What Does an Operations Analyst Do?

The dizzying speed of business digitization has transformed the way companies operate. Emerging data sources and technological advances have given organizations unparalleled insight into their daily operations and the ability to implement real-time changes in the very moment that problems arise.

With these improvements, the role of operations analytics has also erupted. While operations analytics is not a new discipline, the data to which we now have access has very much reshaped the role for the 21st-century.

But hold up a moment! What exactly is operational analytics, and what does it involve? In this post, we’ll find out, answering:

What is operational analytics?
What does an operations analyst do?
What’s the difference between an operations analyst and a business analyst?
How to become an operations analyst
How much do operations analysts make?
Key takeaways

Ready to get the low-down on operations analytics? Then let’s dive in.

1. What is operational analytics?

Operational analytics is a subset of data analytics that concerns itself with improving an organization’s processes and operational efficiency. It is particularly common in manufacturing, transport, and logistics. However, it has become increasingly industry-agnostic, as access to high-quality data becomes more widely available to all types of businesses. It’s sometimes referred to as operational research or industrial engineering.

The main difference between operational analytics and other forms of data analytics is that the former utilizes almost real-time data. Many forms of data analytics solely use historical data, for instance, to make financial projections or to identify patterns that might affect upcoming product launches (for example).

Meanwhile, operational analytics incorporates the constant, incoming data streams that have become widely available in recent years. This helps operations analysts make decisions at the point of need, in a way that would have been impossible ten—or even five—years ago. Due to this real-time nature of operations data, some refer to the field as continuous analytics.

2. What does an operations analyst do?

Just like all data analysts, operations analysts are primarily problem solvers. What distinguishes them from other types of analysts is the type of problem they tackle. Depending on the nature of their organization, an operations analyst’s responsibilities are varied. However, they usually include things like:

Operational policy-making
Supporting C-suite decision-making
Oversight of all IT and data activities
Logistics and resource management
Design and implementation of trading systems
Client reporting and dashboard development
Quality assurance and performance monitoring
Forecasting and risk management

Due to the complexity of the tasks involved, operations analysts usually work as part of a larger team. But don’t let the responsibility of the job intimidate you—ultimately, an operations analyst’s goal is the same as any other business analyst: to help businesses run more smoothly. If that’s something that interests you, you may be surprised by how motivating that can be for picking up the necessary skills. Speaking of which…

What skills does an operations analyst need?

Core skills that all operations analysts need include:

Applied math and statistics: Fundamental for analyzing and making sense of varied and complex sources.
Problem-solving and critical thinking: For gaining insights into data but also for identifying and devising solutions to real-world problems, as and when they arise.
Systems analysis: The ability to dissect, evaluate and improve processes/procedures, as well as IT and software systems.
Programming expertise: For supporting systems analysis, software implementations, and for building custom-built apps or algorithms.
Management skills: A basic grasp of core business management principles, such as strategic planning, resource timetabling, and leadership.
Financial expertise: Ability to collate and understand financial accounting data, and to contextualize insights against wider industry and economic practices.
Proficiency with data analytics tools: Familiarity with a variety of data analytics systems, tools, and processes, from Python and Excel to proprietary systems like SAP.
Transportation and logistics expertise: As big business in the manufacturing sector, you’ll need working knowledge of supply chain processes.
Stress tolerance: Operations analysis involves high pressure, real-time decision-making. You’ll have to maintain your cool and keep your judgment unclouded.

Because of the breadth of skills required for this job, most operations analysts have a bachelor’s degree and will start their career in another data analytics role, before progressing into operations analytics. There are such things as entry-level operations analyst jobs, but the best performers often have experience in other areas, which gives them an edge when they apply those skills to their new chosen field.

3. What’s the difference between an operations analyst and a business analyst?

By this point, you may be wondering what the difference is between operations analytics and business analytics (which, no doubt, you have also heard about). In a world where data is constantly evolving and finding new applications, this is a fair question.

Before we get into the differences, it helps to highlight similarities between operations and business analytics. These include:

Both roles are concerned with problems that impact the way a business runs.
Both focus on driving efficiency, improving systems/processes, and the bottom line.
Both feed into the C-suite’s strategic decision-making.

Meanwhile, the between the roles lies in what they prioritize. Let’s touch on this now.

Historic data vs. real-time data

The main difference between operational analytics and business analytics is the immediacy of the data they use.

Business analytics primarily relies on past data. This might include things like financial accounts, historical log files, market research insights, product or project documentation, press releases, product reviews, and so on. They use the insights gained from these data to inform future approaches to a variety of issues and to make predictions about the market landscape. In this respect, business analytics tends to deal more with longer-term planning.

Meanwhile, operations analysts primarily work with real-time data. It includes supply chain geodata, e-commerce data, server logs, and other data streaming from real-time sources like social media, ATMs, or customer service systems. Using this information, operations analysts can solve problems immediately when they arise. For instance, if a supply chain faces disruption, analysts will be alerted immediately and resolve the issue as quickly as possible. In this respect, operations analytics tend to deal with shorter-term planning.

