DLR Group’s Applied Research Leader, Premnath Sundharam, AIA, identifies new business models for design innovation.
The recent Design Futures Council Leadership Summit for Environmental Responsibility in 2020 turned our attention toward technology’s role in the business of design to optimize design processes, construction, and operations for sustainable outcomes. While the summit provided insight and tools to support this effort, we recognize it will be a slow ascent with many small steps to achieve a collective, actionable commitment in environmental responsibility.
These discussions supported how to track and move toward sustainable goals and prompted new ideas about what lies beneath the practice of design. This opened the door to exploring business models that can shift the industry into high gear to accelerate the desired outcomes of environmental responsibility through design innovation.
Adopting a framework for design innovation can empower the industry to retool itself by transforming its business value propositions for environmental responsibility. That begins by identifying ways to act on that responsibility by creating a culture of design innovation through data analytics, practice-based research, and unique partnerships.
Environmental Responsibility and Systems Thinking
An understanding of environmental responsibility tells us that everything is interconnected. Modern science addresses this interconnectedness through the concept of chaos theory’s “butterfly effect,” which suggests that a small change can result in unanticipated outcomes in systems. Designers need this state of mind to address today’s environmental and social challenges. We cannot operate in isolation. If we don’t appreciate the interconnectedness in the world, we will never be open to seeing cause-and-effect connections in broader contexts.
Discussions of a broader, higher view that connects environmental responsibility to systems thinking, might imply simplifying our focus and our processes. Paradoxically, this connectedness to all things calls on us to embrace the complexity inherent in a multi-layered, multi-perspective, multi-engagement world reality instead of shying away from it.
How does such belief transform our responsibility? It begins with a collective commitment to systems thinking. For example, at DLR Group, advocating for the planet, communities, and climate change is a fundamental tenet of our business success. In defining Sustainability 2.0 within the firm, we explored a more holistic and connected framework based on the scale and tiers of impact of each design decision. Connecting these factors helped us better understand their relationships and explore opportunities to build capacities for healthier interactions. This moved us from simple environmental consciousness to a more complex, connected level of systems thinking.
Relationship as the Foundation of Systems Thinking
The culture and commitment to systems thinking encourages inquiry, deepens purpose, and identifies emerging relationships before considering potential solutions or tackling traditional tasks. But convincing designers to let go of task-focused design is a giant leap. For instance, a design choice to generate more electricity than required to operate a building can be delivered through a series of tasks. But it could have more impact if we were to consider the neighboring community’s health benefits if the excess electricity were to be offered to the community, especially in communities where power interruptions are frequent. These kinds of beneficial systems effects require asking questions beyond: how do we deliver a single, self-focused solution?
Understanding the social and environmental contexts of design projects opens the doors for new levels of engagement through exploration, deeper empathy, and a stronger sense of environmental responsibility.
The Challenge of Design Innovation
But how do we create room in the design process to allow for such explorations when our current business models are based on paid-for-time tasks rather than paid-for-value knowledge?
And how do we ensure our workforce has the skills to navigate such complex, connected data points?
If we develop tools to help clients navigate and prioritize the connections important to their stakeholders, we can respond with design solutions that look through all three lenses − social, economic and environmental impacts − at the same time. Applied research is an effective tool to help us understand cause and effect in the real world and empower us to act on our environmental responsibility.
Four Business Models for Systems Thinking
To amplify this approach across design practice, we need business models that allow for exploration by design professionals who can intelligently and intuitively engage clients and their stakeholders during design process.
Traditional design industry business models favor problem solving over inquiry and exploration of inter-connected issues, or as some call it, “problem seeking.” Designers are inclined to offer solutions over exploring questions. A client (for a building) or a manufacturer (for a product) typically has a set of problems to solve, whether it’s getting into a new building quicker or getting a product to market first. In either case, sheer market economics drives down the level of problem seeking allowed before a set of design solutions is devised. But by employing a problem-seeking approach, we begin to understand the relationships. As a result, our solutions become richer, more regenerative and more sustainable. As the value of design continues to be commoditized, how might we pause to understand the connectedness of every design choice we make?
Every business model considers two aspects of this question, the traditional sides of the economic equation:
• Demand for Systems Thinking: How do we drive the adoption of systems thinking − not just within the design practice, but with every stakeholder group?
• Supply Skillsets: How do we ensure there are enough skillsets in the workforce to tackle complexity, reconcile differences, and provide clarity?
Let’s address this equation by first understanding the business model for a typical design practice using a value proposition to illustrate the needed change in perspective. The graphic below reflects the evolution from task-driven business models to value-driven models in four steps.
1. Task-Based Model (Production Driven)
For a design practice, the primary deliverable is a set of construction documents for building designs. In this business model, driven by contractual deliverables, most revenue is earned for tasks that add little value to the primary problem identified by the client. This model allocates less time for understanding questions and potential problems before quickly developing strategies to break down the problem. Analyzing the benefits of this model tells us:
- Demand for Systems Thinking: Demand is low as the focus of the business is to quickly arrive at solutions. Data handling is siloed. The business value proposition for systems thinking is not clearly understood.
