The Process Collaboration Pair Makes Great Organizational DNA

Who is this article for?

• Organizations looking to improve efficiency and performance through better collaboration
• Companies undergoing digital transformation of their business processes
• Enterprises seeking to foster more innovation through cross-functional teamwork
• Managers and team leaders responsible for process improvement
• Project managers looking for ways to deliver successful outcomes consistently
• Business analysts and process designers mapping out workflows
• IT leaders evaluating tools to support collaboration and process management

These roles need to understand how to build collaboration into business processes in order to improve organizational performance. Integrating collaboration and process allows teams to work together more effectively to achieve business objectives.

What is process collaboration and why does it matter?

Process collaboration refers to integrating collaborative practices directly into structured business processes. It’s about enabling people to work together seamlessly as they execute on defined workflows to deliver business results.

• Access to diverse skills and knowledge
• Faster problem-solving and innovation
• Ability to break work into manageable chunks
• Scalability of processes
• Constructive differences in perspective
• Improved employee engagement and job satisfaction

However, collaboration alone is not enough. It needs the structure and direction provided by well-designed business processes.
As Corradini et al. (2018) explain, formalizing the semantics of business process models is essential for enabling effective collaboration. A clear process framework helps embed collaborative practices in a meaningful way.

How to implement process collaboration

Follow these steps to successfully pair collaboration and process in your organization:

1. Define business objectives: Clarify the outcomes you want to achieve through better collaboration. This allows you to design processes and collaborative practices that support those goals.
2. Map out processes: Document the steps involved in key processes, including what information is needed when and by whom. Visual process maps make it easy to see opportunities for collaboration.

What are common challenges with process collaboration?

Watch out for these pitfalls when implementing process collaboration:

• Lack of clear goals: Without well-defined objectives, collaboration can become unproductive. Ensure managers can articulate how collaboration supports business priorities.
• Lack of decision-making transparency: Teams need to understand how decisions will be made within the collaborative process. Define decision criteria upfront.
• Lack of management commitment: Managers must visibly support collaborative processes and abide by the same rules. Their engagement is critical for adoption.

How Tallyfy enables process collaboration

Tallyfy provides a platform to document processes once and make them accessible to all, so teams have a shared understanding. This AI-powered documentation serves as the backbone for collaboration.

With Tallyfy, you can structure intake to channel work into well-defined processes. This replaces ad hoc requests and disjointed forms with trackable workflows.

Conditional logic allows you to show the right task to the right person at the right time. This keeps work flowing while allowing for flexibility based on the situation.

Real-time tracking provides visibility into work status without constant check-ins. Managers can see progress at a glance and identify bottlenecks.

Customer-facing links allow you to extend process collaboration to clients and partners. They can provide information and complete tasks without creating an account.

Tallyfy’s fill-in-the-blank templates ensure consistency in deliverables while still giving users flexibility. This supports standardization and creativity.

Conclusion

How is AI Changing Process Collaboration?

Process collaboration – the concept of teams working together to execute business processes – is undergoing a major transformation thanks to artificial intelligence (AI) and related technologies. AI is enabling more intelligent, automated and data-driven ways for teams to collaborate on workflows and processes.

At a high level, AI can help make process collaboration more efficient and effective in several key ways:

• Automating repetitive tasks and workflows to free up human time
• Providing real-time process analytics and optimization recommendations
• Enabling more intelligent task routing and resource allocation
• Enhancing communication and knowledge sharing among team members

For example, AI-powered process mining can automatically discover, monitor and improve real processes by extracting knowledge from event logs in information systems (Corradini et al., 2018). This allows teams to gain unprecedented visibility and control over how work actually gets done.

Natural language processing (NLP) and chatbots are also transforming how teams interface with business processes. Rather than navigating complex systems, users can simply converse with an AI to kick off workflows, get task updates, or find relevant information (Dustdar, 2004). This makes process collaboration much more intuitive and accessible.

The Future of AI-Driven Process Collaboration

Looking ahead, we can expect AI to drive even more transformative changes in how teams execute processes together. Some potential future developments include:

• Processes that can dynamically self-optimize in real-time based on goals and KPIs
• Intelligent process agents that proactively guide users and make smart recommendations
• Seamless integration of AI into collaborative interfaces like video conferencing and virtual whiteboards
• AI systems that can infer and map tacit process knowledge within organizations

Of course, realizing this future will require addressing key challenges around change management, algorithm transparency, data privacy and more (Tan et al., 2012). Leaders will need to actively shape the path forward to ensure AI enhances rather than inhibits effective process collaboration.

However, the potential benefits are immense. With the power of AI and data, organizations can unlock massive efficiency gains while enabling teams to focus on higher-value work powered by seamless, intelligent process flows. The future of work is one where humans and AI closely collaborate to achieve process excellence.

Related Questions

What is an example of collaboration process?

