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The scene is familiar: a technology leader is presenting a proposed implementation of a new platform to the stakeholders in their company. They share how the technology will result in ROI through new efficiencies and speed. The price? Expensive. But the cost is presented as a boast of the organization’s willingness to take high-dollar risks to be competitive. “This new investment will scale current processes and change the way we will work,” the leader says with optimism. “If teams don’t get on board, we will be left behind and competitors will surge ahead. The business will lose. Someone else will win.”
Today’s processes? Broken. Old. Limited. Obsolete.
Tomorrow’s processes? Streamlined. New. Scalable. Adaptable.
There is some truth to narratives like this and even many of our own consulting stories and narratives follow similar patterns. However, those truths are often overly simplified to make a complicated idea easier to consume with a sense of urgency for action. This is most certainly exasperated in the era of social media sound bites where binary stories of digital “winners vs. losers”, “new vs. old”, and “adapt or die” are dominating the discourse. It gets clicks… but it’s far from the full story.
The realities of any digital transformation are far more nuanced, rife with tradeoffs, and non-linear in their implementation roadmap. To unpack this underlying complexity, I will explore three prominent fallacies that are present in today’s technology discourse and illustrate concepts for keeping your own strategies grounded and effective.
Fallacy 1 – “New equals Progress”
If there is one bias in the world of technology it is for the new. New is better. New is the next generation. New is progress.
Over 13 years ago, I was working on one of my first plugins for Grasshopper called Slingshot. The idea was to create workflows between computational design and Relational Database Management Systems (RDBMS). The plugin included tools for formatting SQL commands and exposing read/write connections.
RDMS systems were–and continue to be–extremely mature and reliable technologies for structuring high volumes of data. They originated in the late-60s and early-70s (also known as the ancient 1900s).
At the time of my development, ‘NoSQL’ solutions like MongoDB were all the buzz and becoming very popular for handling unstructured data. “Why aren’t you developing for NoSQL instead. SQL is old. NoSQL is the future!” was a common question from my savvy colleagues. My answer was simple: SQL was mature, widely understood, and the bedrock of data systems. Why chase the new thing when the old thing more than satisfies the objective? Over a decade later, SQL remains the dominant database solution and many of my team’s current developments remain based on this 56 year-old technology.
Had I become enamoured by the hype of a new trend, I would have been distracted from weighing important considerations for maturity, reliability, and suitability for my own use case.
Of course, this is not an indictment of NoSQL solutions which now has a well-established place in the data ecosystem. However, had I become enamoured by the hype of a new trend, I would have been distracted from weighing important considerations for maturity, reliability, and suitability for my own use case.
Fallacy 2 – “Scale is Legitimacy”
The attribute of a technology solution’s scale is often correlated with its perceived value or validity to an organization. How many users does the solution serve? What degree of scope does it have within the organization?
Over the years, I’ve observed–and been a part of–various data warehousing, data centralization, and data normalization efforts. A common strategic tactic is the process for scaling the availability of important data within the organization to support decision-making. These kinds of efforts have often brought me into direct dialog with stakeholders that have, for years, utilized their own ‘point solutions’ in the form of personal spreadsheets, macros, and reports. The benefits of an organization-wide centralized data resource may seem implicit by virtue of their size and scope. However, it is essential to recognize that the ‘small scale’ assets, however limited, have delivered proven value to their users and often at a fraction of the cost of an enterprise system.
Every ‘large scale’ solution will inevitably confront that it will be unable to fully account for every edge case, productivity gain, user preference, and novel feature present in individualized toolkits. For many users, the legitimacy of a solution is not a factor of scale, it is a factor of usefulness (scale be damned!)
For many users, the legitimacy of a solution is not a factor of scale, it is a factor of usefulness (scale be damned!)
More, bigger, faster does not automatically win the day: any solution needs to be aligned with the expectations of the user with clear incentives and motivations for engaging in a broader change in process. Even then, it is also likely that small-scale solutions, hacks, and workarounds will be the things that help calibrate large-scale investments into truly valuable business assets.
Fallacy 3 – “Adapt or Die”
I’ve learned that the CTO’s slide deck is sometimes an interesting place to find simplified misreadings and misattributions of Darwinian theory. On more than one occasion, I’ve seen some variation of an appeal to fear proclaiming “ADAPT OR DIE!”. Years ago, I would see it appear in slides about moving from CAD to BIM. More recently, I’ve seen this theme re-emerge in the context of Artificial Intelligence. The premise is straightforward: using the latest technology is required for a business to adapt and survive. Anyone who doesn’t get on board with the new tech will find themselves obsolete.
Afterall, who wants to be obsolete? I don’t.
But this is a great oversimplification of Darwinian theory. Moreover, it’s generally quite a logical leap to apply metaphors of natural selection to a technological marketplace. Regardless, let’s entertain this premise a bit further…
What is missing from this narrative is that natural adaptation is something that depends heavily on environmental context and pressures. In contrast to what the marketing might tell you, the availability, popularity, and capability of a given technology does not automatically equate to the general suitability of that technology for every business, of every size, in every market. While many architecture firms have adopted tools like Revit as their software of choice over the past two decades, it is notable that there are also numerous design and construction companies that continue to operate successfully with CAD.
The availability, popularity, and capability of a given technology does not automatically equate to the suitability of that technology for every business, of every size, in every market.
Ultimately, how a business adapts to change is highly contextual and grounded in the particulars of their circumstances. A 20-person boutique practice specializing in residential design is going to have a very different technological roadmap than a 2000-person multidisciplinary global practice. Even among similarly-sized practices competing in similar markets, the specific attributes related to operational structures, client relationships, and scopes of service will shape the specifics of how they will evolve.
Key Questions for your Strategy
There is truth to many of the technology narratives found on social media and in marketing materials often do not frame the full story. Companies use simplified appeals to newness, scale, and even fear to motivate interest, clicks, and sales. When presented with a technology opportunity, I propose asking the following questions:
- Are you chasing newness in lieu of researching the best tools and capabilities that fit your objective? You might find that you are best served by boring (but highly mature) solutions.
- Are you weighing potential tradeoffs between scale and usefulness in your technology implementations? You might find that the pursuit of scale undercuts the current efficiencies present among your team’s workflows.
- Is your strategy to adapt and evolve suitable for the context in which your business operates? Numerous factors contribute to how your business responds to change. A technology that is working for your peers might not work for you. The particulars matter.
How can we help?
Proving Ground specializes in helping AEC organizations navigate the complexity of digital transformations including the impacts on people, processes, and technology. We work with our clients to explore new digital trends and evaluate their potential impacts on businesses and projects. If you are looking for unbiased, well informed, human-first guidance, contact us!