes from your ability to identify familiar elements in a new setup and react in a manner that is apt to it. The problem is that your cognitive brain can only process a limited amount of information and is prone to bias. It can become the source of faulty decisions and lead to the fallacy of data-driven decision-making. To overcome the limitations of intuitive decision-making, it's important to back up your conclusions with data. Following our five-step process for data-driven decision-making will help you avoid the pitfalls of intuitive decision-making and make an informed choice.

The value of your digital insights is immense. When an organization realizes the full value of its data, it empowers them with the ability to make informed decisions, maximize revenue, and provide better customer service. To succeed in today's business climate, it is imperative to incorporate data-driven decision-making as part of your organization's culture. At every step, you must make sure that your company is using data to inform and guide its decisions. Enable an environment where critical thinking and curiosity are encouraged and rewarded. Employees should work on their data-driven decision-making skills and hone business intuitions.

TED, an AI-powered value stream intelligence platform from Qentelli, helps you visualize metrics in your business and software value streams. It provides predictions and intelligent data correlation to drive engineering efficiencies and compliance adherence. If your business goal is "How do you monetize the data, you hold?" reach out to Qentelli at [email protected] and we will be glad to help.