- Supply Skillset: Expertise and skillsets for the workforce are focused on solving problems at a micro-scale – this explains the diversification and compartmentalization of design services that has allowed for commoditization over recent decades. Sustainability design consulting is a great example — the basic skillset for sustainability continues to be disengaged from traditional practice skills. This is true with many other skillsets such as commissioning. The solution is not to have everyone trained and adept in everything, but rather, to translate knowledge between silos and bring it to bear in seeking better problems through inquiry.
- Suggested Actions: Establish routine processes that bring knowledge silos into conversation and inquiry around whole projects. Through these regular dialogs, spotlight the need for multiple perspectives from various skillsets and engage more of your workforce in problem seeking and collaborative solving. Complete organizational buy-in and commitment to a definition of environmental responsibility is needed in this model. The next most important action is to recognize the shape of the revenue-creation model, which enables assessing the skillset of the design teams through the systems thinking lens.
2. Smart Model (Data-informed, Practice Driven)
Making time for problem seeking isn’t simply about adding more time to project timelines. Market economics won’t support that yet. To solve that condition, in this model two key initiatives must happen concurrently:
- Save time (and hence revenue) for problem seeking at the top of the triangle at the beginning of the value chain by applying machine learning, smart analytics, and other automation techniques at the bottom of the triangle and at the end of the revenue chain.
- Improve Capacity for system thinking within teams to take full advantage of the saved time/revenue. Design team skillset education and improvement should be an inherent part of the smart model transformation. The result reshapes the revenue-creation model from a triangle to a trapezoid – the problem-seeking phase of the work expands while solution generation becomes more streamlined.
The product of this automation initiative is the generation of smart data by creating relationships between data sets. For instance, BIM data is widely available on every project. However, the data typically lives on its own, unconnected to other available data. What if we added relationship connections to the BIM data?
As an example, take two spaces in a building that serve different purposes – a theater/auditorium and a maker lab in a school. If we analyze all the school projects we have designed and look at the spatial relationships between these two spaces, our analysis might determine a “cause and effect” on what combination of space planning provides the best outcome for space use and community engagement. This is a simple way to address space resource efficiency and community partnership simultaneously. As a further step, this data relationship could be coded to the data set to make the data smart.
- Demand for Systems Thinking: With tangible evidence on time savings in automating tasks that don’t add value to the client’s primary challenges, resources can be reallocated to focus on problem seeking. This requires changes in project management and leadership.
- Supply Skillset: Technology can assist in numerous ways to increase the culture of curiosity to learn more about the connectedness with our design choices. Three ways technology can influence this learning culture include: – Access to meaningful data: Collating all the data within an organization into a data warehouse is the first step. This creates opportunity to look for data sets typically on the periphery of design models, such as GIS data on socio-economic conditions of a project location community. Opportunity to create connections abound between a design consultancy’s data warehouse and existing publicly available open data sets. – Ability to visualize data: With the advent of data visualization, we can communicate complex data sets tailored to an audience to enable systems thinking. Tools like Microsoft’s PowerBI democratize this ability to visualize complex data. Systems thinkers will naturally leverage such technology and offer this high-value service to their clients. – Learning management tools: Amidst so many distractions in today’s work practices, continuous learning must be a priority. By leveraging the best learning management technology, success stories on the application of systems thinking can be promoted to increase demand.
- Suggested Actions: Valuing the opportunity that design data can provide to fundamentally reallocate resources toward problem seeking is the most important action in this model. If the value proposition is clear, then setting the data infrastructure to enable access to data, visualizing data, and learning from innovators will naturally follow.
3. Intelligence Model (Applied Research Driven)
The next model in this transformation is to leverage the smart data and turn it into intelligence. Smart data is just the tip of the iceberg. To grow into a model leveraging intelligence, we need to create technology platforms that mine the relationship data sets and pull insights forward to make informed design decisions.
In the example above, when we design the next school project, if the community identified skills training through maker labs as an economic development opportunity, then the intelligence engine could offer ideal relationships between programmatic spaces based on relational data logic, set alongside existing public data sets. This is the most challenging part in this transformation and requires methodical evaluation of value propositions by sifting through the data noise. The complexity of data sets available through design projects is monumental, but not insurmountable.
While we focus on creating intelligence, we need to increase the value proposition through innovation. Enter applied research. Practice-based research or applied research is fundamental in identifying practical, scalable innovations in design, construction, and operations of the built environment. As we acknowledge a sense of urgency toward climate change, our industry desperately needs to find ways to apply academic research into design practice to overcome the slow adoption rate inherent in our risk-averse industry.
The goal in this model is to transform the revenue generation model from a trapezoid shape to a rectangle – equal revenue generated from problem-seeking services and problem-solving services with the aid of data intelligence and a culture of innovation.
