Since the start of the 21st century, the number of startups has surged, with their combined valuation exceeding $3 trillion. In 2019 alone, global venture capital investments topped $300 billion.
At the same time, the rapid growth of big data is transforming how organizations operate. Relying solely on intuition, logic, or experience for decision-making no longer works.
Many now consider data to be the most valuable asset for businesses, and startups are no exception.
This article explains the role of data-driven decision making for entrepreneurs and lays down the framework for entrepreneurial decision-making needed for startup success.
What is entrepreneurial decision-making?
Conventional decision-making, especially in managerial roles, tends to be more structured. You only need to look for an optimal choice based on available data, which usually leads to a single, agreed-upon answer.
In contrast, entrepreneurial decision-making is fluid. It doesn’t follow a set formula, instead, is more about navigating through ambiguity with a mix of data-driven approach and gut feeling.
Entrepreneurial data-driven decision-making (DDDM) means using data to guide and validate decisions before taking action.
While DDDM has been used in large organizations for years, the increasing amount of data generated today makes it more accessible to businesses of all sizes, including startups.
A PwC survey of over 1,000 senior executives reveals that organizations with a strong focus on data are three times more likely to experience substantial improvements in decision-making.
Entrepreneurs have to make countless decisions, but some of the most critical include:
- What will the business offer, and how will it stand out from the competition?
- What are the costs involved with their intended offer?
- Who is the target audience, and what are their needs and wants?
- How will the business generate revenue?
- Who are the right people to help the business succeed?
- How will the business get the necessary capital to start and grow?
These decisions are complex and interconnected, and there's no one-size-fits-all answer. Entrepreneurs have to weigh the risks and rewards carefully based on data and be prepared to adapt as needed.
How entrepreneurs can make smarter decisions with data?
Whether your startup grows into a large-scale business or fails to drive revenue depends on the choices you make.
With so much on the line, how can entrepreneurs make decisions that are less risky and help them succeed in the long run?
Here are the top 7 tips that will help you with entrepreneurial decision-making using data.
1. Capture, Clean, and Organize relevant data
As an entrepreneur, you should collect as much information as possible, even if you're not sure how you'll use it immediately.
There will come a time when you need answers to questions you currently don’t even know, and the last thing you want is to realize you’re missing crucial data.
Think creatively about what data could be useful. Get your team involved—ask them to come up with scenarios and figure out what data would help make the right decisions.
Don't just stick to data collection methods you've always used. Look at both internal sources, like customer surveys and historical trends, and external ones, like market research. Thanks to modern data platforms, it's easier than ever to bring all this data together.
The more you capture, clean, and organize, the better equipped you'll be to spot patterns and trends that drive smarter decisions.
2. Create a centralized data repository
When data is scattered in silos, it’s tough to see the big picture. Integrate data from all your business operations—HR, sales, project management, code repositories—into a single, scalable data lake.
You can use AWS, Google Cloud, or Azure to build secure and robust data lakes tailored to your business needs. The centralization not only improves accessibility but also allows for easy cross-department insights.
In a centralized system, data is always up-to-date, so everyone is working with the same information. The consistency in data leads to more reliable analysis and smarter entrepreneurial decision-making.
3. Use business intelligence tools to analyze your data
Over the past few years, business intelligence (BI) tools have come a long way from basic reporting systems to robust platforms equipped with big data analytics capabilities and machine learning.
As an entrepreneur, tap into self-service BI tools with drag-and-drop features that let you handle data analysis independently. Create custom reports, automate updates, and interact with your data through dynamic dashboards with analytics tools.
Data visualization platforms are another must-have. They transform complex data into interactive visuals like charts and maps so you understand and communicate your findings better.
Predictive analytics tools for startups use historical data and algorithms to forecast future outcomes, which is invaluable for planning and risk management. It helps you anticipate trends and make proactive decisions.
4. Define the right data KPIs
The success of data-driven businesses hinges on how well your data teams manage your data, from collecting and analyzing data to reporting insights that guide business decisions.
But how can you ensure that your data team is hitting the mark? The key is Key performance Indicators (KPI) reporting:
Here are a few KPIs you should be reporting to zero in on those involved in your data operations:
- Number of insights generated per month
- Frequency of analytics use by decision-makers
- Accuracy of Predictions
- Data system uptime
- Number of errors per month
- Turnaround time for fixing errors
- Number of business problems solved using data
5. Invest in data literacy
Creating a data literacy and decision making framework requires continuous training to ensure everyone in your organization becomes data-savvy.
Leadership sets the tone for a data-driven culture. Your startup executives should actively use a data-driven approach in their decisions and support training programs to show the importance of data literacy.
Before you improve data skills, understand where your organization stands. Evaluate how employees currently use and understand data.
Then, establish clear, achievable targets for improving data literacy. For instance, track the percentage of workflows using key data or how departments contribute to shared datasets.
