skip to Main Content

By the Numbers: Data Application in Business Operations

By the Numbers: Data Application in Business Operations

 

If you’re operating in the digital space, it’s important to incorporate data and process analytics into your work process. Analyzing data and forming insights are crucial to acquiring and retaining customers, mitigating risk, and navigating a path forward that’s profitable and risk-averse. In this article, we’ll outline a few examples of data application from an operational standpoint.

Customer Acquisition & Retention

Customer Management

Customer retention refers to the strategies you use to keep existing customers coming back. Analytics is critical in this regard, as it provides predictive metrics of how your customers might react to company changes, price fluctuations, etc. A data-driven approach using mathematics, statistics, and probability will allow you to safely test strategies and develop prescriptive insights without risking the real-life loyalty of your existing customers.

The same logic applies to new customer acquisition. The first and clearest advantage of an analytical approach to data involves taking a look at the costs associated with actually acquiring a new customer. With the right implementation, you can weigh the combined costs of advertising, offers, delivery, salary, and communications against the value of the customer themselves ahead of time. 

By contrast, conversion rate optimization (CRO) is a user-centric strategy designed to increase the rate of desired behavior amongst users on a website. If you’re collecting data correctly, you’ll be able to more closely scrutinize the user journey across your website pages, forms, customer service, and ecommerce site and adapt your sales and customer journey accordingly.

Internal Process ManagementInternal Process Management Using an iBPM

Many businesses underestimate the importance of internal data capture. Depending on the size of your business, deploying analytics within the context of your own office can be cost-efficient for improving productivity and operational efficiency. Data can be used to improve hiring methods, give insights into effective management, and optimize training methods. It can also be used in conjunction with key performance indicators (KPIs) to more accurately measure team attainment and scrutinize work efficacy.

Another strategy is to use business process management (BPM) to analyze how the people, systems, and data within your business interact. You can also use this tool to automate and optimize processes and workflows, leaving menial tasks to the AI and giving your employees more time to focus on more pressing issues. Automation tools and intelligent business process management (iBPM) combine to make for a more efficient operation. When creating a BPM framework, just be sure that you’re always monitoring its effectiveness and making adjustments to improve output.

Risk ManagementRisk Management

Without data analytics, it’s almost impossible to develop an effective, long-term risk management process. If you have the available technology, you can embed data to identify risks and react in real time to market shifts, faulty internal processes, etc., thereby reducing the likelihood of bad investments and wasted time. With risk profiles, it’s possible to create a framework that weighs financial and strategic threats and prescribes a course of action that would mitigate and manage them. If your data models are precise enough, it’s even possible to predict future outcomes and build workflows that respond automatically, without intervention.

A risk assessment matrix goes a step further and ranks the likelihood, impact, and severity of potential risks. These can then be manifested as key risk indicators (KRIs), which may grow and evolve over time depending on your application of machine learning. Ultimately, you want to create an approach to risk management that changes with the data, ensuring your company is adaptable to hazards as they emerge.

Through data analysis and efficient process management and automation like iBPM, your business will be able to make decisions based on behavior prediction that will improve customer acquisition and retention and company efficiency and reduce the chance of a major setback.

Data Analysis***************

Guest blogger Cody McBride’s love for computers stems from high school when he built his own computer. Today, he is a trained IT technician and knows how the inner workings of computers can be confusing to most. He is the creator of TechDeck.info where he offers easy-to-understand, tech-related advice, and troubleshooting tips.

know someone that needs to hear this? share it!

Need help with your next big project?

Back To Top