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Improving Business Processes via Workflow Orchestration in '24

Updated on Feb 22
3 min read
Written by
Cem Dilmegani
Cem Dilmegani
Cem Dilmegani

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

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As organizations grow, they need to scale their business processes to ensure productivity and manageability. Solutions such as scheduling and automation enable organizations to streamline their IT processes. However, due to the increasing complexity and dependencies of IT processes, simple automation or scheduling are no longer able to meet the requirements of modern business environments.

One of the recent solutions used by organizations is workflow orchestration. As a more comprehensive solution than scheduling and automation, workflow orchestration helps organizations schedule, execute, and manage numerous automated processes and eliminates complexity and faults.

This article presents 4 types of workflow orchestration and 5 criteria to consider when selecting a workflow orchestration tool. 

What is workflow orchestration?

Automated business processes often involve numerous tasks or workflows. A workflow represents a group of tasks or data processes that are interconnected, follow a predefined logic, and result in the previous task triggering the next one (see Figure 1). 

Figure 1: An example of a workflow in an e-commerce application.

Picture shows how Google Cloud works when a new e-commerce invoice is received.
Source: Google Cloud Blog

Workflow orchestration can be defined as a process that ensures the compatibility and order of automated tasks to prevent errors in an IT environment. The orchestration feature: 

  • Ensures the order and accuracy of workflows,
  • Allows users to manage the automated configuration of applications and services,
  • Allows monitoring and reporting errors.

4 Types of workflow orchestration 

1. Cloud orchestration

Cloud orchestration can be defined as the management of automated tasks in a cloud environment based on a predefined sequence. As users can customize the sequence of workflows, its orchestration capability helps organizations increase their agility. 

For example, cloud orchestration can be used for provisioning and deploying servers in the cloud. This involves the orchestration of dependencies and putting numerous tasks in sequence in the cloud, on-premises, and hybrid environments. Other instances include storage allocation and network configuration.

2. Data center orchestration

In a digitized business environment, data centers process huge amounts of data and a large number of automated tasks such as configuration and ETL (extract, load, and transfer) automation, that require information from the data centers. The sequence of these automated tasks plays an important role in an organization’s agility and efficiency of business processes.

Data center orchestration (see Figure 2) maintains the orchestration of automated services such as configuration, performance, load balancing, auto-scaling, and security policies. A successfully completed orchestration ensures coherent and continuous data center operations.

Figure 2: Illustration of a data center orchestration process

Source: Avi Networks

3. Business process orchestration

Business process orchestration refers to the process of coordinating, synchronizing, and monitoring automated workflows in business operations. It represents a strategy for organizations to connect automated processes while improving business efficiency and minimizing process errors.

Business process orchestration can help organizations during the coordination of different but interrelated processes such as hiring and onboarding. These processes require frequent but effective communication and at this point, business process orchestration ensures the proper and coherent running of workflows. 

4. Application release orchestration

Application orchestration is the process of managing and orchestrating the end-to-end release of a software pipeline. It helps development teams to improve the speed and quality of deliveries by coordinating deployment and pipeline management throughout the release phase. It minimizes faults and errors and increases agility while avoiding communication issues between different teams.

5 Criteria to consider when choosing a workflow orchestration tool

  1. Adaptation period: A seamless transition from the existing system to a workflow orchestration tool is critical. Organizations need to be aware of potential delays and interruptions of services.
  2. Hybrid and cloud integration: As business environments are diverse, they require integrations for seamless business processes. Workflow orchestration tools should have easy integrations with cloud and hybrid systems to get the most value from them, as well as flexibility and scalability. 
  3. Maintenance costs: Organizations can avoid additional costs by reviewing them from the very beginning. Maintenance costs should be kept in mind and make sure that the maintenance information, costs, etc. are clearly stated.
  4. End-to-end visualizations: Visibility of workflows under a single pane of glass can help organizations to have complete control over large and complex business processes. Organizations can monitor processes from end to end, helping them quickly identify and fix errors.
  5. Security and access controls: Security and access management are critical during the orchestration of workflows. If the orchestration tool provides access management checks, each user can easily reach out to past activities and learn who has set up which orchestration and connected with which workflow. 

Further Reading

To learn more about WLA solutions, feel free to read our articles:

If you are looking for automation and orchestration tools, you can visit our hub for the automation software landscape.

If you have other questions about workflow orchestration, we can help:

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Cem Dilmegani
Principal Analyst

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Cem's hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

Sources: Traffic Analytics, Ranking & Audience, Similarweb.
Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
Data management barriers to AI success, Deloitte.
Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
Science, Research and Innovation Performance of the EU, European Commission.
Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

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