The entrepreneurial journey is a long and rigorous one. Of any business endeavor or experience, entrepreneurship requires the most comfortability with ambiguity. By nature, it does not come with a tidy roadmap or set of validated parameters. Entrepreneurship requires voyaging out beyond the edges of what has been done or understood before.
Because of this, it can be a very difficult undertaking to track, validate, and predict how an entrepreneurial endeavor should move forward. Many of the conventional rules don’t always apply or work. This can create huge problems for entrepreneurs. Many run into severe roadblocks, difficulties, losses, and “false failures” that sometimes kill projects that actually had huge potential.
However, the growing world of data analytics offers unprecedented tools to entrepreneurs that can change the way they can validate their work. Predictive data analytics can produce insights that can guide entrepreneurial efforts towards quicker wins and stronger successes, and help them avoid pitfalls and wasted time.
Applying predictive data analytics is a must-do in today’s increasingly competitive and evidence-dependent entrepreneurial markets.
The Challenges and Responsibilities That Accompany Entrepreneurship
Entrepreneurs are innovators. They work to bring into existence something that wasn’t already available. Most entrepreneurial endeavors start small and are strapped for resources, requiring entrepreneurs to wear many hats and contribute to all aspects of a business’s development in the early days.
Single founders in particular are marketers, product designers, accountants, salespersons, developers, and executives all in one. They are confronted with numerous decisions a day, many of them vastly varied from each other and some of them highly impactful or risky. Without strong decision-making support, entrepreneurs can struggle to move their projects or dreams forward effectively.
Entrepreneurs have to cast an ambitious vision for their prospective clients and customers, potential investors, board members, and team. And concurrently, they need to deliver enough value to secure the next sale, contract, or funding round. Entrepreneurs walk a very difficult and demanding road. Further, the ability to continue depends on being able to prove over and over again that their idea is a good one. This is difficult to do on speculation or with limited means of demonstrating it conclusively.
How Data Analytics Is Being Incorporated Into Entrepreneurship
Data analytics, or the process of utilizing large amounts of collected data to glean insights and inform business decisions, is a rapidly developing area within the realm of business. Data analytics is a relatively broad term that can refer to a number of different processes, methods, and applications. It is being used in industries that range from manufacturing to service-based agencies to high-scale tech.
Applications of data analytics can range widely between instances because it can be used to achieve so many different types of insights. However, the basic archetype usually begins by organizing data from a single source (or aggregating and then organizing data from multiple sources) in a software or data platform where it can be processed. That data is then sliced, diced, computed, and/or expressed in visualizations. The final result includes a better and more actionable understanding of trends, learnings, habits, customer behavior, best practice, and more.
One of the most promising and exciting capabilities of data analytics is its use in generating predictive intelligence. Because data analytics tools and applications can process huge quantities of data (much more than could ever realistically be computed or analyzed by hand), the process can not only provide evaluations of past happenings to shape learnings after the fact – but it can also actually predict, with high degrees of accuracy in some cases, what is likely to happen in the future. This is just one of the incredible benefits of applying data analytics in business or entrepreneurship settings.
Creating successful entrepreneurial endeavors relies heavily on correctly anticipating future needs, trends, and realities. Because of this, applying predictive data analytics to entrepreneurship is a natural and highly impactful strategy for improving an entrepreneurial project’s odds. Using predictive analytics can help entrepreneurs design their businesses and concepts correctly and effectively for future users, markets, and needs.
Setting Up Mechanisms for Predictive Data Analytics
It’s one thing to point out its potential. It’s another to actually apply the power of predictive data analytics to an entrepreneurial undertaking in real life. How does an entrepreneur actually make use of data analytics to start making better decisions about the future of their field or industry? This is possible and achievable in just about every industry. However, it takes a little bit of implementation and effort.
It might seem that the first step to incorporating predictive data analytics into a new business effort would be to start amassing data. While this will be an important step, it shouldn’t actually be the first part of the process. Incorporating a data strategy should actually start with a thorough analysis of the end game.
What insights would likely help move the needle forward? What things need to be made known in order to ensure the company is moving in the right direction? What learnings will help avoid mistakes and resource waste? What feedback is most critical in this stage of the business’s growth? These questions and more should be used to identify how data analytics will actually be applied to the endeavor. Data doesn’t do anything by itself – it needs to be effectively and thoughtfully applied to decision-making processes and allowed to inform assumptions and behaviors before it begins to create value.
Once an entrepreneur and/or an entrepreneurial team has given these questions honest consideration, the next step is to begin procuring the necessary data that will provide these insights. Data can come from nearly infinite sources. Many data types are now generated automatically without anyone needing to manually capture them. These include things like computer or application-generated user data or behavior statistics, usage metrics stored automatically by devices and smart objects, video footage from security cameras, public records, information, and many more.
Depending on the needs of the entrepreneur and the business or project, these types of data might suffice or may not be remotely relevant. Other types of data might need to be collected more intentionally. Survey data, academic research, interviews with clients or prospective customers, write-ups from experts within the team or the industry, and more all fall into the category of data that must be more diligently gathered before it can be processed. Whatever types of data were identified during the first step need to be gathered and wrangled into an accessible form or location to move forward.
Once an entrepreneur has secured whatever data types and sources are needed and has a reliable way of capturing it, the next part of the process involves using some type of platform or data processing software to work with the data and process it into insights.
This might be a Business Intelligence (BI) tool, a database or online application, a data processing service, an Excel spreadsheet, or something else entirely. There is no wrong way to process data as long as it provides quality, accurate information.
Applying Insights to Decision-Making
Once optimal data has been identified, captured, and processed, there is a final step for entrepreneurs who want to benefit from predictive analytics. You can find plenty of examples in recent business history in which great pains were taken to create a data processing pipeline that may have worked perfectly but, in the end, was never ultimately beneficial because the insights were never applied to the business. If a process isn’t clearly instituted to apply the insights generated from a data analytics strategy, it can generate all the pretty graphs and good suggestions in the world and still be a complete waste of time.
If you plan to apply predictive data modeling to your entrepreneurial endeavor, it’s important to think about how you will make sure the last (and arguably most vital) step in the process doesn’t get left out. Apply your learnings to your business. Incorporate your data analytics results in each team meeting, in a dedicated monthly review, or in your quarterly presentation to the board. Make sure your team has access and instructions for how to regard and utilize the data you’re processing. Make it a priority to include teaching your data process when onboarding all new staff. Make it a part of your company’s rhythms and culture.
How Predictive Data Analytics Can Change the Game for Entrepreneurs
If applied well, predictive data analytics could make the difference between picking the right course of action and missing a vital opportunity or choosing the wrong priority and ultimately running out of time or funding. It’s well worth an investment of time and resources to implement for your company or project.
