Design thinking and Intelligent Technologies

The role of technology in the enterprise has been changing for some time now, moving away from its traditional place as a cost centre to occupy a new position as a profit driver. The force behind this is the new capabilities and business models that intel

While having so many possible problems intelligent technologies can solve opens the door to creative innovation, it can leave you in a problematic place. The lack of a defined process or business function to attach them to may leave you wondering where to begin. This isn’t helped by the nearly constant stream of examples of how these technologies have been applied.

CEOs and boards are taking notice. In a recent Forrester survey of more than 2,000 global business leaders, 40% cited adopting emerging technology as the top driver for changing business models. This new purpose necessitates a new approach—an adaption of how we’ve innovated with technology in the past—and design thinking has a role to play within this.

Achieving new growth through the use of intelligent technology is not without its challenges. First and foremost is the fact that they are not tightly connected to business processes in the way more established technologies are. This makes it more complicated to determine how and where to best apply them. For example, blockchain could be used as a currency, to broker mortgages, to manage cold chain logistics, or for traceability of meat products.

While having so many possible problems intelligent technologies can solve opens the door to creative innovation, it can leave you in a problematic place. The lack of a defined process or business function to attach them to may leave you wondering where to begin. This isn’t helped by the nearly constant stream of examples of how these technologies have been applied.

Many have tried to simply get started in the hope that the value will emerge in time; however, this path is fraught with pitfalls. It can leave your technology landscapes littered with POCs (proof of concepts) and prototypes; the consequence of abundant experimentation that lacks a fundamental proof point: business impact at scale.

With boards facing relentless pressure from shareholders to grow and boards pressing leadership to get moving, the compulsion to take this path this is strong. How do we respond to this pressure without falling into this POC/prototype trap and achieve the ultimate goal of delivering business impact at scale?

Design thinking has always played a pivotal role in the question of “where do I begin?” By being laser-focused on uncovering the end user’s needs, it provides a narrower definition of the problem that needs to be solved. This begins with bringing together the different perspectives of the people involved. Marketers, accountants, developers, executives, etc. all bring unique viewpoints that sharpen the understanding of the problem and help to refine the solution.

For example, the Dutch wheelchair manufacturer Life and Mobility was looking to help long-term wheelchair users be more comfortable while also helping to prevent some of the medical conditions that come with extended sitting. Drawing on the perspectives of nurses, patients, ergonomic therapists, and SAP Leonardo engineers, the team learned about the negative effects of an incorrect sitting position and the extended process of treating the pressure ulcers that emerged from improper positioning.

Drawing on these vantage points, blended with an understanding of the technological possibilities, the joint team recognised that these ulcers were entirely preventable if patients and practitioners had better insights and could deliver more real-time feedback on sitting position. This provided a focal point for the technologies: a mix of IoT and advanced data analytics to provide data about proper sitting positions and reduce the negative effects.

The end user perspective, combined with a clear view of the positive impact the team sought and insights from everyone in the ecosystem, was balanced with an understanding of technology to make this outcome possible. However, while this may have been enough in the past, in the new world of intelligent technologies, we need to go farther.

While design thinking brings focus, we need more than this to break free of the POC trap. We must consider two additional perspectives to catapult a great idea into one that delivers business value at scale:

1. Intelligent technologies and the digital platform. Often intelligent technolo-

gies are approached in isolation, separate from the core business they are trying to affect. However, true scale will only come from considering how you connect or embed these technologies into established systems. For example, IoT is nothing without a digital platform to make sense of the data it generates, and machine learning is nothing without data. They are reliant on a digital platform to generate value and this needs to be inherent in the design. For example, the shoe giant Adidas has layered machine learning on top of supply chain systems to create “speed factories” that deliver personalised shoes. It reduces the time it takes Adidas to turn trends into shoes from a typical 18month time frame down to days. This innovation is only made possible by combining the digital platform and intelligent technologies.

2. Scale (from the start).

Three questions have been the mainstays of design thinking for some time, namely, is it desirable (are we solving the right customer problem?), is it feasible (will the solution be practical and workable using the assets and capability we have today?), and is it viable (will it deliver business value over time?). However, to escape the POC trap, we need to add an additional perspective: is it scalable? In other words, can it be scaled from a technical and business perspective? This is an important consideration to determine the business and technology capability needed to deploy it across locations and geographies. Moreover, we need to think about scalability right from the start. Regardless of where we begin, even in early explorations, we must ensure that critical questions, like the cost of scaling sensors across locations or the effort to maintain a blockchain consortium, are known and addressed. It breaks the innovation free of the POC trap by reframing the role of the prototype from being its own endpoint to merely a step on the way towards scale.

As companies increasingly look to growth and the application of intelligent technologies to enable this, it’s obviously important that we don’t forget the role of customer value and user stories, but these are meaningless if we cannot scale them. Adding these two vantage points, the blending of intelligent technologies and the digital platform, and adding a further perspective focused on scale, is the path by which we’ll be able to break free of the POC trap and deliver the impact we all aspire to create.