Benefits of Data-Driven Development
Do you think twice about why you should use a data-driven approach in your organization? According to 90% of business professionals, data and analytics are essential to the organization's digital transformation. However, most companies still need to be convinced to embrace the data-driven approach.
Big data has become common, and it is all for a good reason. Businesses that use big data have an 8% increase in their profits.
Leveraging digital insights allows you to embrace business intelligence and make informed decisions that lead to evolution and commercial growth. Data-driven organizations see a 3x improvement in decision-making.
Nowadays, businesses have to deal with a lot of data daily—clients, employees, accounting, finance, etc. Even though some companies use smart technologies to manage the data, others have difficulty leveraging data to decide for their businesses.
As much as data-driven decision-making is crucial, approximately 5% of organizations need it to make decisions. Most organizations trust their instincts in making decisions based on past experiences. That is a very wrong approach to decision-making.
In a world where more than half of the people rely on their gut to make decisions, you'll be ahead of your competition when you make data-driven decisions. A survey by the PWC shows that highly data-driven organizations are three times more likely to have significant improvements in decision-making compared to those with fewer data.
Making all your decisions based on intuition can be a huge mistake. Modern development teams utilize data, which is a powerful tool. Data allows you to quantify, verify, and understand the information before you make your final decision. Data helps visualize the output quantity and quality.
Data-driven business development is a critical paradigm in software development. It is a programming approach that describes what data needs to meet a given set of requirements. This article will explore the benefits of data-driven development in modern apps.
What Are Data-Driven Applications?
Data applications present themselves in many different ways, but in their simplest form, data-driven applications are created to store, display, and manage data. The end-user uses this application to access the data within.
In a data-driven system, the data itself defines how the application operates. From personalized portals to wearable devices, data-driven apps surround us.
What Is Data-Driven Development?
There are thousands of apps being launched online daily, and some may be successful, having millions of downloads; others are usually forgotten. The functionality, user interface, and attractive layout are some factors that determine if the app gets downloads or not.
Modern app development is a hit or miss; you must return to the drawing board to make changes. However, understanding why you are developing the app and your target marketing increases your chances of success. With the right reporting tools, you can measure data accurately and make decisions to move your business forward.
When developing software, you use the data-driven development framework. It involves using metrics to help in the development process. Through the metrics, developers will gain a deep understanding of their products and understand their organization's goals. With a database-driven web application, you'll notice an improvement in profitability. Even though it involves data collection, developers must use actionable metrics. It is, therefore, vital to focus on a data-driven business development process.
Data-driven app development refers to building apps and harnessing data, which increases your chances of success. With data-driven app development, you can see the facts without scrutinizing whether it works. Here are some of its benefits, including smart data collection, since data-driven engineering allows you to collect data faster. You can set up data points to help you find solutions to questions you may have as innovation progresses.
What Is a Data-Driven Approach?
Before you begin making data-driven decision making, what does data-driven mean? Data-driven decision-making (DDDM) means you make decisions after fact-checking with data. You'll need a combination of systems and strategy to succeed with data-driven decision-making. Your main goal should be to make intentional, informed, and effective decisions.
You can conduct the data collection in different ways depending on your organization. You'll have to collect feedback to determine what is working and what is not. DDDM could be:
Conduct user testing that helps your organization observe how customers use your products or services and identify any issues you must resolve before making an entire release.
Collect survey responses to identify the services, products, and features your customers will like.
Launching a new product in the test market to understand how a product performs in the market.
Analyze the demographic data shifts to determine opportunities and threats.
Data-driven decision-making means companies collect and store relevant data and analyze it to make decisions.
The planning and strategy in your business should be made based on actual numbers, and you have to do that by analyzing data. Your company will require additional digital tools to collect and analyze the data. The tools you need vary depending on your business.
Benefits of Data-Driven Decision-Making
Data-driven development decision-making helps transform organizations and provides tremendous benefits. Through the modern approach, you can use digital tools to analyze data. Here is what you stand to benefit from when you make data-driven decision-making.
Make Confident Decisions
When you start analyzing data, you'll become confident to make decisions regardless of any challenge you face in your business. Data allows you to understand better how the decision will impact your business. With this newfound confidence, you'll commit to your organization's vision without worrying about making the wrong decision. However, remember that even if the decision is data-based, it may only sometimes be correct. The data will show you a pattern, but you'll make a wrong decision if the data collection process is flawed.
Informed decisions can help grow your business, but you must rely on more than just the data to make the decisions. You need a combination of observations, experience, and data-driven applications to get incredible results. When you consider analyzed data, you have a precise forecast and adjust your decisions accordingly.
