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Why Is Data Important In Data Decisions?

Table of Contents

When you actively transform your raw data and marketing metrics into actionable insights, you stay one step ahead of the competition at every turn. Not to mention, you gain a deeper understanding of your audiences and industry.

Today, it’s difficult not to hear about big data and data-driven decision-making. The term alone has recently become something of a buzzword in business, and for a good reason.

Data allows business owners to leverage the endless digital insights available at their fingertips and embrace the power of data-driven business intelligence to make more informed decisions that are better for business growth and evolution, plus increasing profits.

The approach helps the entrepreneurs mine data, saving time with useful insights.

A precise analytical objective helps solve some business problems, making it have powerful performance and predictive insights.

Data-based decision-making gives a place for the firms to gauge themselves, to test different strategies to see what is truly useful for their audience and customers.

Also, when the organization’s decisions are based on data and facts, it dramatically increases the speed of decision-making.

To help you on your quest toward analytical enlightenment, we’re going to explore data-driven decision making, study the importance of data-driven decisions, consider the benefits of developing a data-driven kulture, and examine some real-world examples of turning insight into business-boosting action.

What Is Data-Driven Decision-Making?

Data is important in the decision-making process, which is the new golden rule in the business world.

Businesses are always trying to find the balance of cutting costs while people can improve their efficiency and productivity.

Data-driven decision-making (DDDM) uses facts, metrics, and data to guide strategic business decisions that align with your goals, objectives, and initiatives.

Key performance indicators (KPIs) and measurable goals are key factors in data-driven decision-making for the business.

Facts and patterns gained from these insights are analyzed, and they are used to develop activities and strategies designed to be the most beneficial for the business.

Modern analytics tools such as interactive dashboards help people overcome biases and make the best managerial rulings aligned with business strategies.

When organizations realize the full value of their data, everyone—whether you’re a business analyst, sales manager, or human resource specialist—is empowered to make better decisions with data, every day.

Spending some time verifying the data and making sure that you are tracking the correct metrics for your decision-making process can help you think outside of your decision patterns and put the data to use to make the right choices for your business.

Making Customers Happy

Your decisions are ultimately designed to better target customers with more relevant experiences. You want to make the best choices for your customers, right?

In turn, happier customers improve your sales, increase brand loyalty and retention, lower your costs and guarantee your marketing success.

Knowledge of Technology

Becoming data-driven often involves an investment in technology. 

As we covered earlier, the most ground-breaking and valuable data initiatives are often automated, involve huge amounts of datasets (falling into the category we often refer to as “big data”), and advanced analytics capabilities like AI.

This is a big challenge and requires a strategic approach, ensuring that projects and initiatives are in line with overall business goals and priorities.

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Is Your Data Accurate?

Firstly, you have to ensure that your data is accurate and relevant to what you are looking to achieve with your goals.

While the data might show a particular pattern or suggest a certain outcome, if the data collection process or interpretation is flawed, then any decision based on the data would be inaccurate.

This is why the impact of every business decision should be regularly measured and monitored.

Making decisions based on inaccurate data can have huge implications on your business outcomes. 

Analyzing data that isn’t relevant to your goals adds to the jungle of inefficiencies that you and your organization could be facing.

Using data to drive your business decisions will automatically make them more accurate and successful.

With seemingly infinite strings or sets of data to work with, drilling down into the most relevant, valuable insights is the only way to gain clarity and make better decisions.

Once you’ve gathered your data from your most relevant sources, taking the time to mine for the most business-boosting insights will ensure you can squeeze every last drop of value from your analytical efforts.

However, a data-driven decision-making strategy should accompany various strategies and actions to get the most from the process and propel your business towards success using data.

When it comes to data-driven decision-making (DDDM), reducing bias and letting numbers speak for themselves make all the difference.

Avoid Gut Decision Making

Today, data driven-business decisions are more important than ever.

And while sometimes it’s best to go with your gut, most business decisions need to be based on facts, figures, and metrics that tie in with your goals and aims.

This provides something solid to back up your business operations and management aims.

As human beings, we often make split-second decisions based on feeling and intuition, without considering the outcome or consequence.

We can’t always help it, and we are emotional and empathetic creatures!

However, when it comes to making business decisions, it is crucial to take all external factors into account before taking any decisive action.

Rather than relying on guesswork, data-driven decision-making allows business professionals to leverage verified and analyzed data when working towards main business goals and objectives.

Instead of using opinions, gut feelings, intuitions, assumptions, etc., you rely on concrete evidence supplied by your data to guide your decisions.

Through data-driven decision-making (DDDM), you can ensure that cold, hard evidence guides your business needs and objectives.

Beyond this, data is logical and concrete in a way that gut instinct and intuition simply aren’t.

