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As organizations grow, so does their data and business applications. Different departments and teams will likely use a variety of different business applications, which leads to disparate data. If this data is not orchestrated properly, it can affect all aspects or your organization, from understanding your audience, to communicating with customers and reporting on the success of activities. So, data orchestration is needed to unite information and help the organization to run optimally.
But manual data coordination is a cumbersome task. One that grows even harder the bigger your organization is, particularly if you start to embrace big data. The answer lies in automated data orchestration…
Data orchestration is an automated way of bringing together siloed data stored in various sources. Uniting data from these disparate systems readies it for processes, analysis and interpretation, which can help the organization to make better, data-informed decisions.
Quite simply, you don’t know what you cannot see. So, if your data is stored in multiple locations that not all departments have access to, it creates blind spots and gaps in your business’s knowledge, which lead to the following problems.
Duplicated data: A lack of visibility over your data then means that data is often duplicated. As organizations grow, this problem often does too. This can lead to skewed results in analysis or poor customer experience if you have multiple contact details.
Poor data analytics: Disconnected data makes it very difficult to gain meaningful insights from your data. This can impact both internal and external insights, from customer behaviour to how well your departments are operating. This makes it hard to make informed business decisions.
Wasted time and resources: Time spent trying to locate, format and verify data can be an incredible time sink for employees. This time could be better spent analyzing the results of the data and using it to inform their business strategy and improve customer experience.
Poor customer experience: Customer communication relies heavily on data. From name and contact details for basic communication to important and sensitive data like payment details, to the more nuanced customer behaviour data, such as product usage, purchases, reviews, queries and complaints. Providing a customer with irrelevant or incorrect information because their data was not properly orchestrated can be very damaging.
Poor collaboration between teams: If different teams have different sets of data that they’re looking at, it’s hard to properly collaborate. People will believe the data that’s sitting in front of them, which can lead to disagreements if it differs. Or if the data isn’t present, then they waste time sharing the data back and forth, which hinders productivity.
Lack of innovation: Incomplete view of information makes it hard to make strategic decisions that lead to innovation. Data orchestration can help organizations to see the bigger picture, which can help them to try out new techniques and innovate. And in today’s competitive business landscape, those that don’t innovate are likely to get left behind.
Inability to automate processes: If there are gaps between data, it makes it difficult to automate processes and the data cannot effectively pass through the process. This can hinder your company’s progress if you are looking to optimize business operations. In order to ensure your automated processes work effectively, the data, applications, and processes should all be orchestrated.
Of course, some might ask, why don’t you just unite your data by putting it all in one place? But migrating data to a single source is a mammoth, if not impossible task. But data orchestration can unite the data held in separate systems.
Data orchestration enables all data and information to run in their unique applications and systems, while providing the benefits of visibility, speed and accuracy across the organization. This data orchestration ultimately allows better analysis, to help facilitate better business decisions.
Reduce costs: If your data is orchestrated, you don’t need to spend time and money locating, collecting, formatting and verifying data. It’s automatically done for you. Plus, orchestrated data means you don’t have to spend money on additional systems.
Increase efficiency: Orchestrated data eliminates bottlenecks such as passing data back and forth and any mishandled data, which saves time and means users can get on the task in hand more quickly without worrying about data collection and preparation.
Enable innovation: The business insights gleaned from proper and thorough data analysis can reveal new business opportunities, and help keep customers satisfied.
Optimize business operations: Having the full picture of data will enable business users to make better, data-informed decisions. The more data you have, the more important it becomes. Big data orchestration can help to make decision making more efficient and accurate.
Unilever Asia Private Limited, part of one of the world’s leading consumer good companies, needed to orchestrate information for its cross-border shipments to enable speed and accuracy of data. They needed to create clear, integrated workflows to optimize operations in processes including customer shipping. Complex shipping documents were shared over email, with no proper visibility or control over the process.
Using Bizagi’s low-code platform, they were able to orchestrate and manage large data sets, without having to rely on manually completing spreadsheets and sharing them over email. Integrations with key applications, such as SAP and DocuSign, and automated Excel uploads, provided an easy and reliable way to ensure data was up-to-date and decisions were approved on time by the correct people.
Information now flows from the various systems into Bizagi for full visibility and control. Over 170 fields are imported from Excel and displayed in an easy-to-use tabbed format in Bizagi. Over 1,900 cases were submitted in the first seven months of use, with 87% of cases completed within a month of submission. Previously, cases would have taken up to two months to complete.
Read the full case study to find out more.
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