BECOME A DATA-DRIVEN BUSINESS
By: Michael O
Tags: Data Science, Business Intelligence, Competition, Data, Data Analysis

The 21st century is filled with huge opportunities for businesses that understand the power of data. Being able to gather the right data and conducting analysis that will provide a competitive insight for the business is important. This can determine either you will remain in business or not. The competition is fierce as the big players get bigger and new entrance to your niche market can lead to disruptive innovation. Having the right data can provide you with information that will both enable you to make good decisions and put your business ahead of the competition. Your investment in data and data experts as a business can no longer be considered a nice thing to do; it is the necessary thing to do. Businesses that refuse to take advantage of the power of data and are negligent to the values this might bring to the organization will eventually get submerged. We are now in the age of data where understanding your customer is an art and likewise science. In this short article, allow me to quickly show you ways you can utilize data and the kinds of data analysis you can use in your business to make well-informed decisions. These are

Descriptive Analysis

This type of analysis can be considered the starting point and it is useful in business as it can provide a summary of what has happened in the past in order to help the management understand the situation of things. This type of analysis makes use of past data gathered from past events or activities. It can provide you a summary of your business performance. For example, this type of analysis can show you how many times a particular customer has ordered your product or used your services, how many times a particular customer has complained about a particular issue with regards to your product or service. It can also capture your revenue reports and sales. This type of data will help you to answer what has happened in the past. This will provide you with information about what has happened but will not tell you why, how, or what you can do better.

Diagnostic Analysis To find the solution to a problem, you do not just want to know what has happened, but you will be interested in knowing why? Understanding why it happened can point you in the direction of what you can do differently as a business. The diagnostic analysis can be useful in helping you to answer why. Using your findings from your descriptive analysis, you then need to drill further to ask why. To conduct a diagnostic analysis using the example of the customer above, you could follow these three steps. Note that these steps are not absolute and there is nothing wrong with including any steps that might work for your business. At the end of the day, want you need is the result.

Dig out exactly what happened: Here you are taking a closer look at your descriptive result to identify specifics. From the example above, the descriptive result already showed you that your customers are unsatisfied and complaints have gone up drastically. In digging out what has happened, you want to know what exactly your customers are not happy about. For example, if your customers are not happy with your fresh drink product, you will want to ask questions such as which of the product? What flavor of the product your customers are not satisfied with, why are they dissatisfied with a particular flavor, what is the percentage of customers who are not satisfied with the particular flavor, how much purchase percentage this group of customers contribute to the monthly sales of this particular product, for how long has this been going on. The questions can go on and on. The more specific you are in this type of analysis, the closer you are to the root-cause of finding an answer to your why.

Here you are taking a closer look at your descriptive result to identify specifics. From the example above, the descriptive result already showed you that your customers are unsatisfied and complaints have gone up drastically. In digging out what has happened, you want to know what exactly your customers are not happy about. For example, if your customers are not happy with your fresh drink product, you will want to ask questions such as which of the product? What flavor of the product your customers are not satisfied with, why are they dissatisfied with a particular flavor, what is the percentage of customers who are not satisfied with the particular flavor, how much purchase percentage this group of customers contribute to the monthly sales of this particular product, for how long has this been going on. The questions can go on and on. The more specific you are in this type of analysis, the closer you are to the root-cause of finding an answer to your why. Identify your data source: Here you want to ensure you are collecting data from the right customers. One way to do this again using the same customer complaint example, you can request the contact details of all the customers who have complained and speak to them to collect data. Note that it is important to get direct contact with the customers and in collecting your data, it will be a plus to use the medium that will allow the customers to provide a sincere response and not one that is convenient for you.

Here you want to ensure you are collecting data from the right customers. One way to do this again using the same customer complaint example, you can request the contact details of all the customers who have complained and speak to them to collect data. Note that it is important to get direct contact with the customers and in collecting your data, it will be a plus to use the medium that will allow the customers to provide a sincere response and not one that is convenient for you. Understand the impact that has happened: In most cases, the business-customer relationship will be affected when customers feel dissatisfied. It is your responsibility as a business to immediately amend the relationship. Your customer will probably know and have the contact of other customers. When customers come together to exchange views about their experience with your business, two things will happen- you will either gain their loyalty or lose them.

Predictive Analysis

This type of analysis is useful in that it can predict with the help of added technology what could happen in the future by analyzing what has happened in the past. This is a buildup on your descriptive and diagnostic analysis. With the power of statistical modeling, this type of analysis can forecast the future. It can be useful for risk assessment, sales forecast, and many more. Although this type of analysis is predictive which means it is only an estimation that is dependent on the integrity of your data. Predictive analysis has been applied in manufacturing for equipment maintenance where data from the health and performance status of the equipment is monitored and sent to an intelligent system that automatically conducts predictive maintenance analysis. This can also be applied in your business regardless of the industry you operate. Predictive analysis can help you understand which of the products your customers will most likely purchase more, it can help be helpful in your sales forecast, and many more. With software like SAS Advanced Analytics, Board, SAP Predictive Analytics, and many others out there, you can do so much with your business and remain ahead of your competitors.

Prescriptive Analysis

This type of analysis makes use of advanced Artificial Intelligence (AI) systems to analyze a large volume of data that can help improve decision making. This type of analysis is currently considered the final phase of data analysis but we truly do not know what kinds of technology might come on board in the future within the field of data analysis. Big players such as Apple, Google, Facebook, IBM, and many others are currently using this type of analysis to analyze a large volume of data that can be useful to make prescriptive decisions with regards to tailored marketing and advertisement. It is endless what you can do with the power of data in the 21st century. Some software you can use for prescriptive analysis are AIMMS, Tableau, sisense, and many others.

Conclusion

Data is at the core of everything we see happening in the 21st-century world and this is not going to change anytime soon. In fact, all the 4th industrial revolution technologies are built on data and will require data to function. As I have shown above, your understanding of how to use the data in your business can serve as a competitive advantage. Your business success is highly dependent on how intelligently you can use data. To thrive in the 21st-century business environment, you must be ready and committed to becoming a data-driven business. I hope you find this useful. Kindly share your thought in the comment session below.

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Published By Michael O’ Adetu