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5 Ways Data Can Increase Operational Efficiency and Productivity in Economic Volatility
5 Ways Data Can Increase Operational Efficiency and Productivity in Economic Volatility

November 18, 2022

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On most econometric models, the probability of a recession has now increased from 30% to around 60%.

The sense of an approaching catastrophe in the market is forcing businesses to take hasty, imprudent actions. Spending is cut too far, new initiatives are put on hold, and staff members are abruptly fired. Business executives are worried about the unpredictable nature of the future while attempting to maneuver through a potential recession.

Data may reduce a portion of this tension.

When the economy struggles, an organization’s most precious asset provides actual value. To maintain business stability and beat the repercussions of the recession, businesses must focus on using data to improve operational efficiency and productivity instead of taking drastic measures. Using historical data to uncover trends and insights and analyzing current data to understand the ongoing market and customer behavior will ensure profitability and create a competitive edge.

Here are the top five ways how.

Improving processes and workflows

Using internal data to identify the tasks that are operating as they ought to and the tasks that squandered time and money is one technique to develop an effective workflow. Dynamic management of processes can be achieved at all business levels, and tasks based on performance can be initiated automatically using data analytics. By assisting managers in evaluating the efficacy of current workflows, examining the results of the processes, automating new workflows, and continuously improving them, data analysis contributes to better company management. Data also enables leaders to assess whether any processes are cumbersome, expensive, or difficult to use and helps them speed up their digital initiatives from difficult/error-prone manual workflows to optimized/automated procedures.

Reducing waste and inefficiency

Operational efficiency and productivity are something that every company strives for. After all, who wouldn’t want their employees to work smarter, not harder? One way that companies are beginning to achieve this goal is by taking a data-driven approach. By analyzing the data generated by their business operations, companies can identify areas where there is room for improvement. This could be anything from finding ways to reduce waste and inefficiency to increasing communication and collaboration between departments. Businesses, for instance, can learn more about their data by using content and context analysis. This data can be further categorized as cold and hot, ROT, dark data, and sensitive data based on the knowledge incurred about the data. Businesses can optimize their data storage processes based on the kind of data by putting cold data in inexpensive object storage. Additionally, enterprises can reduce redundancies and duplication by consolidating multiple data lakes into one centralized data ocean.

Increasing transparency and communication

Enterprises can save time, uncover more insights, and make better decisions by rethinking how organizations distribute and consume data. They can democratize data by making it accessible to all users-both technical and non-technical-in order to gain a 360° view of

their customers, foster innovation, enable seamless hybrid working, and improve customer

experience. Communicating insights and sharing them across different departments for better decision-making will help achieve effective data interoperability, democratization, and literacy.

Ensuring accuracy and quality

Monitoring processes and tracking KPIs in real time can help enterprises improve process accuracy and quality. As a result, deviations from the norm can be identified and addressed quickly to maintain quality. Data helps to track process metrics, identify trends, spot gaps quickly, and take steps to rectify them. Additionally, analysis of historical data can reveal patterns or trends that may indicate future challenges, as well as remediation measures that have proven to be successful. Consistently implementing all of these steps help increase quality, efficiency, and productivity.

Tracking progress and productivity

Data can also be used to assess the results of different productivity initiatives and determine the most effective ones. Using this feedback, existing programs can be refined or adjusted, and new ones can be designed to increase productivity even further. In addition, data can be used to track employee performance, identify areas where they may need additional training or support, and initiate training programs accordingly. Data can help enterprises boost operational productivity as well as upskill employees.


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