Best Tips to Incorporate Operational Analytics into Business Process

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The Power of Operational Analytics: Tips for Implementation

Operational analytics can play a crucial role in driving the success of a business by providing valuable insights into its processes, performance, and customer behavior. It is a powerful decision-making tool, helping organizations optimize their operations and achieve their goals more effectively. However, incorporating operational analytics into a business can seem daunting.

This blog will explore the best tips for seamlessly integrating operational analytics in to your business processes and maximizing its potential benefits. From defining the right metrics to measure to choosing the right tools and technologies, we will cover all the key considerations for successful implementation. By following these tips, you can unlock the full potential of operational analytics and take your business to the next level.

What is Operational Analytics?

Operational analytics is a branch of business intelligence that focuses on using data and analytics to improve the efficiency and effectiveness of an organization's operations. It involves collecting, analyzing, and interpreting data from various sources within an organization. Data will be from transactional systems, log files, and sensor networks, to provide real-time insights into the performance of business processes, systems, and people.

The goal of operational analytics is to help organizations make informed decisions about their operations, identify areas for improvement, and optimize their processes to achieve better outcomes. This can include improving customer satisfaction, reducing operational costs, increasing operational efficiency, and improving the overall effectiveness of business processes.

Did you know?

According to a report by Forrester Research, the  global operational analytics market is expected to reach over $25 billion by 2023, growing at a compound annual growth rate of more than 20%.

Why Operational Analytics?

Operational analytics is a crucial aspect of modern businesses, providing real-time insights into day-to-day operations. With the help of operational analytics, organizations can make informed decisions, identify areas for improvement, and streamline processes. It helps organizations to track and monitor key performance indicators, customer behavior, and market trends. By analyzing data from various sources, businesses can gain valuable insights into their operations, which can be used to optimize processes, improve efficiency, and increase profitability. Operational analytics enables organizations to respond quickly to changes in the market and customer demands, making it an indispensable tool for businesses looking to remain competitive in today's fast-paced market. In addition, it allows businesses to identify areas where they can cut costs, reduce waste, and improve their bottom line.

Did you know?

A study conducted by Gartner found that companies that invest in operational  analytics can improve their operational efficiency by up to 15%.
Why should  companies invest in operational analytics?

90% of businesses have adopted operational analytics in  some form
Operational analytics is estimated to be 15% of the  overall IT budget of companies
65% improved decision-making
60% increase in operational efficiency
55% reported better customer experiences 

Operational Analytics and its Impacts on Businesses

Operational analytics have the potential to impact a business in several ways significantly. Operational analytics' key impacts on a business include

  • Improved Efficiency: By providing real-time insights into business processes, operational analytics can help organizations identify areas for improvement and optimize their operations, leading to increased efficiency and reduced costs.
  • Better Decision-Making: Operational analytics tools provide data-driven insights that can inform decision-making and help organizations make more informed decisions about their operations and strategies.
  • Enhanced Customer Satisfaction: Operational analytics can provide insights into customer behavior and preferences, allowing organizations to improve the customer experience and increase satisfaction.
  • Increased Revenue: By improving efficiency, making better decisions, and enhancing customer satisfaction, operational analytics can help organizations increase their revenue and profitability.
  • Improved Risk Management: Operational analytics can help organizations proactively identify and mitigate potential risks, improving their overall risk management capabilities and reducing the likely hood of negative impacts on the business.
  • Competitive Advantage: By using operational analytics, organizations can stay ahead and gain a competitive advantage in the market.
A study by Accenture found that companies that use  operational analytics can reduce costs by up to 25% through more efficient  operations and data-driven decision-making.

Tips for Implementing Operational Analytics in your Business

Incorporating an operational analytics platform into your business process can unlock its full potential and drive better outcomes for your organization. Here are some tips to help you get started, backed by statistics:

1. Define your Goals and Metrics:

Start by defining the goals you want to achieve through operational analytics and the metrics that will help you measure progress towards those goals. This will help you determine the data and information you need to collect and the questions you want to answer through your analytics. Organizations with clear, well-defined goals for their analytics initiatives are three times more likely to see a significant return on investment.

According to a report by Forrester Research,  companies that implement operational analytics see an average return on investment (ROI) of over 200% within the first year.

2. Choose the Right Technology:

Choosing the right technology for implementing operational analytics solutions in business requires careful consideration of several factors. Start by defining your business requirements and goals, and then assess the data sources and systems you already have in place. Consider the technology's scalability, reliability, and security and its compatibility with your existing infrastructure and your team's skills. Consider cloud-based solutions for greater flexibility and scalability

A report by Gartner found that cloud-based analytics  solutions are growing much faster than on-premises solutions, with a 25%  increase in adoption year-over-year.

3. Create a Data-Driven Culture:

Encourage a data-driven culture within your organization, where data and insights inform decision-making and drive continuous improvement. This can be achieved by promoting a data-centric mindset, providing data access and data analysis training, and encouraging employees to use data to inform decision-making.

