Empowering Designers with Data

JASON DIAMOND: Hello, and welcome to Empowering Designers with Data. Iffat and I are very excited to speak with you today. Before we get into this, we're going to do a brief introduction to tell you about ourselves. I will begin.

I am Jason Diamond. I am the digital practice manager at the Atlanta office for Perkins and Will. I have an architectural background. I'm a licensed architect, LEED green associate. Plenty of experience in the industry. Worked on a wide array of project types. Worked with a diverse group of different types of designers, from urban planners, landscape architects. Very happy to be here talking with you today.

IFFAT MAI: Hi. My name is Iffat Mai, and I'm a digital practice development manager at Perkins and Will on a firm-wide level. And I'm based in New York City. I'm also a LEED green associate. And just like Jason, I've got many years of AEC industry experience, primarily in developing tools, custom tools for design applications and working with different designers to streamline the workflow and productivity.

JASON DIAMOND: All right. So today, we are going to talk about several different aspects of what we're going to call design data management here, and share with you what we've learned over several years of capturing and reporting information about our designs. And so over the years, we've tried to automate or simplify this process of capturing the data. And we've created this tool called-- we'll call it Area Sync-- used in Revit and Rhino and other applications that help with this part of the process. So we'll be telling you a little bit more about that, some details about that.

But today, we're going to focus on four key phases of managing design data. And hopefully you find some or all of this information helpful. To begin with, Iffat is going to start talking about connection and integration of the data. And then she's going to talk about how that data gets synced. And then I will talk a little bit about how we start to visualize that data once we have it and how we monitor that data moving forward. So start with this first section. Iffat, go ahead and take it away.

IFFAT MAI: Thank you, Jason. And I'll be talking about connection and integration. So the first phase is connection and integration. By that, we'll talk about how to connect and integrate the program data and building design model data.

As we all know, almost every project will start with an architectural program. The architectural program is really developed during the predevelopment phase of a building project, and it contains a list of building wants and needs, ultimately identifying the scope of work to be designed. So more specifically, it contains the amount of space needed and the relationship required among spaces.

It can also contain additional information relating to sustainability, resilience, site analysis, and many, many other factors that are critically important to our designers throughout the design process.

And most of these design requirement data, they will be stored in tabulated format, much like Excel. So our very first challenge is to connect and integrate these data from different sources with our design model. And this can be very challenging, as the data is often in different formats and is stored in different locations. However, by using APIs and developing custom plug-ins, these data can be easily integrated and synchronized.

We had used Power Query tools inside the Excel to extract relevant data into a room-by-room format, and we feed it into a database. By using Power Query, we really are able to preserve the original data analysis format by keeping it simple and easy for the planners and programmers so they can continue working in the environment they're comfortable with, in the same fashion that they're familiar with.

But our ultimate goal is to take those data and integrate the program into the modeling environment, empowering our designers as they craft the building in 3D and fitting all the required spaces into a new or an existing building. Now, this phase of the design process typically happens in a modeling program, such as Revit or Rhino.

So the first step of connecting the data typically begins with a one-time import of the program data into the BIM model. However, once these program data are imported into the modeling environment, the data connection is usually lost, and the two data does not remain synchronized anymore. It is very difficult to store and manage all the extra data inside the BIM model. And when the BIM model becomes bloated, it often crashes and results in model corruption.

Now, a much better alternative is to collect all the data outside of the application and store them in a cloud database, which can easily communicate with different data coming from different application sources. Now, the cloud data is much more efficient at storing large amount of data, and then provide flexibility, reliability, security, and affordability.

Now, more importantly, you can access all these data through a business intelligence platform, such as Tableau or Power BI.

By using Power BI, which was our preferred platform, we can create interactive dashboard that can integrate the different data between Excel and 3D models to visualize and track all your key measures and to avoid rework.

Now, having an interactive dashboard for the project showing synchronized real-time data from all the relevant data sources, this enabled us to highlight all the key measures and make them more accessible to the entire design team, and even to the clients, without the need for anyone to open an Excel file or 3D models and dig through all the latest, digging through these models for the latest information to prepare a static report.

Now, as Jason had mentioned before, we have created a tool called Area Sync, which consists of many smaller plug-ins that connect all the data from different sources into our central database in the cloud.

So for Excel, we created an Excel plug-in that connects the program data and the model data in a bidirectional fashion via the cloud database.

So our planners and programmers, they can continue working their Excel file while gaining direct access to the latest development of the building design data, comparing the number of rooms that have been planned versus designed, checking if any department are over or under the target area, all while working in the Excel environment, without having to open any kind of Revit model or Rhino model and kind of bothering the design team and saying where we are, providing all these active design data sets available to the programmers and the planners right at their fingertips.

