Service design is at an inflection point. It is both well established in many organizations and also challenged to rise to a new moment. This is because AI requires us to revisit our ethos, methods, and tools. The capabilities of AI and its widespread adoption expose some of the shortcomings of service design, shortcomings that we have been aware of but have worked with up until now.
I want to face these head-on and explore two related hypotheses. I will publicly share my investigation, and I intend to regularly post about experiments, progress, and learnings. My focus is the service blueprint as the keystone tool of service design and three key challenges that we face that AI may be able to help us address:
- Evidence–the ability to make a strong case for change and prove value.
- Speed–the ability to interface with the business need for speed of delivery.
- Leadership–the ability to effectively lead and govern change.
My first hypothesis is that AI can help us evolve the service blueprint to become a more powerful tool by addressing the evidence and speed challenges–an evolved service blueprint that becomes a collaboration space for human and AI change agents and designers.
My second, bolder hypothesis is that this evolved blueprint could become an essential tool for change leaders–the strategic control mechanism for the CEO, the secretary of state, the director of a hospital, or any leader who needs to oversee change that is complex and systemic.
So, that’s it in a nutshell–please follow, as this is the start of an evolving investigation and conversation.
The blueprint: promise vs. reality
The service blueprint (sometimes referred to as a customer journey map) is a key tool for the design of services and experiences. It was one of the first things we decided to define at Livework when we started on our service design odyssey.
Our reference was blueprints used by industrial designers and architects to specify their creations. Documents that enable the translation of designs into reality. Blueprints that were used for designers to talk to engineers. These blueprints are critical documents that guide construction or manufacturing. We want the service blueprint to be equally vital.
A blueprint is a powerful tool for guiding the creation or change of a service. We have used them in many sectors from healthcare to banking. It can translate insight into the needs and experience of service users or customers into change that can be implemented by engineers who deliver the systems and processes that underpin services. It specifies how the capabilities of an organization–its products, people, processes, systems, and policies–come together to meet the needs of customers.
A service blueprint can go further and also enable the organization itself to understand how to better align around outcomes and across traditional departmental silos. It can be both a detailed specification and an executive summary. We have used a service blueprint to enable a CEO to have one view of the organisation–literally a service operating model–and also to specify how to integrate digital and IT systems across a fragmented NHS system of over 20 different organizations. It works.
The challenge is–as I said–evidence, speed, and leadership. Let me unpack these three a little more.
Evidence
Service design is built on human insight–the beating heart of service design is empathy for the needs and experiences of people in services. Customers, users, staff, etc. This insight provides a guiding principle for service design–good experiences that deliver for customers generally perform better. Like many things in life, your strength is also your weakness, and the empathic focus can come with a lack of focus on the very performance we aim to impact as measured by hard numbers. Numbers that measure business, operational, or other performance outcomes.
Incorporating evidence into service design is not impossible. At Livework, we have worked hard to connect with business strategists and other numbers-oriented colleagues to make sure our designs are backed by evidence. We have, for example, developed an evaluation model for public health services that bakes clinical and public health outcomes into the process.
However, there is still a challenge in this space. It is partly cultural, as qualitative and quantitative colleagues are very different, so collaboration requires a lot of work and translation. It is also partly about capability. If you are good at empathic research and creative problem-solving, it is a big ask for you to also be good at sourcing and analyzing data.
The challenge this presents to service design can be a lack of connection to core business or operational drivers and colleagues who are driven by these metrics. Our work then falls short of its potential.
The opportunity with AI is to incorporate the models that we have developed into the tooling itself, both structurally and, more importantly, by using AI to do the data sourcing, analysis, verification, and maintenance.
Speed
Service design is built on the method of “slow down to go faster.” We look at the bigger cycles of customer experience and take a systemic approach. This provides “big picture” and “holistic” perspectives that are invaluable to more integrated and strategic thinking. We “connect the silos,” which requires slowing down to collaborate and align.
The challenge is that our pace leads to a mismatch with many business cultures and technology methodologies that are on fast-forward. Again, this is not something that is unknown or has not been addressed. There are successful integrations of service design with Agile delivery methods and fast-paced business approaches that work. The irony is that good service design is more than capable of providing a significant business uplift and a multi-year roadmap. We can fill a backlog.
Whilst there are exceptions, this culture clash is evident. When service design efforts flounder, it is on the rocks of a business culture that cannot wait or a technology operation that bulldozes subtlety. Service design needs speedy translation engines for both business and delivery.
Here again, I think AI can help. Translation engines can be built that make these connections and translations–both to business value and to delivery. By building integrations into the reporting and workflows of these powerful forces, we can build the gears that transition between design, business, and delivery.
Leadership
Service design makes bold claims. We are “end-to-end,” meaning we “encompass the whole service.” This means we cross the domains of all aspects of an organization, from marketing to sales to delivery and support. We “orient organizations around customers,” meaning we are transformative for organizations and how they operate. These things can be true, but they are bold and sound like the role of the CEO.
We have known CEOs who have adopted service design as a core part of how they perform their role, but generally, service design is not in the executive suite, let alone at the CEO’s desk.
Here, the challenge I am posing is less a problem with service design and more an opportunity for service design. What if service design were the CEO? How would we step into those shoes? I genuinely believe that a business that orients itself around creating value for customers, service users, patients, etc., and does it fully will be higher-performing. So how do we achieve this state? I am not here rehashing the tired “designer in the boardroom” debate. I am asking how we make service design a core part of a CEO’s toolkit–how they run the business.
As this challenge is different, so is my hypothesis for AI. I think AI poses a challenge to the CEO: one of control and leadership. With AI, things can get out of control in the “black box,” as teams develop tools that are complex and harder to understand. Technology in a large organization is already a wild animal. With AI, the risk is that it breaks free. The hypothesis is that service design can provide the system-level prompt that AI needs for a CEO to retain control and to lead the business.
Let’s start with an evidence-based blueprint
The three challenges build on one another. I believe that the ability to evidence value early and substantially will open new doors for service design. We do well when our client (internal or external) “gets it.” “Gets it” means they value the human, empathic approach, and they know it will lead to results. These clients are often mavericks who are willing to take some risks and provide cover for the design team. This is an inhibitor of service design progress, as mavericks are not everywhere, and being a maverick is hard work.
So the test is: Can we make a blueprint that provides the evidence that speaks to the business?
AI has the capability to source, analyze, and structure data that most humans, especially designers, do not. I plan to use this capability to complement the value of human insight into needs, value, and experience with a quantitative analysis of how that insight could translate into opportunity.
Additionally, when we have a design solution that addresses human needs, value, and experience, we can use AI to quantify the potential of that solution. When the data is out there, we can more easily and economically find it and employ it. If it is not, then we can surface what we are lacking and design experiments that build the data.
To conduct these experiments, I have two areas of focus where we at Livework have rich materials and insight into the human needs and business challenges–areas where we have had a substantial impact for some of our maverick clients. The first is in healthcare, and the second is with B2B business services. In both cases, we know that our designs worked, as they delivered substantial benefits. For the healthcare organizations, these were improvements in care and accompanying cost savings. For the B2B businesses, our work led to growth in revenue and market share and reduced cost to serve. In both cases, we feel we have insight that would be valuable to a wider audience–more similar healthcare organizations and more B2B businesses.
So the proof of our hypothesis is this. If we build a blueprint for their sector and services, and we augment that blueprint with evidence, then our blueprint will reach a new audience who need strong evidence in order to get their attention.
The article originally appeared on LinkedIn.