Every business has its challenges, and finding the cause of the problem is a great way to resolve it. You should not only make data based on obvious facts but go through the numbers and analyze them.
With the data, you'll determine if you should cut costs, whether you need team members, or what your customers like. You can get all the answers to your questions through data analysis and a data-driven system.
Streamline Marketing Efforts
Data analysis helps improve marketing efforts. You can analyze data to make informed decisions about your marketing campaigns. Understanding customer preferences enable you to make the most of your marketing budget.
With DDDM, you'll identify the successful strategies and the ones that require you to adjust your approach. It helps to track the campaign's return on investment and how your effort impacts your business. If data-driven decision-making is used correctly, it will be a valuable tool to help your marketing team optimize the campaigns and improve overall performance.
Reduce Operational Costs
Business decisions go hand in hand with financial risks. One wrong move can see you lose profit and invest much more than expected. By using data-driven applications in decision-making, you'll avoid the risk and reduce the chances of budget loss.
With data, you'll find gaps in your operations that are cost-consuming. However, with financial performance, you can reach your operational efficiency and develop ways to streamline your development process.
Develop Better Strategies
Using data allows you to assess demand for the digital solution and invest in the best decisions. You can use analytical tools to forecast trends and predict changes in customer behavior.
Furthermore, many organizations are using AI-powered decision-making tools in marketing. When you analyze your competitor's products and services, you can assess their target market potential.
Process Optimization
If your business is growing, you have some room for improvement. You'll have to handle process optimization with time. However, you can only do process optimization with relevant data about performance and analyze data to see the changes needed in each department. DDDM improves the hiring process, risk management and customer service, and onboarding of new team members.
A data-driven decision-making approach provides valuable insights you can use to change your business strategy. You can set reasonable goals once you know the market trends, performance, and customer behavior patterns.
Examples of Data-Driven Decision-Making
Some of the largest and most successful organizations utilize data to make high-impact decisions. Here are examples of data-driven systems used in decision-making to help you know how to use data in your decision-making process.
Google - Leadership Development
Google is a notable example of data-driven decision-making — it focuses on people analytics. The project Oxygen is one of the initiatives that allowed Google to mine data from over 10,000 reviews. The organization utilized the data to determine high-performance manager behaviors and developed training programs to improve their competencies. It then made a data comparison with employee retention rates. The result was an increase in managers' median favorability from 83 percent to 88 percent.
Starbucks - Real Estate Decisions
In 2008, Starbucks' hundreds of locations were closed. This problem made the then CEO, Howard Schultz, take an analytical approach when deciding on future store locations. The organization has partnered with a location analytics firm to identify ideal areas using traffic patterns and demographics. It also used input from the regional teams to help make informed decisions. Starbucks then used the data to determine the success of a location before investing.
Amazon - Driving Sales
Amazon used to identify the products to recommend to their customers based on purchases and search behavior patterns. It does not suggest products blindly but uses machine learning and data analytics to make recommendations. Thirty-five percent of Amazon consumer purchases were a result of the recommendation system.
Walmart - Emergency Merchandise Preparation for Hurricane
During times of natural disasters, Americans went for beer and strawberry pop-tarts. Walmart executives explored the merchandise to stock before the storm. The analysts used records from previous purchases from other Walmart stores in similar conditions. Walmart analysts kept the beer and the pop tarts in stock but also created profits in anticipation of demand because most of the products were sold out quickly.
Southwest Airlines
A data-driven decision is crucial for all industries, but the airline industry is the one that benefits the most from it. Southwest airlines executives used customer data to understand the new services that would be more profitable and popular among customers.
Southwest airlines' driven decisions saw an increase in customer base and brand loyalty. It saw steady growth year after year. After analyzing online customer behavior, the airline found out that it could offer different customer segments with their best rates and an excellent customer experience.
Netflix
Netflix is the streaming service industry leader boosting 128 million active users. It didn't get there by making decisions based on intuition. Netflix used data to retain its customers. The streaming industry is becoming more competitive daily, and there is a need for organizations in this space to look for ways to enhance their user experience and increase customer retention.
Netflix uses different metrics related to their customers, such as location, watch time, types of shows, data, and when a user pauses or resumes content. Additionally, Netflix used the information to generate a recommendation to improve the viewer-watching experience. The organization implemented an algorithm, analyzed the results, and found that 80% of users followed the advice. Therefore, the strategy succeeded and helped Netflix retain customer rates.
Why Data-Driven?
