Bad data is typically categorized as erroneous, duplicative, personal or sensitive in nature, but there's more to it than that. Bad data can also be defined as anything that is stored in an outdated or non-functional legacy software, kept for the purposes of record keeping. Whether it’s the nature of its contents or how it’s being stored, most organizations are increasingly faced with managing the complexities of bad data. What’s worse, the practice of retaining dirty data can cost organizations billions of dollars each year if they are in violation of information and data management policies and procedures.
It is often unclear whose job it is to properly manage all the data that exists in an organization. Most rely on their IT or records management departments to perform this function, but the reality is that it's everyone’s responsibility. Every employee plays a role in contributing to the data deluge that organizations are faced with and therefore are critical in addressing the problem successfully.
It is important to recognize why clean data improves the overall quality of it for everyone at your organization. Here are the top five reasons it's time to contribute to clean data efforts:
1. It increases productivity and lowers your operational risk.
Organizations are creating more and more information with emails, instant messaging, social media, images and video – and that list only continues to grow. The information is disorganized and difficult, if not impossible, to analyse, yet the data holds incredible value for IT analysts. IDC estimates that by 2020, 37 per cent of unstructured data will be useful if properly analysed, resulting in $430 billion in productivity gains for organizations if properly utilized. Properly-managed data improves your ability to locate documents when you need them.
2. It improves your capacity to leverage technology and uncover potential value.
We all know the phrase “keep it simple,” however the mantra can sometimes seem impossible to implement in the world of mass data volumes. The truth is, the simpler your data is classified, the easier it is to leverage technology around it. Once properly categorized, AI technology can give you an even more comprehensive understanding of your data, resolve data leaks of personal information, and uncover business insights and potential value in the costly dark data you are storing - and not using.
3. It mitigates your cybersecurity risk to help keep your brand protected.
Guarding your organization’s brand identity is crucial to remain competitive in any industry. Any breach of company data or personal customer information significantly decreases consumers’ trust in that organization which will impact its bottom line. In a 2018 study, IBM and the Ponemon Institute found that the average cost of a data breach is $3.86 million USD. Structuring your data mitigates the risk of a data breech and maintains your company’s brand reputation.
4. It improves data literacy amongst your stakeholders.
Imagine an organization where every department spoke their own unique language. That’s essentially how a data-driven business functions when there is no data literacy. If no one outside of the department understands what is being said, it doesn’t matter if data analysis offers immense business value and is a required component of any business in this digital age.
Even if an organization has a digital mindset, communicating business value to a global consumer can seem nearly impossible. In order to remain competitive, organizations must champion data literacy and provide awareness on data management best practices to all departments.
5. It allows you to rid yourself of ROT.
Cleansing bad data is not only in the best interest of your organization, but for your clients as well. The trouble with data is that it’s somewhat invisible. Many of us don’t know how to tackle the problem of data deluge. The legal industry especially faces the challenge of being told to “keep everything, just in case.” Meanwhile, IT and records management departments try to juggle competing priorities such as security, adhering to retention policies, all while acquiring and setting up more storage to support the ongoing flood of data being created.
With the onslaught of data breaches occurring today, organizations are putting an immediate focus on their data management strategies to address their Redundant, Obsolete, or Trivial (ROT) data. Organizations don’t want to wait until they are forced to look at their data and establish solutions on the fly that are costly, time consuming and and affect their organizational reputation. CEO’s and executives want to sleep better at night knowing that their organization’s data is well-managed, and the appropriate strategy and operational procedures are put in place from the outset.