The Long-term Costs of Data Debt: How Inaccurate, Incomplete, and Outdated Information Can Harm Your Business

The Long-term Costs of Data Debt

It’s no secret that many of today’s enterprises are experiencing an extreme state of data overload. With the rapid adoption of new technologies to accommodate pandemic-induced shifts like remote work and changing customer expectations, incoming data is flooding businesses.

Due to this information overload, it can be challenging for a business to take the time to hone in and discern what information may be relevant and what may be inaccurate, outdated, or incomplete. Unfortunately, outdated, incomplete, and inaccurate data can accumulate and result in detrimental ramifications to a business. Such data can harm an organization’s approach to internal operations, financial decisions, customer service, partner relationships, and more. It can be especially harmful to those who use ServiceNow, a cloud-based workflow automation platform.

Before the pandemic, the cost of bad data was estimated to be an astounding 15% to 25% of revenue for companies. With the rapid use of new technologies since then, the cost of outdated, inaccurate, and incomplete data is likely to have grown.

Data Debt

Another way to view the culmination of irrelevant information is through the concept “data debt.” The idea of data debt is that the piling up of outdated, inaccurate, and incomplete data will result in long-term negative consequences to a business. Data debt is counterproductive to the overall growth of an organization. It is an issue that will accumulate over time and stay with the company until remedied, similar to other types of debt.

Data Bed.png

Data debt can be categorized into three different types – incomplete, outdated, and inaccurate. Incomplete data is information that is missing critical information. Old data is information that is no longer current and needs to be updated internally. An example of this could be outdated internal records. Lastly, inaccurate data does not enable a business or an IT team to have a holistic view of a process or workflow. Instead, it has holes and inconsistent metrics, preventing a company from making accurate forecasts or predictions.

There can be benefits to experiencing a surplus of incoming data. An increase in data can help businesses make more informed and strategic decisions. It can provide insight into how successful a new product is doing in comparison to older models. However, when a business is plagued with outdated, inaccurate, and incomplete data or “data debt,” internal decisions or insights are no longer founded on the correct information.

Outdated, Inaccurate, and Incomplete data

Data debt can lead to a business making incorrect decisions in areas like hiring talent, forecasting sales, developing department budgets, monitoring the success of a product, responding to customer feedback, and much more. Data debt creeps into every aspect of a business and impacts its bottom line.

The good news is that there has been an increased industry awareness of the costs of outdated, inaccurate, and incomplete data. And with that heightened awareness, IT teams have learned of ways to address and resolve data inconsistencies. Outlined below are best practices on preventing data debt from occurring in the first place and how to resolve information inconsistencies.

  • Consistently update records as soon the new info is available. Some of the best ways to eliminate inconsistencies are to set solid and explicit processes. One of those critical processes is ensuring that IT continually updates records as soon as new information arrives. It’s also good to have internal notifications set to remind IT staff to check in on how current the data is and if it needs to be updated.
  • Develop a data warehouse strategy and take snapshots over time. Inaccurate data can be remedied by data warehousing. Once a data warehouse strategy is in place, it’s essential that IT staff take snapshots of that data over time to store in the data warehouse. Taking snapshots of information and then storing those in a data warehouse enables IT staff to get a comprehensive picture. It allows IT staff to be able to analyze the trends and find any anomalies. Similar to data warehousing, taking snapshots over time is also incredibly effective for inaccurate data.
  • Frequently sync technology. The process of regularly syncing technology is critical for identifying and solving data inconsistencies. To do this, there is a process of either “pulling” the data from where it currently lives or “pushing” the data from inside. “Pulling” is widely used in the industry, but it requires giving outside individuals permission to access data (i.e., the username, log-in info, etc.) This can expose data to inaccurate modifications, deletion, and other detrimental changes. Push technology, however, is a newer technique. It has more protection protocols and is a much more secure way to snapshot and data warehouse internal information in near real-time.
  • Collect and analyze data across multiple applications or workflows to cross-check. IT teams should use various applications or workflows when monitoring and updating data to help cross-reference one another. Using various applications, instead of just one, to scan data and ensure its relevant creates more barriers and makes it is less likely for inaccurate, outdated, or incomplete data to slip past.

The inflow of data is not going away. In fact, it will only significantly increase in the future. According to analyst firm IDC, the amount of data created over the next few years will be more than all the data created over the past 30 years. With businesses already overwhelmed with the current influx of information, it’s imperative to be proactive now and set solid processes to manage and resolve data inconsistencies. Implementing reliable tracking, ensuring consistent snapshotting, and continuously syncing technology are a few ways enterprises and IT professionals can avoid data debt.

By David Loo

Dr. Mike Lloyd

How to Mitigate Security Risks in the Cloud

How to Mitigate Security Risks in the Cloud Enterprises continue to spend billions annually on security technology, yet cyber breaches continue to come fast and furious. So what exactly is going on here? Why are ...
Derrek Schutman

Implementing Digital Capabilities Successfully to Boost NPS and Maximize Value Realization

Implementing Digital Capabilities Successfully Building robust digital capabilities can deliver huge benefits to Digital Service Providers (DSPs). A recent TMForum survey shows that building digital capabilities (including digitization of customer experience and operations), is the ...
Jim Fagan

The Geopolitics of Subsea Connectivity

Subsea Connectivity Digital transformation and the migration of data and applications to the cloud is a global phenomenon. While we may like to think that the cloud knows no borders, the reality is that geopolitics ...
Marcus Schmidt

What IT Leaders Should Know About Microsoft’s Operator Connect

Microsoft’s Operator Connect Earlier this year, Microsoft announced a new calling service for Microsoft Teams (Teams) users called Operator Connect. IT leaders justifiably want to know how Operator Connect is different from Microsoft’s existing PSTN ...
Derrek Schutman

Providing Robust Digital Capabilities by Building a Digital Enablement Layer

Building a Digital Enablement Layer Most Digital Service Providers (DSPs) aim to provide digital capabilities to customers but struggle to transform with legacy O/BSS systems. According to McKinsey research, 70% of digital transformation projects don’t ...


The CloudTweaks technology lists will include updated resources to leading services from around the globe. Examples include leading IT Monitoring Services, Bootcamps, VPNs, CDNs, Reseller Programs and much more...

  • Opsview


    Opsview is a global privately held IT Systems Management software company whose core product, Opsview Enterprise was released in 2009. The company has offices in the UK and USA, boasting some 35,000 corporate clients. Their prominent clients include Cisco, MIT, Allianz, NewVoiceMedia, Active Network, and University of Surrey.

  • Nagios


    Nagios is one of the leading vendors of IT monitoring and management tools offering cloud monitoring capabilities for AWS, EC2 (Elastic Compute Cloud) and S3 (Simple Storage Service). Their products include infrastructure, server, and network monitoring solutions like Nagios XI, Nagios Log Server, and Nagios Network Analyzer.

  • Datadog


    DataDog is a startup based out of New York which secured $31 Million in series C funding. They are quickly making a name for themselves and have a truly impressive client list with the likes of Adobe, Salesforce, HP, Facebook and many others.

  • Sematext Logo


    Sematext bridges the gap between performance monitoring, real user monitoring, transaction tracing, and logs. Sematext all-in-one monitoring platform gives businesses full-stack visibility by exposing logs, metrics, and traces through a single Cloud or On-Premise solution. Sematext helps smart DevOps teams move faster.