A great example of a collaboration process is a team of designers working together to create a new product. They might start by brainstorming ideas, then divide up the work based on each person’s strengths. Throughout the project, they’ll meet regularly to share progress, give feedback, and make adjustments. By the end, they’ll have a finished product that’s better than any one person could have created alone.

What are the steps of the collaboration process?

While every collaboration is unique, most follow a similar process. It starts with clearly defining the goal and agreeing on roles and responsibilities. Next, the team gathers information and generates ideas. They then evaluate those ideas and create a plan of action. As the work gets done, the team communicates constantly, sharing progress and troubleshooting issues. Finally, they review the end result and reflect on lessons learned for next time.

How do you describe a collaborative process?

A collaborative process is all about people working together towards a common goal. It involves open communication, shared decision-making, and a willingness to value diverse perspectives. In a true collaboration, everyone contributes their unique skills and insights. Conflicts are resolved constructively and the group dynamic is one of mutual trust and respect. The end result is something that no individual could have achieved working alone.

What are the 4 stages of collaboration?

Most collaborations progress through four key stages. First is forming, where the team comes together and gets to know each other. Next is storming, where different ideas and personalities may clash as the group figures out how to work together. Then comes norming, where the team finds its rhythm and processes. Finally is performing, where the team is working at its peak, fully in sync and achieving great results.

How does collaboration expand the creative process?

Collaboration can take creativity to a whole new level. When people with different backgrounds, skills and perspectives come together, they can spark ideas that no one would have thought of alone. Collaborating forces you to explain your thinking, consider alternatives, and make novel connections. It can help you break out of creative ruts and see problems in a new light. Plus, the energy and enthusiasm of a group can keep you motivated through even the toughest creative challenges.

References and Editorial Perspectives

Brown, P., Daniels, C., V., Bocken, N., & Balkenende, A. (2021). A process model for collaboration in circular oriented innovation. Journal of cleaner production, 286, 125499 – 125499. https://doi.org/10.1016/j.jclepro.2020.125499

Summary of this study

This study investigates the processes companies undertake when designing and implementing collaborations for circular oriented innovation. It integrates strategic management literature to identify collaborative process “know-how” and relevant “building blocks”. The study also generates practice-based insights to understand how companies collaborate within circular oriented innovation. It identifies key challenges related to formulating an initial circular proposition, involving the right people, aligning on a shared circular purpose, developing circular governance and decision-making, and developing a value capture model focused on collective outcomes.

Editor perspectives

As a workflow platform, we at Tallyfy find this study highly relevant for understanding how to enable effective process collaboration for circular and sustainable innovation. The process model and identified challenges provide valuable guidance for companies looking to set up collaborative workflows to drive circular initiatives forward.

Corradini, F., Fornari, F., Polini, A., Re, B., & Tiezzi, F. (2018). A formal approach to modeling and verification of business process collaborations. Science of computer programming, 166, 35 – 70. https://doi.org/10.1016/j.scico.2018.05.008

Summary of this study

This paper provides a direct formalization of the semantics of the BPMN 2.0 standard for modeling business process collaborations. It focuses on the capability to model collaborations among organizations via message exchange. A key aspect is the ability to model business processes with arbitrary topology, allowing designers to freely specify processes according to reality. The formalization is implemented using Maude, enabling automatic verification of collaboration properties.

Editor perspectives

The formal modeling approach in this study is very interesting to us at Tallyfy. Being able to precisely specify and verify the semantics of collaborative business processes is crucial for ensuring they execute as intended. We see a lot of potential in leveraging such formalizations to provide more robust workflow automation capabilities.

Dustdar, S. (2004). Caramba—A Process-Aware Collaboration System Supporting Ad hoc and Collaborative Processes in Virtual Teams. Distributed and parallel databases, 15, 45 – 66. https://doi.org/10.1023/b:dapd.0000009431.20250.56

Summary of this study

This paper presents Caramba, a novel approach and system for supporting process collaboration in virtual teams. It tightly integrates associations between processes, artifacts, and resources to enable efficient communication, coordination and collaboration. The paper analyzes criteria for process-aware collaboration system metaphors, coordination models for virtual team structures and ad-hoc processes, and architectural considerations for an integrated internet-based collaboration system.

Editor perspectives

The Caramba system described in this paper aligns very well with Tallyfy’s vision of providing an integrated platform for process collaboration. We believe the tight coupling of processes, artifacts and resources is key to streamlining virtual teamwork. The architectural considerations around internet-based delivery are also still highly relevant today.

Grekova, K., Calantone, R., J., Bremmers, H., Trienekens, J., & Omta, S. (2016). How environmental collaboration with suppliers and customers influences firm performance: evidence from Dutch food and beverage processors. Journal of cleaner production, 112, 1861 – 1871. https://doi.org/10.1016/j.jclepro.2015.03.022

Summary of this study

This study explores how environmental collaboration with suppliers and customers can improve the sustainability and business performance of Dutch food and beverage processors. It finds that collaboration with suppliers can directly improve performance through cost savings. However, collaboration with customers has a more indirect effect, by stimulating firms to implement sustainable process improvements that subsequently lead to cost savings and market gains.

