Visitors of this blog know that I often discuss digital transformation by reflecting on experiences working with other businesses. As a consultant I have personally seen companies both thrive and struggle with the changes that new digital workflows, technologies, and skills are bring to the workplace.
Like many of the businesses we consult with, Proving Ground is also not immune to digital transformation. As a small business, we are also challenged to keep up with the latest trends, adapt to industry changes, and strategically look at how we can best take advantage of technology. We don’t claim to be doing everything perfectly but we can claim to be eating our own dog food. A primary driver of our of our business is to be agile and critical of our processes and always look for ways to continuously improve as we grow our capabilities.
As a small business, we are also challenged to keep up with the latest trends, adapt to industry changes, and strategically look at how we can best take advantage of technology.
In the interest of sharing our experiences, here I will cover some of our own digital transformations and reflect on how our approach is shaped by leveraging data and using processes for continuous improvement…
In the building industry, I feel as though data is still discussed in very abstract terms. It has become fashionable to make general proclamations about an organization’s data such as “We have a lot of it” and “we just need to be using it more”. This perception often trivializes the effort involved in procuring really good data and putting the data to meaningful use where it can positively impact business processes. This past year, Proving Ground made several purposeful investments in our business processes that are changing the way we are collecting data and putting it to work.
First, we have continued to develop our Minecart platform for internal and external use. In 2018, we have developed new automation tools that allow us to rapidly harvest object data and relationships from Revit and IFC files into centralized databases. We are using this data to support quality control processes and also support facility management processes. We have observed that low data quality is a central hindrance to being able to leverage data-driven workflows. This observation has led us to also develop preliminary workflows that position collected facility data as training sets for supervised machine learning for data cleaning procedures. Our approach to rapidly harvesting data from model files has allowed us to rapidly analyze projects and make targeted recommendations for improving our client’s processes.
Our approach to rapidly harvesting data from model files has allowed us to rapidly analyze projects and make targeted recommendations for improving our client’s processes.
Second, we wanted to better understand the reach of our popular free and open source tools. While platforms, such as Food4Rhino and the Dynamo package, manager provide some nominal statistics of downloads, it has not been clear to us how often our tools are downloaded and where these downloads are coming from. In the last year, we started to deploy installers that request basic information from our users. This has helped us to understand installation frequency, tool popularity, and where our users are in the world (at a country level).
Basic data about our tools has helped our business start to quantify our reach in the world
Basic data like this has helped our business start to quantify our reach in the world (assuming that people are honestly submitting information!) We are excited to observe that our free and open source tools are used in 202 countries and experience up to 230 installs daily – not bad for niche software. This information is also giving us a good picture of where our future development energy should be put to support our audience. For example, LunchBox for Grasshopper is by far the most adopted tool in our portfolio – outpacing the Dynamo version by 4 to 1.
Reusable – and Improvable – Processes
The most common excuse I hear for the lack of automation and digital adoption in architecture is: “Every building is unique. We do one-off designs.” This statement is used to justify lack of standards adoption to dismissing the potential to introduce automation into the design workflow. I have always felt these arguments held little water. When I first entered into the workforce as a designer, I immediately recognized the abundance of wasted time and energy that would go into repetitive tasks and a lack of mature repeatable processes. This arguably contributed in reduced design deliverable quality and very tired design teams.
When I first entered into the workforce as a designer, I immediately recognized the abundance of wasted time and energy that would go into repetitive tasks and a lack of mature repeatable processes.
When it came to designing my own creative business, I wanted to build the business around fundamentals of leveraging reusable – and improvable – processes. Years ago, when I first developed LunchBox for Grasshopper, my motivation was to capture common computational functions that I frequently used in concept design and make them into reusable components. More recently, our Conveyor tools – which create direct connections between Rhino and Revit – were developed first and foremost as a reusable codebase from which we can build custom project solutions.
Creating reusable processes is more than developing tools. It also means establishing consistent approaches for managing and executing our work. In nearly 4 years of being in business, I can see a clear trend in how our contracted scopes of work have matured to reflect well established working methods allowing us to deliver faster, with less cost, and increased quality. For example, our research in mesh-driven BIM workflows we first implemented on the Gilder Center for Science, Education, and Innovation allowed us to accelerate our development of robust geometry tools that would later be applied to the Lucas Museum of Narrative Art and the Las Vegas NFL Stadium. Each project was immensely different, but our investment continuously improving our digital workflow allowed us to deliver better outcomes across each project.
Keeping a Critical Eye on What Works
The topic of Digital Transformation brings with it a great deal of hype with it – especially for new technologies. New tools are entering the marketplace daily and I often observe technology enthusiasts becoming enamored with questions of “what’s new?” rather than “what’s good?” or with “what works?”. With Proving Ground we are chiefly concerned with transforming our work – and the work of others – by orchestrating digital transformations that realize meaningful solutions to prevailing problems. To me, that means being critical and selective about our digital tools, building on the strengths of our knowledge, and focusing our research on areas that will help us critically evaluate new trends relative to how they will help us be better.
We are chiefly concerned with transforming our work (and the work of others) by orchestrating digital transformations that realize meaningful solutions to prevailing problems.
In Kevin Kelly’s book What Technology Wants, he reflects on his time spent with the Amish noting that “Like them, I don’t want a lot of devices that add maintenance chores to my life without adding real benefits. I do want to be choosy about what I spend timing mastering.”
When it comes to pursuing digital transformation and all of its potential, perhaps we can all take an unlikely cue from the Amish – keep critical eye toward our tools what works for us.
How we can help…
- Define your data innovation strategy
- Create tailored solutions with software customization
- Support the digital workflow with project consulting