Why Data Driven Decision Making is Your Path To Business Success

We read about it everywhere. The term ‘big data’ alone has become something of a buzzword in recent times – and for good reason.

By leveraging the wealth of digital insights available at your fingertips and embracing the power of business intelligence, it’s possible to make more informed decisions that will lead to commercial growth, evolution, and an increased bottom line.

By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of 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. In most cases, this can prove detrimental to the business.

While sometimes it’s okay to follow your instincts, the vast majority of your business-based decisions should be backed by metrics, facts, or figures related to your aims, goals, or initiatives that can ensure a stable backbone to your management reports and business operations.

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

What Is Data Driven Decision Making?

Data driven decision making (DDDM) is a process that involves collecting data based on measurable goals or KPIs, analyzing patterns and facts from these insights, and utilizing them to develop strategies and activities that benefit the business in a number of areas.

Fundamentally, data driven decision making means working towards key business goals by leveraging verified, analyzed data rather than merely shooting in the dark.

However, to extract genuine value from your data, it must be accurate as well as relevant to your aims. Collecting, extracting, formatting, and analyzing insights for enhanced data driven decision making in business was once an all-encompassing task, which naturally delayed the entire data decision making process.

But today, the development and democratization of business intelligence software empowers users without deep-rooted technical expertise to analyze as well as 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.

From these developments, data science was born (or at least, it 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.

The ‘gold’ that data scientists ‘mine’ comes in two distinctive types: qualitative and quantitative, and both are critical to making a data driven decision.

Qualitative Data Analysis

It focuses on data that isn’t defined by numbers or metrics such as interviews, videos, and anecdotes. Qualitative data analysis is based on observation rather than measurement.

Here, it’s crucial to code the data to ensure that items are grouped together methodically as well as intelligently.

Quantitative Data Analysis 

It focuses on numbers and statistics. The median, standard deviation, and other descriptive stats play a pivotal role here.

This type of analysis is measured rather than observed.

Both qualitative and quantitative data should be analyzed to make smarter data driven business decisions.

Now that we’ve explored the meaning of decision making in business, it’s time to consider the reason why data driven decision making (DDDM) is important.

“Information is the oil of the 21st Century, and analytics is the combustion engine.” – Peter Sondergaard

Why Data Driven Decision Making Is Important?

The importance of data in decision lies in consistency and continual growth. It enables companies to create new business opportunities, generate more revenue, predict future trends, optimize current operational efforts, and produce actionable insights. That way, you stand to grow and evolve your empire over time, making your organization more adaptable as a result. The digital world is in a constant state of flux, and to move with the ever-changing landscape around you, you must leverage data to make more informed and powerful data driven business decisions.

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

In our study, we discovered that among the companies surveyed, the ones that were primarily data driven benefited from 4% higher productivity as well as 6% higher profits.

Companies that approach decision making collaboratively tend to treat information as a real asset more than companies with other, more ambiguous approaches.

Finally, here are 10 practical tips and takeaways for better data driven decision making in business. By the end, you’ll be 110% sold on the importance of making these kinds of decisions.

1) Guard against your biases

Much of the mental work we do is unconscious, which makes it difficult to verify the logic we use when we make a decision. We can even be guilty of seeing the data we wish was there instead of what’s really in front of us. This is one of the ways a good team can help. Running your decisions by a competent party who doesn’t share (or even know) your biases is an invaluable step.

Working with a team who knows the data you are working with opens the door to helpful and insightful feedback. Democratizing data empowers all people, regardless of their technical skills, to access it and help make informed decisions.

Often this is done through innovative dashboard software, visualizing once complicated tables and graphs in such ways that more people can initiate good data driven business decisions.

2) Define objectives

To get the most out of your data teams, companies should define their objectives before beginning their analysis. Set a strategy to avoid following the hype instead of the needs of your business and define clear Key Performance Indicators (KPIs).

Although there are various KPI examples you could choose from, don’t overdo it and concentrate on the most important ones within your industry.

3) Gather data now

Gathering the right data is as crucial as asking the right questions. For smaller businesses or start-ups, data collection should begin on day one. Jack Dorsey, co-creator and founder of Twitter, shared this learning with Stanford. “For the first two years of Twitter’s life, we were flying blind…

We’re basing everything on intuition instead of having a good balance between intuition and data… so the first thing I wrote for Square is an admin dashboard. We have a very strong discipline to log everything and measure everything”. That being said, and done, implementing a business dashboard culture in your company is a key component to manage properly the tidal waves of data you will collect.

4) Find the unresolved questions

Once your strategy and goals are set, you will then need to find the questions in need of an answer, so that you reach these goals. Asking the right data analysis questions helps teams focus on the right data, saving time and money.

5) Find the data needed to solve these questions

Among the data you have gathered, try to focus on your ideal data, that will help you answer the unresolved questions defined at the previous stage. Once it is identified, check if you already have this data collected internally, or if you need to set up a way to collect it or acquire it externally.

6) Analyze and understand

That may seem obvious, but we have to mention it: after setting the frame of all the questions to answer and the data collection, you then need to read through it to extract meaningful insights and analytical reports that will lead you to make data driven business decisions.

7) Don’t be afraid to revisit and reevaluate

Our brains leap to conclusions and are reluctant to consider alternatives; we are particularly bad at revisiting our first assessments.

Verifying data and ensuring you are tracking the right metrics can help you step out of your decision patterns.

8) Present the data in a meaningful way

Digging and gleaning insights is nice, but managing to tell your discoveries and convey your message is better. You have to make sure that your acumen doesn’t remain untapped and dusty, and that it will be used for future decision making. With the help of a great data visualization software, you don’t need to be an IT crack to build and customize a powerful online dashboard that will tell your data story and assist you, your team, and your management to make the right data driven business decisions. 

9) Set measurable goals for decision making

After you have your question, your data, your insights, then comes the hard part: decision making. You need to apply the findings you got to the business decisions, but also ensure that your decisions are aligned with the company’s mission and vision, even if the data are contradictory. Set measurable goals to be sure that you are on the right track… and turn data into action!

10) Continue to evolve your data driven business decisions

This is often overlooked, but it’s incredibly important 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. To extract real value from this wealth of insights, it’s vital to continually refresh and evolve your business goals based on the landscape moving around you.

Do you want a career in data analytics?

Enroll for our Data Analytics Training Courses such as

• Microsoft Excel Data Analytics
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• Microsoft SQL Data Analytics

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