Design a diverse training program that accommodates different learning styles. Your employees should be proficient with the following decision-making frameworks:
- Decision matrix
- Pros-and-cons list
- Decision tree
- Pareto analysis
- Cost-benefit analysis
- Conjoint analysis
- SWOT analysis
- PEST analysis
You may also incentivize data literacy by tying rewards or even compensation to data-related achievements.
6. Leverage AI-powered decision making
The beauty of AI is in its ability to process huge amounts of data at lightning speed and bring insights that would take humans forever to spot.
The more intricate the decision, the more AI can help with cutting through the noise to give you clear, data-backed options.
By 2026, it's predicted that 85% of enterprises will use a blend of human intuition and AI for better decision-making.
MakerSights, for instance, is an AI tool that helps retailers with data-driven business decisions by analyzing everything from sales data to customer preferences. It then suggests decisions on new product launches and marketing strategies.
Rainbird takes a different angle and prioritizes optimizing customer experiences and helping to create innovative digital products, all based on data.
7. Find a balance between data and intuition
Develop a systematic approach by setting clear rules for data analysis and decision-making. Use data to validate and refine your gut feelings, such as leveraging market trends to time your product launch effectively.
While data gives you a snapshot, your intuition, honed through experience and reflection, adds depth. So, you need to be continuously improving your analytical skills while staying tuned into your instincts for entrepreneurial decision-making.
In high-stakes scenarios, intuition can act as a decisive force. Laura Huang's research highlights that leaders often rely on gut feelings to make swift decisions, especially when data overload occurs.
Adjust your decision making as your startup grows
As your startup transitions from its initial phase to a growth-stage scale-up, your decision-making processes must adapt.
In the early stages, the flexibility to change direction rapidly is beneficial due to fewer stakeholders and less complex operations.
However, as a startup scales, each decision impacts a larger number of employees and processes, so entrepreneurial decision-making processes should adapt accordingly.
Transition from flexibility to finality
Initially, entrepreneurs make frequent pivots and often change course based on new information or evolving market conditions.
While this flexibility is beneficial initially, it becomes problematic as the company grows. Frequent changes disrupt workflows, confuse employees, and lead to wasted resources.
As you scale up, it’s essential to make decisions with greater finality. This means once a decision is made, commit to it fully and avoid constant revisions.
Move beyond indecision
Indecision, or keeping options open, is tempting but is detrimental in a scaling company. In startup decision making, keeping multiple options open allows for experimentation and adaptability.
However, as the company grows, indecision can lead to fragmented efforts and diluted focus. Make sure you establish clear priorities and make decisive choices.
For example, if choosing a target market or product feature, commit to one direction after thorough analysis and feedback.
Embrace bold, deliberate decision making
Speed is what the startup culture is all about, where quick decisions and rapid iterations are the norm. However, during the growth stage of your company, your focus should be on making well-informed and deliberate decisions.
Quick decisions lead to “shortcut debt,” where temporary solutions create long-term issues. Balance speed with thorough analysis and strategic thinking.
In a growing company, oftentimes, your decisions will be met with criticism.
Ensure that decisions align with the company’s vision and long-term goals, even if they are controversial. Communicate the rationale behind decisions clearly and foster a culture of healthy debate.
Formaloo: A complete startup toolkit
Formaloo offers a robust toolkit for startups that enables streamlined operations and data-driven decisions. With Formaloo:
- Use startup templates to outline your marketing strategy, product management system, and more using drag-and-drop interface.
- Generate real-time reports and custom dashboards to visualize data for better entrepreneurial decision-making.
- Build tailored CRMs and customer portals without coding.
- Utilize targeted surveys and polls with conditional logic to capture high-quality leads.
- Collaborate with your team in shared workspaces and fully customize your surveys.
Formaloo is committed to supporting startups. If you work with one of our global partners or meet our criteria—raised no more than $5 million, launched in the last 5 years, independent, with fewer than 50 employees, and a new user on Formaloo’s Free plan—you can apply for a $1,000 credit to use on our platform.
Try Formaloo today!
FAQs
How do entrepreneurs make decisions?
Entrepreneurs make data-driven decisions by analyzing relevant data to identify insights. They use this information to guide strategic choices and align their decisions with business goals and market needs. Their approach blends quantitative data with their expertise and intuition.
What are common entrepreneurial decision-making frameworks?
Common entrepreneurial decision-making frameworks include the decision matrix for evaluating options. It also includes the SWOT analysis for assessing strengths and weaknesses. Then, there is the cost-benefit analysis for weighing financial impacts.
What are data-driven business decisions examples?
Examples of data-driven business decisions include optimizing marketing strategies based on customer analytics and adjusting product features using user feedback data.
Red Roof Inn, for instance, analyzed flight cancellation rates and weather data to target mobile ads during bad weather, which led to a 10% increase in check-ins.
