DataList Blog

Three Signs that You're Using Bad Data

Written by DataList Team | Sep 7, 2022 10:15:00 PM

In 2021, Gartner found that using bad data costs organizations an average $15 million USD every year. This means that the impact of bad data on your company could be significant, including anything from business inefficiencies and missed opportunities to poor decision-making and lost revenue.

We know that good data needs to be consistent, complete and correct, but how do you recognise bad data? Given that the results of bad data are not always immediately apparent, here are three warning signs that should function as red flags. 

Ineffective business processes

A recent 2022 CRM Report found that relying on manual processes for cleaning and checking data is fraught with problems. Not least is that as your database continues to grow on a daily basis, the ability of employees to keep on top of this amount of data becomes impossible.

Another problem found in this study was that database improvements were entrusted to inexperienced employees. In fact, 23% of companies were found to leave data entry and database improvements to temporary, casual or junior members of staff. These results might be understandable, given that the overwhelming conclusion of this study was that many companies assume that their data is clean and ready for use. 

So if you’re still relying on manual processes and junior staff to improve, manage or maintain your CRM, then it’s likely your data is not clean and not ready to be used in a meaningful way.

Reliance on third party data

If you decide to purchase third party data then your biggest problem is going to be its reliability. This is made even worse if you procure data from multiple providers and need to collate and merge all of this data into one database. 

This can be an expensive undertaking not only in purchasing  the data, but in the time spent by your sales team to verify the information and decide what’s missing, incorrect, out of date or duplicated.

Lack of maintenance on data quality

If you need to maintain your own database, whether it’s in-house data or procured from a third party, a lack of adequate maintenance can have serious consequences. Without at least one employee dedicated to maintaining your CRM, it’s quality and relevance will deteriorate, resulting in data decay. This is the gradual loss of data within the CRM, often due to buying B2B data from unreliable sources, but can also be due to lack of maintenance and aging of the contact data over time. 

It also needs to be considered that due to COVID and remote working, many contact details will no longer be relevant – if your data is not kept strictly up-to-date.

Combating bad data

There are three strategies you can implement today to combat bad data. First, you need to understand your data – is it up-to-date? How often is it maintained? Who is responsible for this maintenance? 

Second, if you don’t have processes in place to manage your CRM, then these need to be implemented ASAP (for example, who can enter data and how). Third, if you’re going to manage your own database then you need to implement good data governance (data security, quality, integration, preservation and usability).

An easier solution is to use a data research team who can supply you with custom built B2B data that’s guaranteed to be 99% accurate.