The design blueprint for an intelligent enterprise

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Author: Kim Bartkowski, IBM Design Principal, IBM iX A/NZ, Global Business Services

Bringing together enterprise strategy and human-centred design can help scale and mature your company’s AI transformation.

IBM Garage: Startup speed. Enterprise scale.

At IBM, it’s no surprise that we talk about AI. A LOT. It’s been a part of our everyday reality for some time. Our design teams are focused on the relationship humans have with the machines that we build to help augment human capabilities and provide essential services to us. Our technology teams are focused on bringing AI into all of our platforms, making it easier to implement and deploy faster. For us, AI is no longer a future-forward outlook for tomorrow’s transformation. It’s an essential building block for today’s business.

Before I can jump into something so heady and conceptual as the design of a human/machine relationship, it’s best that we first understand how people, processes, practices and platforms combine in IBM’s Cognitive Enterprise Business Strategy.

The ingredients of modern enterprises

The diagram below is what we affectionally call a layer cake on my team. It shows how all the ingredients of modern enterprises fit together. From the subconscious to the silicone, you can see how it stacks up. You can also see that corporate culture and experience play an important role in how it all fits together — the people and the practices they will need to use to design and create the processes and platforms that the machines will use to support them. We call these well-designed combinations of human skill and exponential technologies Intelligent Workflows.

IBM’s Cognitive Enterprise Business Strategy

IBM’s Cognitive Enterprise Business Strategy, a blueprint for AI-powered transformation. An overview of the Cognitive Enterprise can be found here.

If you are a service designer, this “stack” will look somewhat familiar to you. If you aren’t a practising service designer, the organisation of this enterprise strategy diagram is the beginning of how service designers identify and architect moments that matter along a value chain. In order for every moment to work as designed, every element in this enterprise stack needs to work together.

If the diagram above is the list of ingredients we need in our enterprises, then our Cognitive Enterprise Design Blueprint is the recipe book on how to bring it all together. A blueprint is not a journey map or a pictorial story. It provides more specific direction on how to choreograph and connect the people, practices, processes and platforms together. Think of it in the same way you would a blueprint for building a house or car.

A foundational design blueprint

Our teams in IBM Garages in Asia-Pacific have been working to marry IBM’s Cognitive Enterprise Strategy with a foundational design blueprint to show our clients how it all comes together in execution. Our teams use this in our IBM Garages in a few ways:

1. During discovery, it can be used to help organise research and identify new value creation.
2. As a team heads into MVP build, it acts as a guided tool so that designers, developers and business product owners know exactly what is being built. Engineering leads have used it for release planning to map Value with Engineering feasibility.
3. It neatly organises the people in a moment with the data, automation and platforms needed to build out a moment in the value chain. We’ve even added a layer in the blueprint that denotes how we can identify compliance and adoption.
4. We use it for training purposes when we are running in-market tests to validate when and how the MVP works in practice.
5. Business product owners use this with their teams to build out their key metrics and can assign values to all aspects of the enterprise.

Blueprint framework contributors: Sally Hughes, Stella Drivas, Monique Aronica, Kathy Veloso, Vishal Tandon, and Kim Bartkowski.

The relationship between human and digital workers

One key feature of this blueprint is the relationship between human and digital workers in delivering an experience. This is featured in the front-stage section above. There is some pre-work in the research and discovery phase that helps the teams understand the needs of the human and the intent of the AI to deliver on those needs. This blueprint shows the outputs from our design thinking for AI toolkit and shows where the data lies in which system to make it happen.

Modifications to this blueprint are easily done and expected. We keep our template in Mural so that everyone has access to the master, and they can modify it based on the work they are doing in their team rooms. Depending on how complex your experience is that you are designing, teams may decide to extend and list out all of the systems on individual lines to help track the data and APIs more easily. Teams have also included extra lines in their blueprints to track the interactions and emotional state of the human experience and how we should feel at each stage. Others have added to their blueprints a section to track unintended bias, especially when experiences bridge from simple automation to machine learning.

The result, when it all comes together, is nothing short of magic for the people using the experience. Other words commonly used in place of magic are seamless, intuitive, and natural.

Natural is exactly how we design our human and machine relationships to be.