- Demand for Systems Thinking: When the design practice begins to co-exist and thrive with intelligent data platforms, the confidence emerges to manage complex design challenges. Demand for systems thinking and problem seeking will be fueled by evidence that design innovation influences outcomes in a positive way. Validating this evidence-based design practice is critical in building credibility with clients on the value proposition.
- Supply Skillset: In this model, we turn curiosity into practical design innovation. That can be done by simultaneously focusing on celebrating design innovation culturally in two ways. – Maker Culture: How do you allow curiosity to manifest into a real-world application to solve a design challenge? Enabling design teams to experiment with new technologies is a concrete way to transform the curiosity culture. For example, when I stumbled upon a phase change material (PCM) product at an AIA convention in 2015, I immediately requested a sample. With a small team we built a small-scale mock-up-testing apparatus equipped with sensors and measured the performance of the product. We were stunned to see the product work in maintaining temperature more efficiently than the control. This led us in 2017 to launch a multi-year research on validating the application of PCMs as an effective energy efficiency and thermal comfort strategy. We now include this design innovation in our tool kit of strategies. – Materials 2.0: In comparison to other industries, the design industry being a risk-averse industry has slowed adoption of technological development in new building materials. Many new materials face the brute reality of the design industry’s resistance to change. However, to overcome the primary challenge of market adoption, the industry must identify ways to minimize risk in applied research. As design teams expand their material palette, by connecting the dots with environmental, social, and human health issues, we can turn curiosity into practical design.
- Suggested Actions: Creating a transparent culture to experiment and fail is the key to success in this model. Establishing a framework for applied research and allowing design professionals to access research resources is necessary. Opportunity to establish the foundation for partnerships with manufacturers, construction partners, and academic partners will emerge with this transformation.
4. Design Value Model (Collaborative Partnership Driven)
The design industry is migrating toward alternative construction delivery models such as mass fabrication and robot-aided construction. By the time a design practice enters this transformational model, alternative construction delivery methods will reach new heights. How can we transform the value proposition?
The revenue generation in this model will rely on identifying challenges and priorities of clients, stakeholders and the environment early in the design process. In most cases, before the design process. The execution of design into construction and operation will be a collaborative partnership with manufacturers, fabricators, and building operators. Opportunities to reduce waste, address health, and promote equity are ripe to accommodate partnership in the delivery of buildings.
- Demand for Systems Thinking: A considerable portion of revenue will come from advising clients on whether to build or not as well as providing services and products associated with their ecosystem. For example, indoor air quality services can assess the environmental quality of existing buildings aiding in the conversation of renovation vs. demolition. Similarly, monitoring-based commissioning extend a typical design project contract well into the operations of the facility aiding building operators in proactively managing their portfolio. These are just a few examples of opportunities to become a client’s trusted advisor in supporting their organizational success.
- Supply Skillset: Two primary skillsets needed in the design-value model are future casting and partnership building. 1. Future casting builds on traditional forecasting techniques that organizations already use by analyzing deeper relational data between human behavior and the built environment. This skillset requires a fundamental understanding of organizational success and the ability to bring multi-disciplinary perspectives to future trends and insights. 2. Building partnerships: The challenges of design thinking to impact climate change and environmental responsibility call for a matrix of partners in various configurations to improve our collective skillset for holistic solutions: a. Horizontal Partnership – peer-to-peer within the design profession. What is the opportunity for collective value proposition? b. Vertical Partnership – within the construction industry. What is the opportunity for fabrication, automation and deep integration of the entire built environment ecosystem? c. Diagonal Partnership – outside of the construction industry. Reaching across lines may offer the most powerful opportunities. The construction industry has continued to rank the lowest in terms of productivity gains. If we don’t partner for lessons learned from non-construction entities and change our trajectory, disruption from outside threatens our services.
- Suggested Actions: Creating a network of collaborators is the most important action in this model. Partners can include government agencies, economic development organizations, impact investors, community organizations, etc. The opportunity to impact with a deep sense of environmental responsibility amplifies by a factor of 10 when collaborators expand the reach of design innovation.
The Path Forward
These business models and suggested actions may appear as a sequential growth pattern. However, they can also occur simultaneously depending on the organization’s commitment to tackle them together and the leadership capital to address them effectively.
Yes, everything is interconnected. The path is wide open for the design industry to transform itself and accelerate environmental responsibility through a new business model. Amplifying the opportunity for transformation involves improving workforce skillset in systems thinking, deriving intelligence from data analytics, scaling design innovations through applied research, and collaborating with partners across and beyond the design industry.
Systems thinking is the heartbeat of this transformation. It requires the ability to navigate complex relationships to inform a resilient, regenerative and sustainable future. If we rethink our value propositions, we can create a more connected world that is better equipped to accelerate environmental responsibility and that is fueled by a commitment to act with systems thinking.
Senior Principal Prem Sundharam, AIA, is an internationally recognized thought leader on sustainability and evidence-based design. As DLR Group’s Applied Research Leader in the Research + Development Studio, and former sustainability leader, Prem collaborates with design teams to develop long-term strategies for a more environmentally responsible design practice. You can reach him at psundharam@dlrgroup.com