WHAT IS DATA DECAY
The word decay refers to when something decomposes, or is beginning to rot. Data decay is a phenomenon which occurs when an organisation’s quality of data deteriorates over time. It is data that has become outdated, inaccurate and no longer fit for purpose.
If an organisation fails to identify when their data has decayed and continues to use it without checking its accuracy, the repercussions can be significant for an organisation. There are many methods to repair data decay, and within this blog, we also describe its causes and consequences.
As we know data decays during its lifetime, it never remains 100% accurate and will require maintenance at various stages. Organisations must update their data frequently or else it can lose accuracy and relevancy after a week, month or after a few years of its capture and storage in your database.
79% of CRM users found that data decay has accelerated after the COVID pandemic. However it has always been a phenomenon businesses must deal with at some point.
If an organisation does not have data checking procedures in place, this can lead to inaccurate reporting, missed opportunities, wasted time and money and they may face the consequences of breaching GDPR laws which include significant fines. Studies have also found that 70% of CRM data is inaccurate by the end of each year.
CAUSES OF DATA DECAY
The first cause of data decay comes as a result of the natural change of personal information over time. For instance, an address line for a given person might change due to them relocating home from one address to another, people might change their job, phone number or even change their name. It is the duty of the organisation to ensure the personal information they store in their database remains as up to date and accurate as possible.
Another cause of data decay occurs in the collection stages of data capture. When data is input to a CRM system, human error can cause the degradation of information. For example a user may enter Av. Instead of Avenue in an address line, or misspell an email address when adding contact information, one might add extra or too few characters and any other human error when entering CRM data. These are basic, but common occurrences during data entry practices.
Duplication is another cause of data decay. Duplicated data occurs when the same piece of information is entered multiple times into a database.
Duplication might occur during data transfer processes between systems or departments, where another copy of data is made by mistake, or if more than one salesperson enters a customer’s details to their CRM system due to poor communication, it becomes a duplicate.
If a duplicated email address were added to the contact list of an email marketing campaign, they would receive more than one copy of the same email address. This would be classed as spam and lead to disgruntled recipients, affect your reputation and your reporting at the end of the campaign.
Duplicates appear either as a carbon copy, or partial duplicate of another record. A partial duplicate is when an address is entered in similar but different ways such as ‘Warrick Avenue’ and ‘Warwick Avenue’. However, with Hopewiser’s Deduplication Services you can ensure your database is enriched, optimised and cleansed of duplicate records.
Overall, data decay is caused by a lack of data governance within an organisation. This is when a business operates without clear ownership or responsibility for the management and assurance of data.
The same processes and tools should be used throughout an organisation’s department, to ensure data capture, storage and maintenance remains consistent and accurate, or else data will become unreliable and fragmented.
CONSEQUENCES OF DATA DECAY
The first consequence of data decay is the fact that you run the risk of breaching GDPR laws. Data decay impacts many of the key principles. For example, having duplicate records breaches the storage limitation law as duplicated data implies there are copies of the same record. Data decay also breaches the accuracy principle of GDPR. Businesses must keep information up to date and take action to ensure it is accurate. Breaching GDPR can lead to massive fines and reputational damage.
Data decay can be a burden to an organisation’s resources. It costs money and takes up storage to hold data so it is fundamental to optimise the data you hold and maintain cost effectiveness. Bad data costs businesses an average of $15 million annually. This is due to data analysts or CRM managers spending a large amount of time assessing, correcting, cleaning or removing bad data. Time which would be better spent carrying out other business matters.
If a business experiences data decay their reputation will be negatively influenced. For example when sending email campaigns or other targeted content to incorrect email addresses this will harm sender reputation, return on investment and lead to unreliable reporting.
Duplicate email addresses in a recipient list of an email campaign will be getting copies of the same email which will not reflect well on your business and make targets less likely to show interest in your email content, and less likely to read future correspondences. Decayed data also harms the relationships your organisation has with customers, for example if you send them irrelevant information that does not relate to them or they have no interest in.
CURING DATA DECAY
Businesses can form a single source of truth (SSOT) to ensure consistent and quality data. A SSOT is the process of bringing together the information in a business from multiple systems, into a single location so that it can be found at a single reference point. This saves organisations the struggle of keeping the same data in multiple areas which is hard to manage in terms of consistency and accuracy.
It is a best practice approach to data management which addresses the issues of poor data integration, which can lead to duplication and data decay. It can be a simple concept to understand and implement, and one with many benefits. If you think this method might suit your business, read more about it in this free guide about the single source of truth.
You may wish to reach out to customers personally in order to achieve data accuracy. A friendly reminder about the importance of accurate data is acceptable as it is common for organisations to ask their customers to complete their profile to ensure the information entered about them is as up to date as possible. It may be an effective strategy to reduce data decay and it also makes customers feel valued and important if they are contacted directly by a business.
HOW HOPEWISER CAN HELP YOUR DATA
Hopewiser’s solutions and services are backed by the most up-to-date sources of information to provide data validity and accuracy.
Address Validation prevents data decay by providing address accuracy at the point of entry and is designed to enable organisations to validate customer addresses and make empowered business decisions based on your enhanced data.
The software behind Address Validation verifies accurate postal addresses so deliveries are made to the correct location and is checked against multiple address databases and makes corrections to data where needed.
Hopewiser’s Data Cleansing service prevents data decay by cleansing addresses and highlighting discrepancies such as movers and deceased persons, allowing organisations to correct their data.
Data Cleansing is specifically tailored to help customers keep track of the changing circumstances that result in data decay. Hopewiser can provide powerful software which uses the latest tech and third party sources to ensure data hygiene and identify records that are matched duplicated goneaway deceased and suppressed using up-to-date UK databases.
You can also reach out to us and request a Data Audit where we assess the quality of your data. You can reduce the risks and costs of inaccurate and inconsistent data to help you support and manage the data part of your wider technical or marketing programs.
The Hopewiser assessment service identifies inconsistencies and duplicates by validating against an agreed set of criteria and using the highest quality dataset providers. The output report details data quality metrics and supports you in planning in both cleansing, deduplication and enriching data programs.
If you have any questions, get in touch on our Contact page
, updated 27th March 2024.
