Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    New Data Analytics Breakthroughs Give eCommerce Startups a Fighting Chance
    New Data Analytics Breakthroughs Give eCommerce Startups a Fighting Chance
    6 Min Read
    How Data Analytics Is Reshaping Patient Financing Decisions
    How Data Analytics Is Reshaping Patient Financing Decisions
    13 Min Read
    business using business intelligence
    How to Use a Competitive Intelligence Dashboard to Turn Market Data Into Smarter Marketing Decisions 
    9 Min Read
    unusual trading activity
    Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
    3 Min Read
    software developer using ai
    How Data Analytics Helps Developers Deliver Better Tech Services
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Why Does Data Decay so Fast?
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > Why Does Data Decay so Fast?
Big DataData MiningData Quality

Why Does Data Decay so Fast?

martindoyle
martindoyle
6 Min Read
SHARE

People change jobs, get promoted and move home. Companies go out of business, expand and relocate.  Every one of these changes contributes to data decay. It’s been said that business databases degrade by around 30% per year, but why?

Contents
    • What is data decay?
  • Why does data decay so quickly?

People change jobs, get promoted and move home. Companies go out of business, expand and relocate.  Every one of these changes contributes to data decay. It’s been said that business databases degrade by around 30% per year, but why?

A report by IDG states that companies with effective data grow 35% faster year-on-year. However, for this to happen your data needs to have a high level of accuracy, consistency, and completeness. Yet for many businesses, data quality is seen as an abstract concept – let’s examine why…

More Read

Getting business value from data? Commercial analytics is where it’s at
Collaboration Is Vital to Success [VIDEO]
Be Wary of the Science of Hiring
Architecting Big Data Solutions
Data Science Journey Walkthrough – From Beginner to Expert

What is data decay?

Data decay refers to the gradual loss of data quality within a system, including key company information, personal details and most importantly, accurate contact information. As a result, the data becomes outdated and often invalid.

Why does data decay so quickly?

The world is constantly changing and sadly data is not immune to that change. From the moment you capture information, your data is at the mercy of processes and systems, as well as a number of human factors:

Disparate systems 
Collecting data across multiple systems can often lead to inaccuracies, including typos, incomplete information or duplicate records.

If you integrate your systems without a cleansing exercise you are only bringing across your “dirty data”. As a result, the new software becomes the old one, posing the same set of data challenges as it did before the integration.

Lack of data quality standards
If your employees don’t use the system as intended, and instead collect information in different formats or use different field types, your business decisions will be misinformed.

Over time, your database will become clogged up by old and inaccurate records. Your employees will struggle to figure out which records are too old to be trusted, which in turn impacts productivity and customer service levels.

Constant change
In the UK, there are around 63.2 million people living in 26.4 million households. According to Experian, every day in the UK 1,600 people die, 18,000 move house and 1800 register with the Mailing Preference Service (MPS). This shows just how much the world around us changing, as some people may marry, move house, change jobs and have a child within the space of a couple of years.

In the B2B market, there is a whole new set of challenges. According to Federation of Small Businesses (FSB), there were 5.5M SME’s at the start of 2016. Some of these companies will cease trading, move premises, change ownership, merge with other companies and change what their core business does, and there will be change almost every day. See our infographic to understand the life of your data.

The consequences of data decay

Financial impact
Each year, UK businesses waste £220 million sending mail to the wrong people. Phone calls are made to contacts that are no longer with the company, which wastes time and manpower.

Business reputation
Sending mail to a deceased person can cause distress to family members and colleagues, impacting on business reputation and customer retention rates.

Compliance issues 
Under Direct Marketing Association guidelines, you have to maintain and protect your customer database. For example, it is illegal to contact customers registered with the Telephone Preference Service.

The next steps
According to the research by Royal Mail Data Services, over 60% of UK businesses report they have out-of-date or incomplete customer information. These findings are confounding considering the importance of data for a business to remain competitive.

What can you do about it?

Implement data quality standards 
To ensure that your system contains good quality data, you should define what data can help you understand your customers and identify the best way to record it, ensuring it is accessible and easy to report on.

Invest in the right tools
Data Cleansing Software will automatically identify matches, ensuring data is free of duplicates and correctly formatted at the point of entry.

Consider automation 
Integrating disparate applications can solve your data quality problems. This should be combined with a thorough cleansing exercise, as well as appropriate training for your workforce on how to use the new system effectively.

Let everyone see the value 
Lethargy is endemic, therefore you should make sure everyone sees the value of keeping accurate records. This should be combined with clear data quality practices that are easy to follow.

Outsource data cleansing
Outsourcing to a third party can save time and will allow you to focus on what matters the most – your business!

Data is the lifeblood of your business – the blood represents the data, the organs are the departments and the brain makes decisions, sadly this is often with poor quality data. As many businesses still struggle to obtain valuable insights to fuel business decisions, be sure to follow our advice to improve data quality, ensuring you never have to face the same problems again.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Why Every Small Business Should Care About an AI Image Generator
Why Every Small Business Should Care About an AI Image Generator
Artificial Intelligence Exclusive
ai for instagram reel marketing
How AI Is Changing Instagram Reel Marketing
Artificial Intelligence Exclusive Marketing
protecting data in public
The Importance Of Protecting Sensitive Data In Public Services
Big Data Data Management Exclusive
New Data Analytics Breakthroughs Give eCommerce Startups a Fighting Chance
New Data Analytics Breakthroughs Give eCommerce Startups a Fighting Chance
Analytics Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

giveaway chatbots
Big DataChatbotsExclusive

How To Get An Award Winning Giveaway Bot

9 Min Read
Image
Big Data

Addressing 5 Objections to Big Data

7 Min Read

How to Evaluate the Effectiveness of Your IT Infrastructure

3 Min Read

The Singularity and Personalization through Data: Where We Are Now

8 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?