Data Quality Is Not Abstract; Companies with Effective Data Grow Faster
It is not only believed but now proved as well that business databases degrade by around 30% every year. People changing their jobs, getting promoted and shifting their locations, followed by companies going out of business, expanding their operations or relocating; are some of the major reasons responsible for this. Enlisted are the statistics that are interesting:
• 65.8% Job or title change
• 42.9% Phone number change
• 37.3% Email address change
• 34.2% Change of company name
• 29.6% Moved from one company to another
• 3.8% Change of name
To add to it, the saddest part is that a survey was conducted on the accuracy of contact information and gathered 1,025 data inputs from a variety of business people. It’s been years now but still, many businesses look at data quality as an abstract concept. These businesses do want to grow faster as against their competitors, but in no way are ready or equipped to adhere to a high level of accuracy, consistency, and completeness of data - which makes their data clean & effective.
The challenge we are referring to here is Data Decay. It is the gradual loss of data quality, such as key company information, personal details, and the most important is accurate contact information. This vice has the characteristic of making your data outdated and invalid. The world is evolving consistently, and data, unfortunately, is not at all resistant to these changes.
From the moment a data set is captured, it is at the mercy of processes and systems, and a number of human interventions including:
1. Distinct systems
Inaccuracies such as typos, incomplete information, and duplication of records are a result of collecting data across multiple systems. Integrating this data with your systems such as CRM and EPM, without data cleansing, you are bringing in “dirty data”, which certainly will prove costly in terms of accuracy, time and wasted efforts. All this will result in slowed down software and dissatisfied clients.
2. Non-adherence to data quality standards
If your business decisions are misinformed, there are chances that your employees are collecting and feeding information in different formats, using different field types, other than specified ones. This will ensure that your database reaches a clogged up stage due to inaccurate data records. This will also lead to a situation where your employees would be confused as to which records to trust and which are not to be – impacting their overall productivity and customer service levels.
3. Consequences of inconsistencies in your business data
Financial impact: Sending emails to wrong people, phone calls made to contacts that are no longer with the company, sending across season’s greetings to customers who are no longer in your network is a mere waste of time and manpower.
Business reputation: Supposedly due to incorrect information, an email is sent to a deceased person causing distress to family members and colleagues. This affects the business reputation and also impacts the customer retention rates – adversely.
Compliance issues: It is mandatory to maintain and protect customer database, it is illegal to call customers registered with Telephone Preference Service. Direct Marketing Association guidelines are of these opinions.
Businesses today, small or big, certainly have out-of-date of incomplete or inaccurate information. This is really confounding looking at the importance of effective data for any business to stay competitive & grow faster.
What is it that businesses need and how could they attain it?
The need of the hour for businesses is effective & clean data. Businesses should have data that assists them in creating better performing marketing campaigns, nurtures customer relationships, and is also compliant with relevant regulations.
To make the data more effective and clean; identifying and removing duplicate records is a must. Upon identifying the missing data it needs to be replaced with fresh details; for which web research or data mining is required. Data cleansing includes address data cleansing, adding missing details like first & last name, DOB, contact details, etc. This then is followed with spelling corrections, misaligned data, company movements and much more. The final step is data auditing and aggregation. All these put together and executed, can be said to be a data cleansing activity that would give businesses that required effective and clean data.
Conclusion
But in this dynamic economy, and frequent slowdowns in the market; can businesses afford to divert their costly manpower or resources to manage this, though very important, back office activity. The ultimate solution is to outsource data cleansing. Outsourcing the data cleansing activity to a third party service provider would not only save time – but also they have the expertise and eye for detail which certainly will work to the advantage of you and your business. It will allow you to focus on what matters the most for you and your business. Several businesses struggle to obtain valuable insights to fuel business decisions, for which they should certainly improve the data quality.