By removing the subjective elements from your business decisions, you can instill confidence in yourself and your company.

This confidence allows your organization to commit fully to a vision or strategy without being overly concerned that they made the wrong decision.

Data Gathering

Gathering the right data is crucial to the analytical process. Data collection should begin as early as possible for any business.

Regardless of how new your business is, starting to gather data as soon as possible helps you avoid a situation where you are relying too heavily on instinct and missing out on making the best decisions backed up by the numbers.

Backing Up Your Arguments

Data is a key component of systems advocacy. Utilizing data will help present a strong argument for systems change.

Whether you are advocating for increased funding from public or private sources, or making a case for regulation changes, illustrating your argument through data will allow you to demonstrate why changes are needed.

Finding New Opportunities

The data won’t speak to you; you’ll have to listen to it, and react accordingly.

If you follow this, we’re sure you’ll find many hidden business opportunities in the form of trends, getting you a step ahead of your competitors.

This is precisely why data-driven organizations capture a huge part of the market compared to conventional ones.

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Share Insights

Once you discover an insight, you need to take action or share it with others for collaboration. One way to do this is by sharing dashboards.

Highlighting key insights by using informative text and interactive visualizations can impact your audience’s decisions and help them make more-informed actions in their daily work.

Faster Decision Making Process

Once, collecting and analyzing data insights were all-encompassing and often led to decision-making delays; however, today, business intelligence software has made making data-driven decisions a much easier process.

Even users who do not have deep technical expertise can easily extract insights from data using these programs.

By using real-time data and past data patterns, the decision-making process becomes fast, and reliable as the organization can make confident decisions.

Finding Patterns

One of the most integral parts of any effective data-based decision-making process is discovering key trends and patterns.

Data analysis is, at its heart, an attempt to find a pattern within, or correlation between, different data points.

From these patterns and correlations, you can draw insights and conclusions.

Making decisions based on the belief that the future will be much better than the past. Managers need to recognize that we are biased in every situation.

There is no such thing as objectivity. The good news is that there are ways to overcome biased behavior.

As a result, these businesses identify business opportunities and predict future trends more accurately, generating more revenue and fostering greater growth through data decision-making.

Cost Savings

There are many reasons a business might choose to invest in a big data initiative and aim to become more data-driven in its processes.

According to a recent survey of Fortune 1,000 executives conducted by NewVantage Partners for the Harvard Business Review, these initiatives vary in their success rates.

One of the most impactful initiatives, according to the survey, is decreasing expenses.

Predicting Customer Behavior To Increase Sales

Marketing becomes much easier when you deeply understand your customers because you know exactly what they want.

Data analysis helps you tap into the products, topics, websites, apps, etc., customers prefer.

You can use this data to put your best foot forward every time you interact with a customer.

You can directly increase your sales and marketing success by analyzing and predicting these audience interests.

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Increasing Efficiency

Effective data collection and analysis will allow you to direct scarce resources where they are most needed.

Suppose an increase in significant incidents is noted in a particular service area. 

You can dissect this data further to determine whether the increase is widespread or isolated to a particular site.

What Is Objective Data?

Objective data helps most organizations to collect data, and use it for record-keeping and compliance. This makes the organization accountable for managing its data properly.

For transparency, data-driven decision-making ensures every piece of information is prioritized, the goals are concrete, and the overall results are measured accordingly.

Qualitative Data

Qualitative data analysis focuses on data that cannot be defined by simply looking at metrics, numbers, and statistics.

This type of data is gathered from conversations, interviews, anecdotes, and interviews.

Quantitative Data

Quantitative data analysis focuses on statistics and numbers, with standard deviation, median, and other descriptive statistics playing a huge role.

The median, standard deviation, and other descriptive stats play a pivotal role here.

This type of analysis is measured rather than observed, to help business owners and managers make more informed business decisions based on numbers.

You should analyze qualitative and quantitative data to make smarter data-driven business decisions.

Why Is Data Visualization Important?

Data-driven business decisions make or break companies. This is a testament to the importance of online data visualization in decision-making.

Since the digital landscape is ever-evolving and changing, businesses need to utilize data to make informed decisions that allow them to move and grow along with the changing environment.

Data-driven business decisions often have the power to either make or break a company, which is why data visualization is so important.

Data Tells You What You're Doing Right

Data allows you to replicate areas of strength across your organization. Data analysis will support you in identifying high-performing programs, service areas, and people.

Once you identify your high-performers, you can study them to develop strategies to assist programs, service areas, and low-performing people.

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Answering Questions

Once you have clear goals and a clear strategy in mind, you will find it easier to reach your business goals when you search out questions that have so far gone unanswered.

Asking the right questions during the data analysis process makes it easier for teams to focus on the most relevant data, which helps you speed the process up and avoid spending more than is necessary to get the results you need.

