Starting with the Business Process: A Foundation for Effective AI Solutions
Effective AI solutions start with understanding the business process. By collaborating with SMEs, organizations can ensure AI aligns with workflows and drives real value.
Artificial intelligence (AI) has become a critical tool for enhancing business operations, but its implementation can only succeed when it aligns with well-defined business processes. Often, organizations rush to adopt AI solutions without fully understanding the workflows, outputs, and impact on their bottom line. This article explores the importance of starting with the business process and working with subject matter experts (SMEs) to ensure AI solutions are practical, accurate, and value-driven.
Understanding the Business Process
Before introducing AI into any organization, it is essential to map out the existing business process in detail. This begins with identifying how workflows are carried out by SMEs. SMEs are the backbone of operational efficiency because they possess a deep understanding of the tasks, tools, and methodologies required for success.
Steps to Understand the Process:
Observe the Workflow
Spend time observing how tasks are performed, including the tools and systems used. This allows you to identify pain points, bottlenecks, and areas for improvement.
Analyze the Outputs
Look at the deliverables generated by the workflows. What purpose do they serve? Who uses them, and how do they impact broader business operations?
Map Dependencies
Understand how outputs from one workflow feed into other processes. This step is critical to see the broader picture and how changes in one area might ripple through the organization.
Define Business Goals
Align the process to specific business objectives. For example, is the goal to improve efficiency, reduce costs, or enhance customer satisfaction? Defining these goals is crucial to evaluating the success of any AI solution later.
Evaluating the Role of AI in the Process
Once the business process is fully understood, you can begin exploring how AI might augment it. AI should not replace workflows wholesale; instead, it should serve as a tool to enhance and optimize them.
Questions to Ask:
Does AI fit the process?
Evaluate whether AI is even necessary. If the workflow is already efficient, AI may add little value.
What tasks can AI augment?
Identify repetitive, time-consuming, or error-prone tasks where AI could provide significant improvements.
How will AI outputs be used?
Ensure that AI-generated outputs integrate seamlessly into existing workflows and meet the needs of those who rely on them.
How do SMEs view the solution?
SMEs must find the AI helpful and accurate. They are the ultimate judges of whether the solution is a practical improvement over existing methods.
Vetting AI Solutions for Business Operations
AI solutions are only as good as the value they provide to the business. To ensure success, the implementation process must involve constant feedback from SMEs and rigorous testing.
Key Practices:
Prototyping and Testing
Build a proof of concept and test it within the workflow. This allows SMEs to evaluate whether the AI is producing useful, reliable outputs.
Feedback Loops
Collect feedback from users and refine the AI model accordingly. A solution that SMEs reject will fail to deliver value, no matter how technically advanced.
Monitor Metrics
Track key performance indicators (KPIs) related to the process, such as time savings, error reduction, or cost efficiencies. These metrics demonstrate the AI’s impact on the bottom line.
Ensuring Alignment with Business Goals
At the heart of AI success is the connection between process improvement and business outcomes. An AI solution that improves operational efficiency or decision-making should directly or indirectly affect the company’s bottom line.
Example:
Consider a translation workflow in an organization that depends on SMEs to analyze foreign-language documents. By understanding the process, you may identify repetitive tasks (e.g., document categorization or keyword extraction) where AI could help. However, unless the AI-generated translations are accurate and reduce SME workloads, the solution will not succeed. The AI must enhance the speed and quality of the process while reducing reliance on costly external services.
Conclusion
The journey to successful AI adoption begins with a deep dive into the business process. By working closely with SMEs to define workflows, outputs, and dependencies, organizations can ensure that AI solutions are tailored to real-world needs. When AI is introduced only after the business process is well understood, it becomes a vetted, user-friendly tool that delivers measurable value. The ultimate success of any AI initiative lies in its ability to help SMEs achieve better outcomes and improve the business’ bottom line.
If you're looking for support, here is how to contact me:
Coaching and Mentorship: I offer coaching and mentorship; book a coaching session here