Data-driven decision-making ensures that decisions are based on reasoning and logic and supported by numerical evidence. Without data, decision-makers risk being influenced by external stimuli and bias. Here are reasons you should be data-driven.
It is objective: DDDM relies on statistics, making it an objective process.
It is easy to evaluate: Data-driven decision-making can be quickly evaluated based on implementing some decisions.
Increases agility: Companies using DDDM are more agile. They can detect business opportunities and identify issues quickly.
Promotes accountability: Data-driven software development is based on numerical information and facilitates transparency and accountability in decision-making.
Why Is Data-Driven Decision Making Important?
In the fast-developing world, data-driven decision-making can make a big difference for companies to gain a competitive advantage. You need more than the data at your disposal; you must use it correctly to get the actual value. The following are the importance of using data-driven software in decision-making.
Continuous Business Growth
By analyzing your data and metrics, you can identify products in the organization and fix them on time. Once you have the key insights, you'll see how data-driven projects help your business grow.
New Business Opportunities
Data-driven projects give you a 360-degree view of your business and clarify your judgment. With a deep analysis of your market and competitors, you'll discover any unexpected opportunities that will lead to success.
Improved Customer Experience
Data-driven decision-making enables you to focus on the quality of products and services and give customers an incredible experience. When you collect data about your customers and their preferences, you can make informed decisions and improve your service.
Improve Communication in Departments
When the department in your organization functions properly, it becomes easier for employees to share insights. You'll have the opportunity to create a solid strategy and communicate effectively with real numbers and metrics.
Steps to Make Data-Driven Decisions
Now that you know what you benefit from using a data-driven decision-making approach, it's time to start using it. Here are the steps to implement data-driven programming in decision-making.
Define Your Business Goals
The first step in a DDDM approach is to analyze what you want to solve by defining your objective. What would you like to accomplish with your decision-making? Or has it increased customer retention rates? Whatever your goal, ensure it is focused, defined, and well-documented to lay the groundwork for success. You have to do this before you start the data collection process. You'll know the data to collect and what you should not collect. Defining your objectives ensures you have something to measure your success. Make sure everyone is on the same page for this step to work.
Establish a Hypothesis
Formulating the hypothesis is the next step to creating a data-driven program. It is vital to develop a strategy to accomplish your goals. Your focus should be on areas where DDDM will have a considerable impact. For instance, if your goal is to generate more leads by increasing the email list, your hypothesis should be to create a lead magnet to measure the impact of the email subscriptions you get.
Identify the Data You'll Need
In this step, you must identify the data you need for your data-driven product development. Data is divided into two broad types: quantitative and qualitative. Quantitative data is what people talk about big data. Qualitative data is non-numeric in nature and subjective.
Build Your Data Process
After identifying the data you need, you have to figure out how you'll collect the data. Check if the data collection process is something you can do in-house or if you'll have to outsource the process. If you already have a method for collecting data, you don't have to put much thought into this step.
Ensure you find a reliable source and determine how the data will be sampled. Data from a single source will be limited in scope. Therefore, having more data sources is the best way to go. However, if you currently don't have that process, you must look for a company specializing in data collection. The average business uses five data sources, and three of the sources are external. Using multiple data sources, you'll need common variables in each source to ensure the information can be integrated accordingly.
Analyze the Data
Once the data collection process is over, you must proceed to the next step, the analysis by developing data. In this step, you have to invest in quality tools. You are good to go if you have the skills, resources, and capabilities to analyze the data. However, hiring a trained specialist to handle the order effectively is advisable.
Having the right people is key to data management and analysis. The right people will be the heads of departments and any responsible parties. It will be easier to interpret data if it is more accessible.
Visualize Data Into Action Points
Once you have streamlined the data, you need to create smart strategies. The data you get from DDDM will be invaluable and help identify product functionalities issues.
Make the Decision
Now that you have everything ready, it's time to decide using the insights you have gained. Transform the insights into actionable strategies that will be beneficial to your business. Presenting the data and communicating is an easy-to-understand way, even to people without any technical training. Timing and presentation are crucial if you want to make an impact. Any decisions backed by quality data and numbers will be objective and sound.
Conclusion
Data-driven decision-making is not the only new trend businesses have to hop into to be more relevant; it is a process that allows companies to make systematic decisions. Using the power of data in decision-making will set your organization for success.
Data-driven methodologies have to do more with just business choices. Still, it involves the idea's effectiveness based on facts and analytics you get once you study the market. At Mach One Digital, we have been using the data-driven approach to make the best decisions that help us create digital solutions for our clients. Schedule a discovery call with Mach One Digital for more information.
