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SmartData Collective > IT > Cloud Computing > Battling Data Silos: 3 Tips to Finance and Operations Integration
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Battling Data Silos: 3 Tips to Finance and Operations Integration

johnnyor58
johnnyor58
4 Min Read
Battling Data Silos: 3 Tips to Finance and Operations Integration
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Finance is often flying half blind.

Finance is often flying half blind.  Charged with tasks such as budgeting, planning, forecasting, and reporting Finance executives are often only able to see half the picture: the limited amount of data that they have.

This data is usually limited to simply the planned or projected revenue and expenditures versus the actual revenue and expenditures. They often have no access to the data that tells the “how and why” that could lead to more accurate planning and forecasting.

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  • Finance is often flying half blind.
  • Finance is often flying half blind.  Charged with tasks such as budgeting, planning, forecasting, and reporting Finance executives are often only able to see half the picture: the limited amount of data that they have.

What is the solution? The solution is to break down the data silos and combine the data from other applications into a cloud-based enterprise performance management (EPM) platform that is used for planning, reporting, modeling, and analysis. Data silos are systems, files, and documents that exist across the enterprise and outside of the financial data sets. This includes all sorts of operational and business data that Finance often has limited access to. By breaking down those data silos and making all of the data readily available to Finance, you give them the power to budget and forecast like never before. Here’s how to get it right in your organization.

1. Conduct a Data Discovery Audit

Where is all the data? Basically, all of the data collected by disparate systems in the organization should be accessible to Finance. This would include legacy systems, spreadsheets, and department-specific applications like HR systems, CRM solutions, and any business or operational software that is in use. Don’t forget to include any cloud-based applications your business utilizes, including IT Service Management (ITSM), email marketing, marketing automation tools, etc.

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2. Develop a Plan for Consolidating Data

Consolidating your data silos doesn’t just help Finance. It also provides a single version of the truth for corporate data for users in other functions. There are numerous integration tools available to offload data from the original sources to a consolidated data store, such as a data warehouse or data lake. The most problematic offloading involves legacy systems that were developed in-house or by a vendor that has long since abandoned the product or gone out of business. It’s much easier to offload data from more modern applications, as most are developed to be compatible with other common business applications.  For purposes of planning and reporting, many organizations just integrate selected data from financial, HCM and CRM systems directly into their EPM platform.

3. Realize the Value of the Cloud for High-Performance and Scalability

Cloud storage is ideal, because it is immensely scalable, very affordable, and the cloud vendor usually takes over the responsibilities of data security, data backups, and other daily data storage issues. Once offloaded and consolidated, the data can be used to build a more comprehensive view of the organization and its financial picture and outlook via a cloud-based EPM platform.

Once all of the data is made available in the EPM solution, Finance has access to a more complete picture of the “why’s and how’s” behind what came in and what went out during any given fiscal period. Now, budgeting and forecasting can be more accurate, and the entire business can have more confidence in the projections Finance derives from the numbers. Plus, with a consolidated data store, everyone wins. Operations, human resources, customer service, sales, and marketing — everyone benefits from breaking down the data silos and consolidating the entirety of the organization’s data.

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