Note: A knock-on effect of an operations analysts’ reliance on real-time data is the importance of maintaining the integrity of their data sources, storage capabilities, and quality assurance. While these things are fundamental to all forms of data analytics, they’re a particular focus for operations analysts, since these things have a very immediate impact on their work. So you will find that operations analysts are fastidious about organization!

Internal focus vs. external focus

Another difference between business analytics and operations analytics is their focus.

Business analytics tends to approach problems from a broad, market-level perspective. In this respect, they’ll usually look at external factors like competitor analysis and market research to inform their strategy (this remains true, even if that strategy affects internal systems and processes).

Meanwhile, operations analysts tend to focus more on the granular daily operations of how a business runs. While tweaking a project methodology or choosing a new IT system may involve using external data sources, the key here is that the problems they solve are generally more inward-facing.

4. How to become an operations analyst

If operations analytics sounds like a career you’d like to pursue, here are some key steps you’ll need to take to get started.

1. Get a bachelor’s degree

The first step towards landing an entry-level data analytics job is to get an undergraduate degree. In general, this is a prerequisite for any skilled job like operations analysis. Ideally, your bachelor’s will, therefore, be in a field broadly related to math, science, or computer technology.

But so long as you can supplement your degree with additional qualifications that highlight your data analysis, mathematics, and statistics skills (which are all fundamental to the role) many degrees are acceptable.

Finally, while not a concern at this stage, be aware that many operations analysts later specialize further as they climb the career ladder, possibly obtaining a master’s or even Ph.D. in a field like operations research.

2. Follow-up with a professional certification

If you already have a degree (that’s not in math or computer science) you’ll need a professional certification to evidence your data skills. This needn’t be in operations analysis, but you will need to show that you have a solid grasp of data analytics and the associated theory, tools, and processes.

Unfortunately, a free online course won’t cut it here (although they are good for cutting your teeth!) There are many certified online programs, though, offering excellent value for money. Plus, if you’re taking a sideways step from an existing role, your company may be willing to pay the fees as part of your continuing professional development.

3. Land yourself an entry-level data analytics job

Once you’re certified, the next step is to land yourself an entry-level data analytics job. If you’re lucky, you may land headfirst into an operations team. Chances are, however, that you’ll first need to prove your worth elsewhere in the business. This is not definite but it’s worth being prepared to work your way up.

Whatever job you land, gain whatever practical experience you can. Hone your core data analytics skills in areas like Python, Excel, and using various data analytical models.

4. Immerse yourself in all things operations related

Whatever role you’re in, grab any chance to obtain experience and immerse yourself in everything operations-related. What can you do to hone your programming skills? How can you learn more about transport and logistics? Manufacturing? Supply chain management and procurement? These are invaluable areas that you’ll need to explore.

It’s also worth looking to see what you can learn from outside the business. This list of operations research blogs is a fab place to get started. The Institute for Operations Research and the Management Sciences (snappy name!) also has a goldmine of free resources worth digging into. Furthermore, their academic program database lists globally recognized programs of study based in the US, should you choose to go down this route. From here, you should be ready to thrive in an operational analysis team.

5. How much do operations analysts make?

Considering the complexity of the role, it’s probably not a big surprise to learn that operations analysts—once established—can earn quite a comfortable living. In this section, we look at the average operations analyst salaries from the world’s top 10 largest economies (according to the World Bank) using data from the pay comparison site, Salary Expert:

United States: $65,017
China: $27,759 (or 176377 Yuan)
Japan: $52,244 (or 5,946,689 Yen)
Germany: $66,848 (or €58,469)
United Kingdom: $54,656 (or £39,912)
India: $8,516 (or 6,31,263 INR)
France: $55,872 (or €48,857)
Italy: $51,092 (or €44,690)
Canada: $57,474 (or $71,939 CAD)
South Korea: $38,353 (or 45,587,287 won)

It’s worth noting, despite variations in salary, that operations analysts are globally in demand. If you’re considering relocating, why not look at one of these countries to work in? With its specialist skills, operations analytics can be a great passport for exploring the world.

6. Key takeaways

There we have it: operations analytics in a nutshell! In this post, we’ve learned that:

Operational analytics is a subset of data analytics concerned with improving organizational processes and operational efficiency.
Operations analysts work with real-time data, mostly focusing on granular, internal-facing aspects of business operations.
An operational analyst’s responsibilities include operational policy-making, supporting C-suite decision-making, logistics, performance monitoring, and trading systems management.
Operational analysts require skills in math and statistics, critical thinking, systems analysis, programming, stress tolerance (for dealing with the demands of the job), and more.
Operations analysts are internationally sought after, something that their salaries reflect. An operations analyst in the U.S., for instance, can earn an average salary of around $65,000.

As businesses large and small obtain greater access to real-time data, the easier it becomes for them to utilize operational teams. If improving business efficiency and helping organizations run smoothly sounds like a job you’d be interested in, be sure to check out more.

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