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What is Operational Analytics?

Operational Analytics is a specific term within analytics that refers to the category of business analytics that focuses on measuring the existing and real-time operations of business.

Through the use of tools designed for data mining and data aggregation, businesses can reap the benefits of being able to make better decisions because of the transparency that results from using operational analytics. So if you’ve ever heard of things like “Real-time Reporting,” or “Actionable Analytics” you’ve heard of Operational Analytics.

Being able to access real-time data with total transparency into customer behaviors and business processes is paramount in today’s business world. Only the most up-to-date data will enable business owners to specifically see the function of their day-to-day operations. After which, appropriate adjustments can be made to enhance customer satisfaction and the bottom line.

How is Operational Analytics Used in Business Today?

Operational analytics uses statistical analysis extensively and this includes fact-based management and predictive and explanatory modeling to drive decision making. Therefore, it is closely associated with management science. This type of analytics could drive fully automated decisions or may be utilized as input for management decisions.

Business intelligence involves querying, reporting, real time push “alerts” and online analytical processing (OLAP). These processes are alert tools that can be used to address questions like where the problems are, what occurred, how many instances, how frequently and what needs to happen to fix them. Operational analytics can respond to questions like “Why are these things happening?”, “What will happen if these trends persist?”, and it can predict what will happen next as well as optimize to determine what the best results are that could transpire in the future.

The following are some industry examples of how operational analytics are used today:

  • Banks use operational analytics to distinguish among their customers based on usage, credit risk and other features.
    • The data is then used to match characteristics of customers with suitable product offerings.
  • In manufacturing, operational analytics could trigger preventive maintenance to identify potential problems before they happen.
    • With this data, maintenance or the manufacturer can be alerted to the fact that service is required.

The Future of Operational Analytics

Businesses must operate in the moment to maintain their competitive advantage. To do this they need fresh operational insights. Therefore, the future of operational analytics is bright because to some degree, virtually every company is a tech company. This means they absolutely must work with data and they definitely need professionals to support them in using data to make vital decisions towards the growth and sustainability of their organizations.

The demand for cloud-based or on-demand operational analytics solutions is growing because of their time-efficient and cost-effective features. In Small and Medium Enterprises, the adoption of these platforms is especially high.

Between 2016 and 2021, the growth for operational analytics platforms is projected between $4.65 Billion and $10.93 Billion. This will be at a Compound Annual Growth Rate of 18.6 percent during the projection period.

Major growth drivers behind this staggering explosion of data are resulting from the advent of IoT-enabled devices. They increase the need for processing and operations control and optimization, advanced data management strategy adoption, and growing concentration on market and competitive intelligence.

Use Cases in the Business World

Below are 5 common operational analytics use cases:

  1. Visualizing the Environment
    • Having the ability to visualize the application environment and recognize the dependencies is a vital foundation for the other use cases below.
  2. Fast Troubleshooting
    • Having the ability to use generated data from an application environment to rapidly identify the root cause of a problem is of utmost importance for businesses in which their revenue source depends on these kinds of applications.
  3. Prioritize Opportunities and Issues
    • Once the root cause of an application performance problem is isolated, determining how to prioritize the issues is the next step.
  4. Analyze Impact on the Business
    • This is a method of quantifying the value of the work put in by operations professionals to ensure application environments operate as effortlessly as possible.
  5. Create Action Plans
    • This is all about taking the right action once the data is at your fingertips.

The Services are In Hot Demand

Among all operational analytics services, professional consulting services are projected to have the highest demand. This is because of the escalating need of analytics software solutions across industries.

Major business functions for which operational analytics is used includes marketing, information technology, finance, sales and human resources. Using operational analytics for marketing is projected to significantly increase in the coming years.

In-demand Jobs for Operational Analytics

  • Operations Research Analysts
    • These analysts are sophisticated problem-solvers who use sophisticated techniques like data mining, optimization, mathematical modeling and statistical analysis to develop solutions to assist businesses and organizations in operating more efficiently.
  • Data Scientists
    • Data scientists work closely with databases and high-performance coding and computing, machine learning and parallel processing.
  • Sales Operations Analysts
    • The primary role of a sales operations analysts is to support the sales operations team. This includes the collection and evaluation of data associated with sales performance and providing management with key insights and data concerning sales operations challenges.
  • Data Business Analysts
    • A data business analyst uses generated data to come up with insights regarding the business. It is appealing to individuals who are looking for a combination of data analysis and business-related tasks. The ability to see the big picture and inquisitiveness are typical characteristics among individuals in this field.
    • Research on analytics careers revealed some amount of uniformity in job descriptions. For example, each career path calls for individuals with the capacity to work in a dynamic and fast-paced environments. An analytical perspective is necessary as well as the ability to communicate exceptionally in both the verbal and written forms. Analytics specialists must be driven self-starters, who are capable of producing meaningful and organized products, with knowledge of content and project management tools.

Interesting Statistics

  • A recent study revealed that development in operations via the use of data can assist in raising annual profits as much as $117 billion worldwide. This represents a sharp increase in comparison to customer analytics that drives roughly $38 billion in profits. An improvement in the bottom line indicates you are capable of scaling your business, regardless of its size.
  • A recent survey found that 70 percent of companies have begun focusing on operations processes rather than consumer processes.

Overall Operational Analytics is still a very widely under-utilized phrase in the world of business analytics. However, it is a key area nevertheless and we expect to watch it grow in the years to come. Mark our words, you heard it here first! #OperationalAnalytics #InsightsAnalytics