Improving Monitoring & Reporting

The ticketing industry is essential as it helps set expectations between parties to ensure a smooth business transaction in data management.

For many businesses, a ticketing software system also supports modules for monitoring and reporting, to be able to track all the activities and their productivity levels.

The real-time data acquired from the reports helps the managers to make informed decisions.

Using The Right Data Analysis Tools

When it comes to business analytics for data-driven decisions, working with the right tools is essential if you want to realize your goals and make consistently informed decisions.

By implementing the right reporting tools and understanding how to analyze and measure your data accurately, you will be able to make data-driven decisions that will drive your business forward.

Of course, this sounds incredible in theory.

But in practice, even if you have access to the world’s greatest data, it’s possible to make decisions that disregard tangible insight, going with your gut instead.

User Feedback

Depending on the type of questions that you need to find answers to, it is likely that you will need to take some time to study the data that you have gathered to extract analytical reports and meaningful insights to support your decision-making process.

User feedback can be a handy tool for businesses that need to carry out a more in-depth analysis before making key decisions that will impact the customer experience.

Often, it’s important to have the context to use data as effectively as possible when making any decision that will impact your business or customers.

Adaptability

One of the prime benefits of data-driven decision-making is making your business incredibly adaptable.

By embracing digital data, you stand to grow and evolve your empire over time, making your organization more adaptable.

Life Improvement

Data will help you improve the quality of life for the people you support: Improving quality is first and foremost among the reasons organizations should be using data.

By allowing you to measure and take action, an effective data system can enable your organization to improve the quality of people’s lives.

What Are Cognitive Biases?

Cognitive biases are tendencies to make decisions based on limited information, or on lessons from past experiences that may not be relevant to the current situation.

Cognitive bias occurs every day, in some way, in every decision we make. These biases can influence business leaders to ignore solid data and go with their assumptions.

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What Is Data Science?

The adaption of business intelligence software empowers users without deep-rooted technical expertise to analyze and extract insights from their data.

As a direct result, less IT support is required to produce reports, trends, visualizations, and insights that facilitate the data decision-making process.

Data science was born (or at least evolved in a huge way) – a discipline where hacking skills and statistics meet niche expertise.

This fairly new profession involves sifting large amounts of raw data to make intelligent data-driven business decisions.

What Are Psychographics?

In marketing, psychographics target a person’s interests and characteristics instead of just their behavior.

It is a market research technique that looks at the psychological motivations of a buyer.

Lufthansa Group

With over 500 subsidiary companies, the Lufthansa Group is the second-largest airline company in Europe in terms of passengers carried.

It brings in billions in revenue, but at one point, there was no uniformity in terms of data analytics across the many subsidiaries of this massive company.

However, after deciding to use one analytics platform company-wide, efficiency skyrocketed 30% across the company.

By creating a data culture, decision-makers across the company’s subsidiaries could make better-informed decisions after careful data collection and analysis.

Amazon

Amazon uses data to decide which products they should recommend to customers based on their prior purchases and patterns in search behavior.

Rather than blindly suggesting a product, Amazon uses data analytics and machine learning to drive its recommendation engine.

McKinsey estimated that, in 2017, 35% of Amazon’s consumer purchases could tie back to the company’s recommendation system.

JPMorgan Chase

JPMorgan Chase embraced a modern analytics solution to make decisions important to the bank’s health.

JPMC understands the customer’s journey by reviewing line-of-business relationships (i.e., products, marketing, and service touchpoints) with customer data.

For example, the marketing operations team performs analyses that influence design decisions for the website, promotional materials, and products like the Chase mobile application.

Starbucks

After hundreds of Starbucks locations were closed in 2008, then-CEO Howard Schultz promised that the company would take a more analytical approach to identify future store locations.

Starbucks now partners with a location-analytics company to pinpoint ideal store locations using data like demographics and traffic patterns.

The organization also considers input from its regional teams before making decisions.

Starbucks uses this data to determine the likelihood of success for a particular location before taking on a new investment.

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The Charles Schwab Corporation

The Charles Schwab Corporation is one of the largest publicly-traded financial services firms based on client assets.

Data is fundamental to enhancing the customer experience, driving operational leverage, and reducing risk.

With growing staff interest in data and analytics, they rethought their capacity planning and data support model, opting for an enterprise BI platform that supports analysts and novice, business users.

Continue Evolving Your Data-Driven Decisions

Data-driven decision-making has never been more important for companies that want to succeed.

This is often overlooked, but it’s essential nonetheless: you should never stop examining, analyzing, and questioning your data-driven decisions.

In our hyper-connected digital age, we have more access to data than ever before.

Hop-On The Kennected Train

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