Technology and Data Analytics Boost Operational Efficiency

Technology and Data Analytics Boost Operational Efficiency

Once your business is off and running, you are likely spending your time attempting to improve your company’s operational efficiency. What is operational efficiency, you ask? This concept means maximizing your desired business output whatever that may be, reports the CIO UK publication. Usually, this entails keeping costs down or streamlining the time it takes to accomplish projects as well as the time it takes to finish product development.

Yet, research shows that using operational efficiency to keep costs low tends to fail in the long term. For example, one study from PwC found that less than 30 percent of programs aimed at reducing costs actually hit their target while less than 20 percent obtained a long-term reward over a three-year time period.

As such, operational efficiency will need to involve factors such as streamlining processes, feedback from team members, technological innovation, and utilizing metrics. Continually enhancing these types of processes can lead to better operational efficiency and will keep a company geared toward innovation.

Improving processes, measuring data and success, engaging workers and receiving feedback from employees, and taking part in technological transformations are all considered key parts of operational efficiency. Strengthening productivity is becoming more and more important in running a successful and competitive business. Below we outline four ways to boost productivity known as Operations 4.0 or Ops 4.0.

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Operations 4.0: Four Methods to Streamline Productivity

There are four specific ways to improve productivity including (1) product driven processes, (2) the cost and budget driven process, (3) journey driven methods, and (4) manufacturing driven factors, according to a McKinsey & Company article.

The product driven process involves developing and launching products by effectively utilizing advanced analytics and design to value methodology. Cost and budget driven measures relate to using more complex analytics techniques to make zero-based budgeting a reality. This method ensures that zero-based budgeting becomes more profitable than ever before and becomes more flexible and realistic as well.

The journey driven process includes end-to-end digitization and robotics or intelligent process automation, which can make changes to customers’ journeys occur more quickly and easily. In fact, these technologies could make a bigger impact on the journey and lead to greater sustainability.

Lastly, the manufacturing driven process utilizes big data along with throughput and yield analytics to greatly improve resource productivity. Essentially, the manufacturing driven method connects all of the available data sources with machines and process technologies to boost operational efficiency and productivity.

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The Fourth Industrial Revolution Targets Operational Efficiency

Currently, the business world is undergoing the fourth industrial revolution, according to McKinsey & Company. This industrial revolution involves digital analytics that greatly boost productivity by creating a variety of new opportunities for businesses to take advantage of.

Essentially, companies can now accelerate the length of time it takes to complete certain projects and make changes much more quickly. In addition, less resources are used when making certain transformations due to higher levels of operational efficiency.

Companies are forecasting and predicting results with greater precision using big data analytics, which allows them to more accurately plan out their future steps in growing their business. Furthermore, greater engagement among team members stimulates more productivity as well.

There are a variety of new technological advancements that are a part of the fourth industrial revolution such as 3-D printing, robotics, and artificial intelligence. However, one of the most important aspects for the business world that occurred during this industrial revolution is the blossoming of data analytics for use in driving productivity and efficiency of new business models. Higher levels of data and greater computing power has also come into play in recent decades.

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Incorporating Data Analytics for Constant Evaluation of Business Metrics

If you are seeking to ensure continuous improvement at your company especially in terms of operational efficiency, you will need to incorporate some vital business metrics in your data analytics processes. This includes first pass yield and rolled throughput yield metrics. The first pass yield metric involves the number of units that comes out of a process divided by the amount of units that go into a process over a certain amount of time. Rolled throughput yield, on the other hand, involves a probability that determines whether a process with two or more steps will lead to a defect free unit, which means this is essentially the product of yields in each step of the process.

According to Forbes, there are multiple business metrics that a growing company will need to keep track of in terms of data analytics such as sales revenue, operating productivity, the size of their gross margin, customer retention, cost of customer acquisition, and monthly profit.

Sales revenue data should be regularly mined to determine any trends and the meanings behind certain results. Business leaders will need to understand the impact of seasonal changes, product launches, advertising campaigns, and price increases or decreases. The more specific metrics to keep track of include the asset turnover ratio, the return on assets, and the return on sales.

Determining operating productivity is key since high levels of staff satisfaction and operational efficiency are excellent assets to your company. Productivity ratios can be applied to nearly any part of running a business including customer support, marketing, and manufacturing.

When calculating the size of the gross margin, subtract the cost of products sold from the total sales revenue and then divide by the total sales revenue before expressing the value as a percentage. When attempting to determine customer retention and loyalty, you may need to use purchase analysis, customer surveys, or immediate feedback during a purchase.

In addition, the customer acquisition cost can be found by considering the total costs of marketing, sales, and other services needed to acquire a new customer. Lastly, the monthly profit can be calculated by looking at fixed costs as well as variable costs of operation paid every month. More than anything, it is important to realize that analyzing your business metrics can streamline your operational efficiency.

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How Data Analytics Could Streamline and Improve Operational Efficiency

The CIO UK publication outlines that identifying operational constraints is vital for improving efficiency, which can be determined with the help of data analytics. Once these constraints have been identified, solutions can be created to improve processes and operational efficiency. In order to streamline operational efficiency, strengthening cross-departmental exchange is recommended since divisions between departments have been known to slow down operations.

Additionally, measuring business metrics and all company goals is an important part of streamlining operational efficiency. For example, business leaders will need to develop targets for metrics such as website traffic, sales, and customer satisfaction. In order to effectively complete these tasks, managers and executives will need to incorporate business analytics tools to analyze data and help them make the right business decisions.

“We recognized that while we had lots of data, we weren’t monetizing it as effectively as we should, so I recruited a new role of ‘Data Revenue Director’ to work with the commercial teams,” News UK CTO Christina Scott explained to the news source how her company took advantage of data analytics to reach their business goals and improve operational efficiency.

The McKinsey & Company article discusses how new analytics tools including computer-aided design technology linked to procurement data, price benchmarks, and social media data can help businesses determine ways to boost profits while reducing wasted time and effort. Essentially, this means these tools can help your company improve operational efficiency.

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New Technologies Reduce Waste and Boost Efficiency

Along with data analytics tools, the business world is being revolutionized due to new technologies that streamline production and manufacturing along with many other practices such as marketing campaigns, sales, customer service, and more.

3D-printing has transformed manufacturing while Internet-linked sensors and the addition of Internet of Things applications provide workers with greater control over complex processes than ever before.

If you’re looking for a sure-fire way to improve operational efficiency at your company, you will greatly benefit from incorporating useful project management solutions including time tracking tools that allow virtual teams to budget their time and meet deadlines.

Runrun.it software systems provide the dashboards you will need to track projects and documents in a user-friendly and simple manner. The dashboards incorporate automated templates that will make it easy for virtual teams to communicate and complete tasks.

When looking to reduce waste and enhance operational efficiency, time tracking tools will help you achieve your goals by allowing you to better manage your time. With the right project management solutions, you will know what projects are delayed, the hours spent working on particular tasks, and how to better streamline work tasks.

This software tool could be an important asset for you to boost productivity at your company. To find out whether this project management software system is right for your company, click here for a free trial.

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