In today’s modern landscape, running any size company can be daunting. But when you’re a small business, it can seem you have countless challenges to face, from deciding whether an automated receptionist is worth investing into implementing cybersecurity best practices. At the end of the day, you have one goal in mind: growth.
One primary element of your business strategy that can help drive growth is the enormous amount of data you collect and use on a daily basis. Much of this data comes in raw form, and you need a way to not only collect and store that data, but to transform and analyze it.
Enter data science, a highly beneficial practice that provides valuable insights into data, informing your tactics and helping you achieve growth.
What is Data Science?
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Data science leverages different statistics, scientific methods, processes, and algorithms to make sense of big data that your business and customers generate.
That data can be used in any area of your business, and it’s the job of data scientists to offer you different solutions and tools to work with that data. There are differing forms of data science, some of which you may want to use now, while others will be more useful in the future.
Most of the data you collect now comes in large, unwieldy data sets and is raw in form. Part of data science’s responsibility, particularly in the area of Business Intelligence (BI), is to transform this unstructured data into information that you can use to inform business strategies and decisions. They can also help to design data warehouses (or lakes) that can store your ever-increasing data.
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Once you have data in organized datasets, it becomes easier to access and understand. Data science allows you to utilize that data in various ways to improve your operational efficiency. For example, let’s say you utilize a platform like text messaging services for businesses so you can easily communicate with customers by SMS and MMS.
The data you collect will allow you to segment or cluster customers on the app and optimize messages sent to them.
6 Ways Data Science can Help Your Small Business Grow
Data science is not a single-track road; it is an information-based super highway that can be used in different areas of your organization, in different ways.
By identifying how you can leverage data science for small business, you can look at how it can be applied to nurture growth now and in the future.
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1. Business Intelligence
For many businesses, BI is one of the core uses of data science. As mentioned, most of the data you collect comes in a raw format and isn’t actionable.
Data scientists help design systems and processes that not only collect your data more efficiently but also help store it, sort it, and transform it. Once you have datasets that you can clearly understand, you can make more informed decisions.
Within BI, you can utilize different data in different ways. For example, you could analyze competitor data to strategize ways to outperform them where possible. Or you could look at patterns in your own sales to identify weak points or periods of peak demand.
2. Financial Control
Financial stability is crucial for small businesses where resources are often tight. Data science can help you maintain financial stability by designing and implementing systems that closely monitor all income and outgoings. Data science is also an integral factor in internal audit reporting, allowing you to break down key data into digestible and actionable content.
By utilizing artificial intelligence (AI) and machine learning (ML), any system can pinpoint potential issues before they arise. For example, if you have a large amount of invoices due to suppliers on a certain date and that amount will be larger than due income, it allows you to plan ahead by diverting funds.
3. Improved Efficiency
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Operational efficiency can significantly impact your costs and, ultimately, your profitability. By scientifically processing data, you can monitor different areas of your business to optimize efficiency, leading to lower costs and higher profit margins.
This can be especially useful in manufacturing businesses where outdated processes can be highlighted and workflows streamlined.
However, it’s not just manufacturing where data science can help. It can also be used to monitor and analyze performance in any area of your organization, allowing you to pinpoint areas where improvements can be made.
With statistical data, you can view details such as work volume and staff efficiency, then reactively scale without compromising work quality.
4. Increased Security
Cybersecurity is essential when it comes to protecting all of your data, not just sensitive customer information. Data science helps in this area with cybersecurity analytics.
Applied to your whole network, this process monitors and tracks data to identify vulnerabilities and analyze your capabilities, helping you to implement an effective cybersecurity strategy.
Effective security engenders trust, which is an essential factor for customer service and business continuity. By using ML algorithms and behavioral analytics, data science can provide constant monitoring of your networks and help mitigate the risk of fraud and other cybercrime attacks.
5. Improved Customer Experience
Your customers are usually your primary source of income – and that means providing the best possible customer experience that encourages loyalty.
Better customer retention rates lead to lower customer acquisition costs and more opportunity for growth. So, how can data science help improve the customer experience?
Through customer data collection and analysis, you can improve every step of the customer journey. For example, analytics can help you identify pain points that may be preventing a potential customer from becoming a paying one. Or, if you’re experiencing high rates of cart abandonment, data science can help identify why.
6. Predictive Forecasting
Having an idea of what products to offer in the future can play a crucial role in a business’s ability to grow. By combining historical data with current data, you can forecast what may happen in the future. Predictive analytics can include identifying seasonal fluctuations in demand that can help you make decisions around stock.
As well as your own data, this use of data science also considers emerging market trends to identify what products will remain popular and which new ones you should consider stocking. By strategically analyzing data from social media platforms, your business, and those of competitors, you can focus on products that are likely to sell in the future.
Areas of Data Science to Consider
Depending on your business type and model, different areas of data science may be of more use to you than others. Understanding specific areas of data science and what they do can help in data-driven decision-making. Let’s look at a few key areas that are worth considering.
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Cloud Computing and Databases
With so much data being generated and stored – and that amount increasing daily – having a robust data storage plan is essential. Much of that storage now takes place in the cloud. You can use data science to deliver services from the cloud or design a multi-dimensional data model, such as star schema.
Organizing data this way makes it easily accessible and understandable for decision makers. It also means that any analytics you utilize are more efficient, helping you to make smarter business decisions.
Data Engineering
Data engineering can be a crucial part of an excellent data science strategy.
As you will have gathered, you need systems that harvest necessary data, store it safely, and facilitate the transformation of raw data into usable information. Data engineers build a system that meets your needs and incorporates relevant AI and ML components.
You need these systems (and the ML and AI parts) because each step of your data process would be impossible to achieve manually. Data engineers can write algorithms that focus on collecting and analyzing the data that really matters to you.
The Takeaway
There are many misconceptions around business growth. However, utilizing data science for small business growth is essential to achieving your goals.
The main focus? Other than collecting, storing, and analyzing your business-related data, these scientific processes highlight what isn’t and isn’t working for your company, providing you with valuable insight from which to base future decisions.
By digesting this data into usable information, you can improve performance and operational efficiency, helping you increase supply to keep up with demand, secure more customers by targeting their needs, and scale your business.
While the field of data science may seem daunting to those without technical knowledge, consider it a crucial step in transforming large amounts of what is unintelligible data into information you can understand and utilize to fuel business growth.
Disclaimer: The author is completely responsible for the content of this article. The opinions expressed are their own and do not represent IEEE’s position nor that of the Computer Society nor its Leadership.