Editor perspectives

At Tallyfy, we’re very interested in how collaborative processes can drive sustainability improvements and business results. This study provides great insights into the different mechanisms through which upstream and downstream collaboration influences firm performance. It highlights the importance of customer collaboration for catalyzing internal process changes.

Parker, H. (2000). Interfirm collaboration and the new product development process. Industrial management + data systems/Industrial management & data systems, 100, 255 – 260. https://doi.org/10.1108/02635570010301179

Summary of this study

This study investigated collaboration in new product development within the South African textile and clothing industry. It analyzed the perceived benefits and risks of collaboration, the effect of collaboration on the NPD process, and factors that increase the likelihood of successful collaboration.

Editor perspectives

New product development is an area where we see many of our customers looking to improve their collaborative processes. This study surfaces some important considerations around aligning on the benefits, mitigating risks, and setting up the right conditions for NPD collaboration success. These are all factors we aim to support through the Tallyfy platform.

Philbin, S., P. (2008). Process model for university‐industry research collaboration. European journal of innovation management, 11, 488 – 521. https://doi.org/10.1108/14601060810911138

Summary of this study

This paper proposes an improved process model for university-industry research collaboration. Building on best practices from the literature, it provides a logical methodology for developing and managing research collaborations that captures process, knowledge and social elements. Application of the model to an engineering research program demonstrated benefits as well as underlying issues.

Editor perspectives

The holistic process-based approach to research collaboration described in this paper resonates strongly with us at Tallyfy. By providing a practical “route map” that integrates multiple elements, it offers a lot of value to practitioners. We’re always looking for this kind of structured yet flexible guidance to embed in our workflow management platform.

Sargent, L., D., & Waters, L. (2004). Careers and academic research collaborations: An inductive process framework for understanding successful collaborations. Journal of vocational behavior, 64, 308 – 319. https://doi.org/10.1016/j.jvb.2002.11.001

Summary of this study

This study inductively develops a framework to understand the mechanisms that influence successful academic research collaborations. Drawing on the experiences of distinguished researchers, it outlines the phases of a collaborative project from initiation to completion. Key factors affecting the phases are the collaborative context (resources, support, climate) and interpersonal processes (communication, trust, attraction). The framework provides suggestions for building and maintaining academic collaborative relationships.

Editor perspectives

While this study focuses on academic research collaborations, we believe the insights are highly transferable to other domains. At Tallyfy, we see the interplay of contextual and interpersonal factors as critical for any kind of process collaboration. The phased framework provides a helpful structure for guiding successful collaborative efforts that we can look to operationalize in our workflow tools.

Tan, W., Li, L., Xü, W., Yang, F., Jiang, C., Yang, L., & Choi, J. (2012). A role-oriented service system architecture for enterprise process collaboration. Computers & operations research, 39, 1893 – 1900. https://doi.org/10.1016/j.cor.2011.07.007

Summary of this study

This paper proposes a role-oriented service system architecture to support enterprise process collaboration. It discusses key technologies such as mapping process activities to application services, using XML in process models, and workflow engine techniques. The architecture is implemented and validated in a 4PL business system case study.

Editor perspectives

Enterprise process collaboration is at the heart of what we enable at Tallyfy. The role-oriented service architecture outlined in this paper provides a compelling technical approach. We’re particularly intrigued by the mapping of process activities to application services as a way to drive process automation. The use of standards like XML also aligns with our philosophy of making process definitions portable and interoperable.

Glossary of terms

Business process collaboration

Business process collaboration refers to the coordination and synchronization of activities between multiple parties in order to achieve a common business goal. It involves aligning the workflows and interactions of different organizations, departments or individuals to enable seamless end-to-end process execution.

Collaborative workflow

A collaborative workflow is a defined sequence of tasks and interactions that enable multiple participants to work together towards a shared objective. Collaborative workflows orchestrate the flow of information, documents and activities between people and systems, providing transparency and accountability throughout the process.

Process orchestration

Process orchestration is the coordination and management of multiple sub-processes or services to execute an overarching business process. It involves defining the sequence and logic for invoking various process components, handling data flow between them, and managing overall process state and exceptions.

Inter-organizational process

An inter-organizational process is a business process that spans the boundaries of multiple organizations. It involves the coordination and data exchange between different entities to fulfill a customer need or deliver a product or service. Inter-organizational processes often rely on agreed protocols and interfaces to enable collaboration.

Process-aware information system

A process-aware information system (PAIS) is a software system that manages and executes operational processes involving people, applications, and data based on explicit process models. PAISs provide process transparency, enforce process rules and enable process optimization. Workflow management systems are a common type of PAIS.