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5 Ways Data Analysis Can Improve Tech Organizations

Today’s business landscape is increasingly dominated by those companies which have the best data practices and analytics capability.

Although every organization produces mountains of data every day, not all of them are equipped to truly take advantage of data analysis in a way that pays dividends. For some companies, data can have a more abstract feeling. Proxy metrics are less tangible than sales totalsor inventory figures, for example, but data analytics are vital, nonetheless.

Data Analysis Can Improve Tech Organizations

You may not be convinced that you need to heavily invest in data analysis tools for your tech company. However, you would be surprised at the many ways it can help optimize your workflows.

Here are five ways data analysis can improve your company.

You Can Identify and Remove Workflow Bottlenecks

Tech companies tend to work with complex projects that require significant input from multiple teams at different stages.

Moreover, work is never truly complete—updates must constantly be developed, tested and launched, and apps must be monitored and maintained. Especially in such a crowded market, keeping efficiency and a constant development cycle are vital.

However, it can be easy to get bogged down and lose an edge when links in the chain weaken. Data analytics can help monitor performance at every step and identify trouble areas as well as points where work is slowing down. In turn, you can make the necessary adjustments to keep your time to product at its peak.

It Empowers Team Members to Interact with Data

Data is valuable insofar as you can deploy it at the right time and to the right people. When you need special staff devoted to handling data or have systems that don’t prioritize speed and quality of delivery in place, you can lose much of the advantage. Executive leaders shouldn’t have to rely on specialists to run their queries.

Moreover, it limits your team’s access to vital information they need to make better decisions about project priorities, development tasks, and major bug fixes.

On the other hand, providing users the tools to access data on their own gives them the ability to make smarter choices and perform their own analysis as they need, instead of having to wait for reports that may include outdated data. More importantly, it permits them to act faster and perform better by using data-driven decision making.

You Can Improve Efficiency by Finding Processes That Work

For any organization, human capital is a vital asset for success. Your team is the engine driving development, but many times urgent needs, poor management, or inefficient task delegation can get in the way of reaching their full potential.

Using success metrics can help you understand your team’s work distribution, how long tasks are taking to complete, and how long each project is taking to reach a conclusion. More than just understanding these variables, however, data analysis lets you see how each is correlated, and mash up data with other streams to get a broader comprehension of your team’s performance.

This way, you can create the optimal conditions and the right environment for your team to thrive.

It Drives Smarter Decision-Making

One of the most important benefits data analysis gives you is the ability to make better decisions consistently.

Most companies still rely on “gut instincts,” despite the availability of data. This is not inherently bad, but it does mean that sometimes decisions are made without the full view of a situation and its variables. More concerningly, many organizations only use half of the available information when they make decisions. Using data analysis can help broaden your perspective quickly by tapping into real-time data and parsing it to provide actionable insights.

Instead of relying solely on intuition, adding a layer of data that can help reinforce or advise against a decision has significant value. First, you can react faster to situations by relying on predictive analytics, and second, you can keep ahead of trends by leveraging your existing data. Processes like data commercialisation help digest your data assets from campaigns to formulate a strategy that will help further increase your reach and revenue.

You Create More Efficient Feedback Loops

As a consumer-facing service, apps are constantly receiving feedback about performance, bugs, and other problems users may have. For most companies, sorting through this means manually examining bug reports and reading through potentially hundreds of comments.

This is not only time-consuming but ineffective, as it can lead to time-sensitive problems being missed.Deploying analytics can help you sort through feedback faster using machine learning and AI to sort through, prioritize, and alert you about feedback.

 This not only reduces the time spent by your team working on fixes, but also means that solutions are implemented faster and consumers are more satisfied with your app.

Data-Driven Is the Future

Data analysis is a vital component to any industry’s success, but tech companies can use it to great advantage. By implementing a culture that is reliant on data and can derive real insight from it, you can improve your tech company’s efficiency and develop a better experience for your users and employees alike.

After working as digital marketing consultant for 4 years Deepak decided to leave and start his own Business. To know more about Deepak, find him on Facebook, LinkedIn now.


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