How Can Businesses Best Leverage Data scrubbing?
The hype around data is hardly news. It is a critical part of a business and rightly so. It is the ultimate competitive differentiator and referred to as the new oil of the world that of course, can’t be used raw and needs to undergo various processes of refinement such as data scrubbing, cleansing, and modification.

Data Scrubbing, Data Cleaning, Data Cleansing, Data Processing, Data Validation, Data Management, Data
Poor quality data remains the major challenge, and as per the Data Quality Market Survey, 2017 report by Gartner, poor data costs businesses approximately $15 million yearly. However, it is not a direct financial loss but several indirect and discrete impacts on business processes causing the dent on the business value such as loss in reputation. A higher-risk decision due to poor quality of data and missed opportunities- hitting the businesses where it hurts most. Poor data not only means financial impact but also results in an overall lack of brand value. It is the Achilles’ heel that makes even the massive organizations crumbling down to their knees.

Eighty-four percent of CEOs are concerned that the data they are basing their decisions on might not be at par. Pitney Bowes in “The Data Differentiator: How Improving Data Quality Improves Business” explains that a company might be basing its decisions on poor data due to the volume of legacy data, silos within departments and difficulty in acquiring buy-ins from the executives. However, we also have companies and innovators like Amazon and Airbnb that are solely operating on the sheer power of good data. Which lets them know about their customers, needs, preferences, and challenges they face.

It also means a data deluge due to the massive cloud, mobile, and IoT data. As the companies assess data management infrastructure and want to make the most of big data. It is the mess that the bad data is creating and the most exhausting part they are dealing with. While companies have to deal with CRM data decaying at a rate of more than 30 percent, little do they know that CRM cleaning and scrubbing can boost their sales, reputation, and revenues!

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Why do businesses need data scrubbing?
Successful data-driven organizations have a competitive advantage over the messy ones. Poor data is the culprit that doesn’t let businesses reach up to their true potential and reduces them to a dog chasing its tail.

More than twenty percent of revenue is lost because of bad quality data.
Over forty percent of companies are dealing with messy data plaguing their systems across BI, marketing and CRM and eventually hampering their growth.
Only sixteen percent of businesses acknowledge that their data is accurate and secure.
When data isn’t clean and is used for Business Intelligence and analytics. It is like mixing Nitrogen and Hydrogen with ignitable liquids. It is just a ticking time bomb waiting to corrode and combust. A business process running on low-quality data puts an entire business at stake. It is a domino effect that results in poor insights and poor results. That can be fatal and irreversible for a business.

Neil Patel explains how every organization has created a mountain of data that is difficult to navigate through. In a rush to achieve this information overload, businesses forget to pay attention to the origin of data.

People change jobs, locations, e-mail IDs, phone numbers and job functions. When the information isn’t synced with the database, it results in bad data. Often businesses utilize a third-party database, which leads to duplication of incorrect data, flooding the system with wrong, outdated and incomplete data.

A lead generation company wastes 546 working hours of a sales rep every year due to bad data.

What is data scrubbing?
Data scrubbing is akin to a system cleanse, a detox that every business is in dire need of and should opt for. It is the most exhaustive and complex part of a business process- like a body system used to junk food resisting to the greens and liquid diet. But it is also very important.

Often confused with data cleaning, it is a process of eliminating incomplete, incorrect, inaccurate, out-of-date, duplicate and inconsistent data.

To keep your data spotless- the backbone of your business- implement Data scrubbing. It ensures stronger campaigns, increased quality leads and competitive advantage for a business along with stronger and more targeted marketing campaigns, enhanced customer satisfaction and higher ROI.

Data scrubbing services include
Data scrubbing services are semi-automated, automated and manual. The data can be customized following a business’ specific needs and challenges. The expert and seasoned data engineers work through the vast sets of data in the following phases:

Rectification of records:
An up-to-date customer database is the key priority of data scrubbing. Data scrubbing implement a range of tools, techniques, and methods to identify incomplete and inaccurate customer records and take appropriate action. It ensures proper communication with a targeted group of customers.

When businesses take services of different databases, chances of having similar information run higher. When a sales team sends information, e-mail or unsolicited content. The customers just hit ‘spam’ without giving it a second thought. Data scrubbing utilizes the verification and validation techniques to remove duplicate data. De-duplication ensures that only relevant information makes it to the database, and the rest of it is flagged out.

