Data Cleansing Vital for Improved Productivity and Efficiency

Data Cleansing Vital for Improved Productivity and Efficiency A reliable data cleansing service provider ensures that all data is cleansed, valid and accurate. Having a clean database also makes it easy to identify inactive or unresponsive customers.

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What makes data cleansing services so important for organizations? Data is one of the most valuable business assets. Most organizations face the challenge of maintaining their evergrowing customer data. An updated database containing accurate data is necessary to ensure effective contact with customers as well as maintain compliance standards. Quality of data has a great influence on the effectiveness of marketing campaigns and data quality can be improved by data cleansing. Data cleansing involves the process of maintaining consistent and clean data by identifying and removing unclean or inaccurate data.

Incomplete, outdated, wrongly formatted, and incorrect data falls under the category of unclean data. A clean customer database means there will be only one accurate record for each customer that contains all their details. Clean data ensures increased productivity, improved decision making, increased revenue and streamlined business practices. Regular data cleansing will help avoid a scenario where you encounter low response rates and your marketing campaigns are not proving cost-effective.

Organizations are capturing more data than ever using new sensors, IoT devices and SaaS solutions. According to a report by IBM, 90 percent of the data in the world has been collected in the past two years and the business and consumers now generate 2.5 quintillion bytes each day. Though millions of dollars are invested in new data technologies, many organizations do not evaluate the integrity of that data and how it is used. Are businesses effectively obtaining valuable insights from such data and acting upon it? Probably, no.

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Organizations in the supply chain could be operating in isolation, divided by departments and regions.

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There may be multiple procurement teams around the globe, with each team tracking the same supplier with possible variations of names without knowing that their other teams are interacting with the same supplier.

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There may be old ERP systems that don’t fully account for what goes on in other sections of the network such as stores, distribution centres, and shopping locations.

If polluted data or inaccurate data is fed into the system, retailers would experience a mismatch between what has been sold, what should be there, and what is actually there.

Bad data includes irrelevant, duplicate and outdated data. Customer data is in a state of flux and could become outdated quickly.

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Moreover, businesses may have multiple databases based on diverse criteria such as purchase history, prospect list, email list and so on. The same customer may be present on multiple databases with data bits under each criterion.

Clean data can not only ensure enhanced productivity but also boost customer satisfaction, produce better on-time fulfillment and optimal shelf stocking rates and bring many positive benefits throughout the organization. Improving data standards and practices can make data more actionable and evaluating data collection and processes can also help make more sense of it. But many companies do not properly format data with keywords or associated tags to truly turn it into actionable insight. That data still needs to be converted into formats that both machines and people can understand.

Cleaning of data begins with asking what problems need to be solved and what the data is being used for. Once that end use is identified, then the organization can determine the right data to collect and the format in which to process it. Organizations should create high standards and procedures for entering information into the system. They should have strategies around how they want to govern and manage the data and create a long-term view of the purpose they want that data for. Focus on the data you see on a day-to-day basis for key performance indicators and decision making.

Organizations must become

more collectively disciplined in collecting the right data, storing it and cleaning it at the right time and at the right place.

Tips to Clean the Existing Data:  De-duplication of data: Matching, margining and purging the existing data will ensure that there is no duplication of data.  Standardization and normalization of data: Standardizing and normalizing data will ensure the consistency of data throughout the database  Verification and validation of data: Verifying the records and matching them against up-to-date sources of information to validate the details and ensure accuracy  Update data: Identifying missing details and updating the information is important to ensure that the data is reliable.

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In a competitive world, organizations have to constantly update their database to maintain integrity, validity and add value to their ongoing business processes. An established data cleansing service provider ensures that all data is cleansed, valid and accurate. Having a clean database also makes it easy to identify inactive or unresponsive customers. Data cleansing can help business enterprises to achieve business goals with ease. It not only saves time and money but also ensures that the enterprise achieves overall operational efficiency.

www.managedoutsource.com

8006702809