Service Management Data Integration: A Guide

Service management data integration helps unsilo enterprise and customer data, granting service management professionals a comprehensive view of the right information.

Service-management requires consistent and accurate data. But this consistency is difficult to achieve when disparate tools lead to information silos – and the implications are huge.

Not having the right data available, among the right people, at the right time can undermine the integrity of an organizations data-driven decisions.

Gartner estimates that 97% of business decisions are based on data of unacceptable quality. Further reports indicate flawed data costs companies an astounding 20% of their revenue.

Two leading drivers of poor data quality are unintegrated shadow IT and siloed applications. 

A Symantec study showed that 1,516 cloud apps are in use by the average enterprise, but CIOs believe that only 30-40 cloud apps are in use by their enterprise. This means many unused apps could be generating useful data that is disconnected from the enterprise.  

Forbes Insights found that only 34% of executives have achieved a single view of the customer with aggregated customer data. In addition, 52% of executives say that their siloed apps impede a single view of the customer.

The lack of a holistic view of enterprise and customer data can severely impact an organization’s service management strategies and processes. 

The solution? Data integration.

What Is Data Integration?

Data integration means getting the right data from there to here—so that the data can ultimately be used to offer better service and inform business decisions.

Through better data integration, organizations can enable mass data synchronization between a service-management application (like ServiceNow, Jira or Salesforce) and other endpoints—either in batch updates, or dynamically in real-time.

Such interconnectivity between business applications is fundamental to automating business (and IT) processes. Often those applications will need data to be transformed to a different format as it moves between them, and sometimes the applications are different versions or instances of the same tool—but whatever the case, you need to be able to get all the right data to the right place at the right time.

Why Do Data Integration?

Data integration is all about moving data from one place to another. This often involves large quantities of data, and the integrations are typically one-way.

Data integration is necessary for a variety of purposes, including the following:

  • Developing and testing with real data
  • Promoting and sharing foundation data
  • Populating a CMDB from external sources
  • Syncing data for reporting
  • Copying to a big-data framework
  • Upgrading a tool or migrating to a new tool
    Data integration exists because perfectly aligned data doesn’t. If you’re trying to get data from there to here, it’s because whatever data you have with you now is insufficient.

The Right Data Integration Solution for Service Management

There are a number of different data integration solutions for Service Management use cases. 

The “Do it Yourself” (DIY Data Integration) approach is often assumed to be a cost-effective solution. 

However, for large organizations in particular, the reality does not typically meet this expectation, as DIY data integrations come with hidden costs

Creating and maintaining custom integrations at scale is often inefficient and expensive.

As data volumes grow, custom integrations can severely impact ServiceNow performance, slowing organizations instances down.

At scale, the best data integration model is an integration as a service via message bus native application.

Further, custom integrations consume development resources that could otherwise focus on value adding tasks.  

This makes the DIY approach only really viable for smaller, low volume “one-off” integrations.

At scale, the best data integration model is an integration as a service via message bus native application.

Whether transferring data to run reports, to keep another IT Service Management (ITSM) tool in sync, or to fulfill other needs, modern organizations face the challenge of integrating data without creating significant performance impacts on the production instance of their ITSM tool.

The rest of the organization cannot simply stop what they are doing so that IT can run reports.

With the right integration solution in place, a service provider can create reports or perform other data replications for customers without performance impacts to their ITSM instances.

That kind of integration solution dynamically detects changes in data. Rather than relying on a batch poll, it pushes only the data that has changed, enabling the best possible throughput and flexibility with the least impact to the publishing application.

Native applications in particular provide a number of benefits. 

Without a native application, organizations must undertake manual data entry data and query data across multiple, disparate systems.

Even many custom integrations require more labor than necessary, often requiring ongoing developer maintenance for a solution that is supposed to be “automated”. 

With an application native to the ITSM solution, combined with a common data model, integrations are simple. Organizations can avoid hours of manual data entry, custom development, and maintenance labor.

Interested in a native integration as a service solution? Speak to Perspectium

Perspectium recently announced the Iodine update.

The Perspectium Iodine release introduces many improvements based on user feedback, including powerful data storage options, productivity and data analysis tools and flexible backup and restore for ServiceNow.

See the webinar recording where we examine the new release’s functionality and dive into more features and details.

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Zak Cole