Data Appending
When the engineers find out key datasets to be missing, they verify and check the current information and complete the missing record. Digital footprints and offline attributes such as phone numbers, jobs, and locations are used.

Standardization of data
Several business processes use data in a different format. Some may use a standard title, or some may not. Some may want to categorize the data for specific parameters, whereas, for others, it could be a completely irrelevant criterion. Data scrubbing ensures a uniform pattern of the datasets across the business verticals for easier access and consistency. The entries are similar across the datasets.

Enhancement of data
The data is validated and verified for the information it contains. If needed, the engineers can also assign value to the datasets that can be used to generate insights. The data can be formatted in any format such as Excel, CSV, PDF or XML.

Difference between Data Scrubbing and Data Cleansing
The terms are used interchangeably. However, if you dive deeper into the technicalities:

Data scrubbing is an evolved and more technical process encompassing the merging, translating and filtering out the inconsistencies in data.

Data cleansing is referred to as the identification and elimination of inaccurate and incomplete records in a data set. It also includes the process of deleting and updating the ‘bad’ part of it.

…And that’s about it. Data cleansing and scrubbing go hand-in-hand. This is why it is better to ignore the minute technicalities and tackle the bad data, which is crippling your business.

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Best Data Scrubbing Practices for Businesses
Data scrubbing is complex, but it is an indispensable process. Properly scrubbed data ensures value-driven insights that can drive a business towards its unprecedented growth.

A 2017 report by Forrester established that a Fortune 1000 company could add more than $65 million in revenue to its annual net income with a ten percent increase in data quality! Who knew bringing in a whopping million is ‘this’ easy and doable!

It is ideal for taking data scrubbing as a journey, a continuous process to keep cleaning it up for the greater good. Good data has always been an elusive goal and organizations need to strive constantly for that. However, it can be managed and monitored regularly to ensure the database in their system remains accurate, consistent, complete and valid. If you want to know how to best leverage data scrubbing, read on!

Data should be standardized.
Data should be standardized and categorized at each entry point. Whether a salutation needs to be followed, the serial numbers, postal codes, filters, location, job title, etc. –each parameter needs to be followed thoroughly. A uniform pattern of data across the vertical helps in setting a process that eventually leads to the sanitation of data. Log all changes, take the backup of both raw and scrubbed data as you make changes and label it.

Align your approach
Believe the experts when they say less is more! You don’t need junk data; you need crucial, concise and domain-specific data that can be useful for your business! Uber’s disruptive God-View Mode isn’t about big data. It is about how smartly they have put their data to use. If your data is accurate, complete and valid, the small data well, maybe, even bigger than the big data! It is time to let go! Don’t sit on the vast dead and obsolete data and instead, start asking the hard-hitting questions:

Do you have a data quality plan?
A data quality plan ensures the integrity and accuracy of data by analyzing and finding the root cause of the error. A plan also includes assigning the metrics and setting a contact point in every department to regulate and monitor the quality of data. You should be able to use and read each detail of the data to generate insights out of it. Unless you can do it, there is a scope of improvement.

Tools and Metrics for data accuracy
Does your business implement proper tools and techniques to measure the accuracy of data? If not, it is time to invest in data solutions right now. Alternatively, you can also outsource CRM cleaning and cleansing to a data solution company.

Training and Education.
Change is inevitable, and so does resistance towards it. Rather than pushing your ground and on-field staff to maintain data quality, it is better to educate and train them about the benefits of good-quality data. It is recommended to assign a contact point to help them with any query and question as well as to monitor the quality of data at each entry point.

Your need is specific.
What works for others may not work for you. It is better to assess and analyze why you need to harness the power of data. Hire a cleaning and scrubbing company to discover business-specific insights and data solutions. Knowing the goals and objectives that you want to attain via data will help to figure out the customizations, changes, and enhancement.

Validate and Verify.
Data cleaning is just an aspect of good-quality data. Scrubbed data should be enhanced with correct information and verified for accuracy. A quality review should be conducted regularly to discover any anomaly in the system while there is still time.

Author's Bio: 

Hir Infotech is a leading global outsourcing company with its core focus on offering web scraping, data extraction, lead generation, data scraping, Data Processing, Digital marketing, Web Research services and developing web crawler, web scraper, web spiders, harvester, bot crawlers, and aggregators’ softwares. Our team of dedicated and committed professionals is a unique combination of strategy, creativity, and technology.