According to a survey by New Vantage Partners, 92% of  companies believe that a data-driven culture is critical to success.

4. Ensure Data Quality:

Ensure that the data you collect and use for operational analytics is high quality, accurate, and consistent. Data quality issues can lead to incorrect insights and decisions. To achieve this, your organization should establish clear data governance processes and policies, implement data validation and cleansing routines, and regularly monitor the accuracy and completeness of their data. A strong focus on data quality will help ensure that operational analytics solutions deliver accurate and valuable insights for informed decision-making.

A study by IBM found that poor data quality costs  organizations an average of $14.2 million annually.

5. Automate Data Collection:

Automate data collection and processing to ensure that data is consistently and accurately collected and analyzed in real time. It helps integrate data from multiple sources, such as databases, spreadsheets, and web applications, into a centralized data repository. Automated data collection eliminates manual data entry errors and ensures that data is always up-to-date, enabling organizations to make data-driven decisions confidently. This will help you quickly identify trends and patterns and respond to changing business conditions.

According to a report by Accenture, organizations  that use automation for data collection and processing are 4 times more likely to see improvements in efficiency and accuracy.

6. Communicate Results and Insights:

Effective communication of results and insights from operational analytics is crucial for driving business outcomes. This involves creating clear and visually appealing reports and dashboards that communicate key metrics and KPIs and presenting them in a manner that is easily understandable by all stakeholders. Regular communication of results and insights helps ensure that operational analytics drive meaningful business outcomes and support data-driven decision-making.

A study by McKinsey found that organizations that share  data and insights across functions and departments are 4 times more likely to  make data-driven decisions.

7. Continuously Monitor and Evaluate:

Continuously monitor and evaluate the results of your operational analytics initiatives and make changes as needed. This involves regularly reviewing operational analytics performance, identifying improvement areas, and making necessary adjustments. Continuously monitoring and evaluating operational analytics helps ensure that they remain relevant, effective, and aligned with changing business needs and supports the continuous optimization of business processes.

A survey by Forbes Insights found that organizations  that continuously monitor and evaluate their analytics initiatives are 5 times more likely to see a significant business impact.

By following these tips, you can successfully incorporate operational analytics into your business processes and drive better outcomes for your organization. The key is to start small, be disciplined, and continuously improve over time.

How Could Operational Analytics Help your Business?

Operational analytics solutions can be applied to many business processes and functions to drive better outcomes and improve performance. Here are some common use cases for operational analytics:

  • Supply Chain Management: Operational analytics can help organizations optimize their supply chain processes by analyzing data on supplier performance, inventory levels, and delivery times.
  • Sales and Marketing: Operational analytics can help sales and marketing teams make better, data-driven decisions by analyzing customer behavior, buying patterns, and campaign effectiveness.
  • Customer Service: Operational analytics can help organizations improve customer service by analyzing data on customer interactions, satisfaction levels, and support ticket resolution times.
  • Finance and Accounting: Operational analytics can help finance and accounting teams make more informed decisions by analyzing financial performance, budgeting, and cash flow data.
  • Human Resources: Operational analytics can help HR teams optimize their processes by analyzing employee performance, turnover, and training effectiveness data.
  • Manufacturing: Operational analytics can help manufacturers optimize their operations by analyzing production rates, machine utilization, and product quality data.
  • Healthcare: Operational analytic scan help organizations improve patient outcomes by analyzing treatment effectiveness, patient satisfaction, and resource utilization data.

These are just a few examples of how operational analytics can drive better outcomes in various business processes and functions. The specific use cases will vary depending on the needs and goals of the organization.

According to a recent survey, 60% of organizations  use operational analytics for supply chain management, making it the most  popular application of operational analytics.


In conclusion, operational analytics can have a significant impact on the success of your business. It provides valuable insights into your operations, enabling you to make informed decisions and drive continuous improvement. By incorporating these tips into your business process, you can successfully leverage the power of operational analytics to achieve your goals. Whether you are looking to increase efficiency, reduce costs, or improve customer satisfaction, operational analytics can help you reach your desired outcomes.

However, it's important to remember that operational analytics is an ongoing process and requires continuous monitoring and refinement to remain effective. With the right approach, operational analytics can help you achieve long-term success for your business. Most companies outsource their operational analytics needs to a third-party service provider. Outsourcing operational analytics to a partner like Phygital help your harness the power of data in making the right decisions. Phygital Insights is a leading data analytics company providing various analytics solutions to businesses across the globe.

Article by

John is a seasoned data analytics professional with a profound passion for data science. He has a wealth of knowledge in the data science domain and rich practical experience in dealing with complex datasets. He is interested in writing thought-provoking articles, participating in insightful talks, and collaborating within the data science community. John commonly writes on emerging data analytics trends, methodologies, technologies, and strategies.


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