The Hidden Costs of Bad Data & How You Can Eliminate Them

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Business success is complicated, but when it comes to data’s impact, it’s simple – good data leads to better business decisions, increased productivity, and happy customers. Bad data, on the other hand, does the opposite. In fact, according to Gartner, organizations found that bad data results in $15 million per year of losses.

Is your organization suffering from bad data and bad returns? Read below to discover why bad data is so costly for asset-intensive utility, government, telecommunications, and pipeline organizations, and learn how your organization can fix the problem.

The Hidden Costs: 

Labor Hours and Productivity in the Field

The origins of bad data are very humble. Manual and dual data entry creates opportunities for human error. And, unintegrated enterprise systems create siloed data, which leads to data disparities and errors between enterprise systems. Eventually, the evolution from those humble beginnings starts to critically threaten the productivity of your organization.  Whether the data is siloed, inaccurate, or nonexistent, bad data thwarts the productivity of teams throughout asset-intensive organizations.

Take one of our Utility customers, for example. Before integrating their asset and GIS data with Geonexus, the organization’s data was all over the place. Some data existed in the Asset Management system, some in the GIS system, some in individual employee spreadsheets, and some was never added into any system. These extreme data silos forced asset management crews to make extra site visits before performing maintenance to locate and assess assets – both tasks that should have been completed digitally from home-base. What’s more, the data silos also affected GIS team productivity, forcing GIS teams to create asset location maps for field crews whenever an asset wasn’t properly documented. All in all, these processes not only wasted labor hours, they also caused frequent slowdowns on work and maintenance.

Unhappy Customers

As evidenced above, bad data can cause maintenance and work order slowdowns. This not only affects the business bottom line, but also contributes to customer dissatisfaction. And, in public-facing organizations, like Utilities organizations, providing excellent service to the end-customer is the ultimate goal. Slower maintenance times might mean getting the power back hours past promised or creating billing errors on customer meters.

Bad Business Decisions

As Gartner noted above, bad data can result in real financial losses. In addition to lost labor hours, slower projects, and unhappy consumers, bad data also leads to bad business choices. And, it’s easy to see how in asset-intensive organizations.

For one, with inaccurate data on asset performance and labor hours needed to maintain assets, business leaders may over or underestimate maintenance costs for the year. That same inaccurate data can also lead to purchasing and hiring decisions that don’t reflect the actual needs of an organization.

Cut the Costs:

So, how can you fix the bad data derailing your organization?

Automate and Digitize Formerly Manual Data Processes

Manual data entry, or worse, paper data entry, creates vast opportunity for human error. Digitizing data storage eliminates the need for paper forms that are easily lost and misunderstood from team to team. Further, eliminating dual data entry reduces human error and gives time back to both GIS and Asset Management teams.

Integrate Enterprise Systems

In order to eliminate dual data entry between enterprise systems, organizations need to prioritize data and application integration. Integration eliminates data silos and ensures accurate, up-to-date data in both systems. Having connected systems eliminates the need for extra site visits to check asset location and removes the need for GIS teams to create additional asset location maps, increasing asset management productivity and keeping customers happy.

Prioritize Data Quality in Choosing an Integration Solution

Not all data and application integration solutions are made equal. Though custom-coded integrations and ETL methods used to be popular, without built-in reporting functionality, business leaders are left in the dark about data quality and accuracy. The Geonexus Integration Platform, on the hand, has built-in reporting functionality that reports data discrepancies, errors, updates, and changes each time data in synced between systems. Those reports are sent to users in XML or PDF formats for easy viewing and quick issue resolution, allowing a constant view of data quality between their enterprise systems.

Conclusion

Don’t let bad data derail your organization. Learn how Geonexus prioritizes data quality with our best-of-breed integration platform: https://geo-nexus.com/platform-demos/promoting-data-integrity-through-enterprise-system-integration/.