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Here is why data analytics is a powerful tool for businesses to improve their performance.

Are you looking for ways to increase profits while also boosting business performance? 

PMRC recommends businesses explore applying data analytics as the world is growing more and more dependent on information and collecting statistics to have a competitive edge in the market. Business analytics is all about making decisions, but in a different way than in the past, when decisions were made based on experience, gut instinct, and intuition. Today, decisions are made based on data and evidence. Managerial decision making is undergoing a paradigm shift as a result of the need to make faster and better decisions in today's fiercely competitive business environment, the accessibility of large and feature-rich data sources, and the advanced computer resources (both on the hardware and software side).

Data analytics has become highly in demand as it helps businesses optimize their performance, perform more efficiently, maximize profits, or make more strategically-guided decisions. Data analytics is a crucial process of collecting, categorizing, and analyzing raw data. Data analytics can aid businesses in determining how customers behave, what products and services are selling successfully, and where costs are being spent. With data analytics you are able to make more well-informed decisions based on previously analyzed data. Data analytics techniques can reveal trends and metrics that would otherwise be lost in the mass of information. This information can then be used to optimize processes to increase the overall efficiency of a business or system.  

However, turning the abundance of data stored and accessed by businesses into useful insights is a skill. It comes with costs like time, money, and risk, but if done right, has the potential to drive performance and support growth for years to come. For many businesses, especially small- to mid-sized enterprises, data analytics might seem like a complicated, unapproachable process, yet it is worthwhile.

There are four types of data analytics: descriptive, diagnostic, predictive, and prescriptive. The conduct of each helps businesses to make smarter and safer decisions. Let’s go through them in more detail.

Descriptive Analytics

The main aim of descriptive analysis is to shed light on what happened over the respective period being analyzed. It sheds light on how customers interact with your products or services and how your products are performing. For instance, how many sales of certain products were realized in the previous week/month, did they increase or decrease, etc.

Diagnostic Analytics

As already indicated, a diagnostic analysis is interested in finding out the root cause that impacted the happening of a particular cause, for instance, an increase/decrease in sales. This can either be a specific season of time when the increase or decrease happened, the latest marketing campaign of the company, or any other reason. This is a type of data analytics that is used to identify and diagnose problems in a system. This type of analytics can be used to find and fix problems before they cause major damage to a system.

Predictive Analytics

After the descriptive and diagnostic analysis has taken place, data is oriented into predictive analysis, through which data analysts try to predict what will happen in the near future or how a process will develop. This analysis occurs through a combination of statistics and data mining that ends up with the creation of a visual representation in order to make it understandable and useful. Predictive analysis can be used to optimize business operations, identify and prevent fraud, and forecast customer behavior. Predictive analysis can also be used to identify and predict patterns in large data sets.

Prescriptive Analytics

Finally, a prescriptive analysis gives suggestions. Taking on board the findings of predictive analysis, it suggests a particular course of action to be taken and likewise assesses the potential implications that would come with it. Prescriptive analytics can be used to find patterns and insights in large sets of data in order to make predictions about the future.


Data analytics can help an organization with everything from personalizing a marketing pitch for an individual customer to identifying and mitigating risks to its business, also helping the business to improve its performance in a variety of ways. Some organisations have used data analytics to:

  • Personalise Customer Experience

They use data analytics to create comprehensive customer profiles from this data, businesses can gain insights into customer behaviour to provide a more personalized experience. Take a retail clothing business that has an online and physical presence. The company could analyse its sales data together with data from its social media pages and then create targeted social media campaigns to promote its e-commerce sales for product categories that the customers are already interested in.

  • Inform business decision-making

Enterprises can use data analytics to guide business decisions and minimize financial losses. Predictive analytics can suggest what could happen in response to changes to the business, and prescriptive analytics can indicate how the business should react to these changes. For instance, a business can model changes to pricing or product offerings to determine how those changes would affect customer demand.

  • Mitigate risk and handle setbacks

Risks are everywhere in business. They include customer or employee theft, uncollected receivables, employee safety, and legal liability. Data analytics can help an organization understand risks and take preventive measures. For instance, a retail chain could run a statistical model that can predict future actions or events to determine which stores are at the highest risk for theft. Businesses can analyse the risk management that helps them identify potential risks they might face in the future and measure the costs, impact, and outcomes. Businesses can also use data analytics to limit losses after a setback occurs. If a business overestimates demand for a product, it can use data analytics to determine the optimal price for a clearance sale to reduce inventory.

  • Product Development

Proper data analytics offers businesses better customer insight by gathering data through surveys or tracking clients’ inquiries and purchases. As a result, it helps them deliver to the customers the product that meets their needs.

  • Budgeting and Forecasting

One of the most important goals of data analytics in business is to lower costs while delivering performance. Data analytics helps businesses foresee their customers’ behaviors and interests and apply such insights to their business strategies.

  • Marketing and Sales

Proper marketing campaigns and an increase in sales are among the great contributions that derive from a well-conducted data analysis. In this regard, by knowing the customers’ needs and wants, data analytics allows businesses to personalize marketing campaigns which will most likely increase their sales too.

Data Analytics is a powerful tool to help businesses improve their performance.  Regularly assessing your organization’s performance will assist you in determining how far you have progressed toward your strategic and operational objectives. Implementing data analytics maybe be beneficial to understand how your organization or team members function towards the improvement of business performance.

If you are thinking of incorporating data analytics, you will need expert opinions and consultations from specialists from a reliable company with a strong project background and portfolio. Precise Management and Research Consultancy is here to partner with you. For further enquiries please contact us on     +263 719 225 464 or email us at info@precisemrc.co.zw