With process intelligence, you can get ROI on your AI as you can better pinpoint your agents and automations to fit in the end-to-end process together with your systems and co-workers, suppliers and customers.
To succeed with this, you need to dare to get started. Everything doesn’t have to be perfect. Get a business-critical use case that is easy to explain to leaders and co-workers across your organisation. Simplicity wins..
What is process intelligence in a nutshell?
Process intelligence provides a common language for understanding how a business runs and where performance can be improved. By connecting process data with business context, organisations can identify where value is trapped in day-to-day operations and turn insights into action across functions, teams and systems.
Process intelligence works by analysing process-related information from , for example, event logs generated by enterprise systems, such as ERP or CRM.
By following these digital trails, you can get a clear view of how your processes are executed end-to-end. This means more fact-based decision-making and less gut feeling.
Let’s get practical
We can group it into 5 easy steps: goal-setting, measuring, analysing, designing, and implementing. However, a critical overarching step is the monitoring of value realisation and ROI. Your business leaders will love the opportunity to see the benefits counted.
1. Goal-setting
Start with your strategic goals as a foundation, identify a process like accounts payable that you see a need to improve and clarify what needs to improve. Is it customer experience, lead times, working capital, cost or something else? Good steps to cover are:
- Aligning business strategic goals, key initiatives and pain points
- Consider which value chains are impacted by that strategy
- Consider process maturity when selecting a suitable project
- Define control tower desires (how do I want to track this)
2. Measure
- Get the data : What data do you need for a clear view of the process? What systems are working in this process? Go get that data, e.g. from event logs of your ERPs or CRMs!
- Discovery: Use the retrieved data in a process intelligence platform and see what is actually happening in the process step by step. Discover variations across the organisation, customers, suppliers and materials etc.
If you have more time, already map people, data and tech dependencies to the process.
3. Analyse
Understand problems and improvement potentials. See what issues you find and dig into their root causes.
4. Design and propose improvements
- Use the information from the fact-based analysis phase to determine what might be suitable solutions, now and in a roadmap
- Leverage the AI toolbox for re-design activities
5. Implement business changes
Align people, systems and data
- Use re-designed processes as blueprints for implementation
- Define global standards and local variants
- Assign E2E ownership
- Establish process performance indicators to measure the goal accomplishment and strategy adherence
Technical
- Suitable apps or AI solutions to solve issues (enrich data and decision making)
- Outside solutions, such as clarifying communications to customers or suppliers
- Orchestration of “hidden” process of unstructured data – humans e.g. system of tasks (emails, Excel, etc.) and automations, and agents
Follow up on the improvement of the process and the impact of the change by tracking the value of improvements to the process, agents and/or new intelligent orchestrations.
With our experience in process intelligence, we can help you every step of the way. Don’t hesitate to reach out.
In my next blog post, I’ll deal with favourable organisational prerequisites to succeed, simply put: who you need to succeed.