Automated data integration is strategically important to productivity and business intelligence.
All employees work with data every day. And having information up to date and in the right places when you need it is crucial to productivity. Manual data entry, verification and lookups slow any process down without automated data integration.
Data can also be a business’ greatest asset for growth. When it comes to decisions on how to drive revenue, increase profit, improve efficiency and satisfy customers, data always holds the key to the best idea for improvement. But, your data is only as good as the form it comes in—which in today’s market may mean varying forms and even higher volumes.
Without consolidated, standardized and up-to-date data across the enterprise, you can’t get large-scale business analytics or peak performance in your workflows. But intersystem master data management, consolidated reporting and integrations can be meaningful projects to implement and maintain that can drive your business forward.
Automated data integration tools can help. Here’s how.
Importance of data integrity and data quality
It’s impossible to find meaningful insights in a sea of raw information. As companies become increasingly digital and reliant on technology that uses data within a growing number of systems and software, a company’s data becomes more siloed, disparate, and duplicated, and the sea of data grows. To have high-quality data is to have all information standardized, structured and compiled in a way it can be easily distilled and reported on.
Whereas, if your company relies on manual data entry, your data could have a whole other slew of data integrity issues where information is more likely to be outdated, subjective, or contain copy-and-paste problems or typos due to human error. Having incorrect data like this can come with varying degrees of risk, depending on your industry or role. While disorganization is a risk to company efficiencies and operations, data mistakes expose risks from customer service mixups, a finance department charging or paying incorrect amounts, or even worse threats in an industry like healthcare.
Automated data integration can solve the problem of both data integrity and quality, so that you can find the information you need, analyze it, report on it, and trust that it’s accurate.
Data integration strategy for workflow
Of course the simplest way to execute a data integration strategy is from the beginning, dynamically syncing all of your systems from the start. But, for mature companies, there are still ways to begin to automate and integrate your data without a rip-and-replace scenario or a heavy enterprise data integration overhaul and system architecture project.
A data-based process automation tool can sit directly on top of your existing systems to orchestrate the processes you use them for—and the data that each step contains. This makes it more practical to use data in-context and makes change management easier.
Using a cloud workflow automation tool can embed data integration into every step in your process. When you automate with data tables at the core, tying your process together, you can connect to data from any system—whether unstructured like email or structured in a database—and dynamically connect it to notifications, tasks, or other software you use in a workflow.
With this type of tool, you could build a process that is simply for data migration, conversion and real-time updates, but the real power comes in using automation for dynamic, integrated data-based workflows for everyday operational processes. After all, that’s what you usually need your data for.
This approach to using automated data integration to fill in contextual steps in your workflows can seamlessly connect your people and systems, filling in the gaps and creating a system of record for how your workflows use data.
Over time, building workflows like these that leverage data and organize it in the context of your processes can save employees time, increase data quality, and accuracy as it is constantly being updated and processed through a rules-based automated workflow.
Master data management
An automated master data management process can help with data cleanup. You can use automation technology to connect to a system of record like an HRIS, VMS, CRM or ERP and validate each record’s data against a set of rules.
For example, an automation could pull a vendor list, send a form to each vendor to update their data in a standardized way, then update the corrected data back into a VMS. Using technology like OCR, it could also scan certificates or documentation to automatically extract and validate other information in the record. It can also automatically send a notification to a vendor for renewals if anything is expired.
This process-led approach for master data management is effective to fill in the gap between manual data entry and automated data integration. While automation can find, organize, validate, calculate or process data, a tool that can easily connect to a person—whether an employee, customer, or vendor—to verify or gather new data makes this approach even more effective.
But, automation can also be used to complete one-time data projects to deduplicate and consolidate records across systems. It can use fuzzy matching to identify similarities, then reformat or recalculate any differences into a merged record. It can automatically standardize records within a certain confidence level, and when outliers appear or the confidence level isn’t high, the record can automatically be routed to a person.
Business intelligence and operational insights
As your use of automated data integration in your processes grow, you can start to leverage these data-rich workflows as opportunities for business intelligence and analytics for top-line growth and bottom-line operational improvements.
With a tool for automated data integration, you could build an automation that can extract data from different sources and systems, make conversions and calculations, then present a consolidated report. A dynamic and truly integrated approach could even use this data to populate a presentation-ready PowerPoint or a dashboard in PowerBI, in addition to the obvious spreadsheet report.
When harnessing the power of automatically putting data in a digestible format, business leaders can spend more time analyzing the results and making the smartest decisions, rather than letting data go unused from lack of time, or misunderstood for lack of formatting.
This kind of business intelligence can lead to revenue-generating opportunities to meet an identified customer demand with a product, service, or resource allocation. Not having automated data integration for this purpose is a missed opportunity.
Another facet of business intelligence is operational intelligence. When keeping a system of record for workflow with integrated data, all process information can be recorded and reported on automatically. This makes it easy to find bottlenecks and makes changes to your operations in real time to increase speed and efficiency at any step in the process. And with enough adjustments for efficiency across your organization, your speed to value or operating model can not only cut costs, but become your greatest competitive advantage.