An easy way to add AI skills to your team’s designer practices.
In my last post, I introduced a new blueprint framework our teams in the IBM Garage are using to create Cognitive Enterprises by using AI. In this article, I will be talking about a new designer practice and complimentary artefact to a Cognitive Enterprise Blueprint called Intelligent Workflows. These workflows are how our teams identify opportunities for AI, automation, robotics and IoT to help make business processes more efficient and more useful. The combination of a Cognitive Enterprise Blueprint and Intelligent workflow will become a powerful, cross-functional tool for your own teams when designing human/machine relationships.
We use this blueprint in two ways. My last post focused on the first area when re-designing an enterprise or functional area of a business. This post will focus on the second area, which deals with micro-moments in a user experience:
- To choreograph an enterprise to deliver on the moments that matter for its customers;
- And to help identify the right scenario for the AI to deliver on its purpose, value and trust to the human it is serving.
Whether you are improving a current state or creating a future state, an Intelligent Workflow uses many common design thinking and Lean UX practices. For example, we use Personas and Value Prop canvases to identify people’s needs and the new value we can create by solving those needs. In an Intelligent Workflow, our teams take a Persona canvas and use that to create the role of the digital worker in the workflow. This ensures that the design of the human/machine relationship is transparent to the team and stakeholders by providing direction for how the cognitive systems will fulfil their potential.
What is a digital worker? They are the robots in a workflow that are helping to analyse and automate commonly performed tasks in our work. These robots are enabled by AI and the AI systems are triggered by the sensors on an IoT device. I’ve included an example below of a user story about a digital worker that supports a superintendent in the area of team rostering for an energy company that uses this combination of robotics, automation, AI and IoT.
Consider all the variables that take place when a person calls out sick—the gap in the value chain or workflow from the skills provided by this person; the leading indicators of sickness like the amount of work coming up and the lagging indicators of how many people have been sick in the last week; and the redistribution of work that needs to happen so the team can still deliver to plan with minimal impact to energy production. This multiple-step analysis and synthesis would take a person hours to perform and the day would be half over. In this user story the work is done in minutes, and provides an outcome minimising the impact to production.
The use case and user story maps below are some of the artefacts our teams in the IBM Garage use to describe the organisation and patterns of data that need to flow through the AI systems to identify, understand, and apply knowledge and reason to produce an outcome.
Our product teams of engineers, designers and business product owners work to understand the data that sits underneath the variables to determine the fabric of the intelligence they will be building. They also look at the tasks a human would perform in the scenario and match the intents to a machine that mimics the human process. Then they can collectively design the AI into the experience, interactions and conversations that will take place in the workflow between the humans and the systems. It may sound complicated but we’ve developed fun tools that help to remove the complexity and fear of doing something that is quite new for many clients and new team members.
Our Design for AI workshops are made so that all people can participate with all types of skills and backgrounds. They are intentionally made for cross-functional teams so that everyone can perform the activities and brainstorming sessions. We’ve included a set of cognitive playing cards with capability pictures on them that relate to the skills people use to perform common tasks. Often, it’s not one card that is selected from the pile, but a combination of these cards helps our teams determine how the AI will engage with the human. Once we understand all this, then we can design the features and functions of the intelligence in the workflow.
Often these types of Intelligent Workflows are best communicated and understood by stakeholders through a set of common design artefacts:
- A pictorial story or journey that communicates the experience for both the human and the AI. A customer journey map or Golden Thread is often used for this.
- A sample set of human and AI user stories that simulate the human/machine interactions and how the relationship will build over time, like the ones shown above.
- A Cognitive Enterprise Blueprint that houses the validated moments, data and system require to build each interaction.
- Small scale experiments of the micro-moments in the workflow that show what is possible and how the data will be used.
Related articles: The Design Blueprint for an intelligent enterprise