Now, for our Revit users, we have developed a suite of tools that can help control the data synchronization settings for each project, the tools that simplifies the bidirectional exchange of the program data and the model data.

Now, with our data import tools, the designers can import the program data from the cloud data that was uploaded from the Excel into the Revit model and create placed or unplaced rooms, according to the program. All the related data of each room will transfer into the model as room properties.

Now, these dummy rooms can be created automatically using the room target size, and they can be placed on the correct floor level where the room belongs. We also have options of adding room tags to the rooms and placing family and groups of furniture or equipment with a typical room layout based on a room type code.

For Rhino users, we have Rhino plug-ins. And we implemented a similar schema structure that mirrors the program data, providing our designers the ability to visualize areas categorized by levels or departments as they're going through different iterations of their building design.

Now that we connected, the second phase involves syncing the data. Once the data is connected, it needs to be synced to ensure that it is up to date. The value of the dashboard is really in the ability to see the latest information and data from all the sources. So data synchronization is really a critical part of our Area Sync tool.

The data syncing process can be on demand or automated, ensuring that the data is always accurate and current. The real-time sync is on-demand, retrieving the latest information as needed. Now, the once-a-day sync can be automated to grab the project information on the first open of the day, and we don't need to duplicate it.

The Sync on Save feature can also be automated to capture any data changes when a user issues a save to central command. Lastly, the scheduled update. The scheduled update is typically used for our dashboards. And those can be set up on servers to grab the latest data from a database at a designated time and the preferred frequency.

When we started Area Sync project, we wanted to answer the simple question, which is how big is your building. Now, to answer that, we really needed to extract the area information from the model. Now, there are many ways of calculating the building size, but we narrowed it down to rooms and area plans. We wanted to be able to track all the areas in the building as the project goes through different phases of design and to always have the latest tally of the building's net versus gross areas at any point in time.

We also started extracting elements that the project team needed to help to track for counting or cumulative length or total areas for their various calculation purposes. For those processes, we extracted family elements, such as desks, workstations, special furnitures, walls, windows, et cetera. And all using the dashboards, the project team were able to share the result of the element counts and make critical decisions that keeps the project moving on track and on budget.

Now, with our latest version of Area Sync, we now have direct connection with our business modules on the hub. Teams can use as a log in into our secure network system, allowing the teams to connect directly to our firmwide project database and synchronize project access according to the project staffing assignment. We also added default pie chart visualization of area breakdowns, just for the simple area overviews.

Now, in addition to our pie chart visualizer, our design team can further drill down and examine rooms individually or by floor using our beautiful diagram viewer. The diagram viewer allows the users to pick and choose what rooms they want to look at, maybe grouping them by floors or by areas, and then grabbing that information in a much more pleasant-looking space than a Revit scheduler, and making changes and modifying it on the fly.

And for our Rhino plug-ins, our designers are able to assign properties to any geometry objects, so making schematic design planning much easier. Designers now can track the area breakdown just as they are designing and working through their design.

And in Rhino, they can attach property information to the geometry object, like I mentioned earlier, making it easy to track different types of space, space assignment, space type, and assign colors to those spaces. Now, these properties carry through even when an object is copied over and making different, let's say, floors, adding additional floors, or even a complete different building. The pie chart visualizer updates instantaneously to reflect all that changes.

And having our design data synchronized and saved onto the cloud database makes it much easier to retrieve previous design data. So, let's say maybe you want it for comparison purpose, or you want to check for design changes. The project and team can even chart the area size changes over time if needed, as these previous version are readily available at their fingertips. And with that, I hand it over back to you, Jason.

JASON DIAMOND: All right. Thank you, Iffat. Our third phase here, we're going to talk about visualization, or making sense of the data, which in very simple terms like that is the overall goal here. We want to make this data easier to digest and understand. Our endgame here is to make clear and concise reports or dashboards that inform the project team or client about the design itself.

So what does the data tell you? What do you want to see? Use visuals. Use visual types that speak to your project. Remember, the point here is not just to put a bunch of graphics up that all tell the same stats. We want meaningful and accurate information about the project. We have this nice tracer visual from proving ground that shows us a simple diagram of the spaces that are colored by department, in this case. We've got a level slicer on the right side there that allows us to pull up any floor plan, multiple floor plans, and make comparisons, or just look at that one floor plan. And so, we have a broad depth of information that can be manipulated in many different ways here.

Know your basic visual types. The very common types, like bar charts, whether they're stacked or clustered bar charts, donut and pie charts, everybody's familiar with, showing parts to a whole. The treemap visual does a similar function.

And then a simple card, just showing you a piece of data, and making sure that you master tables and a matrix visual to see hierarchies of data. Basically, learn how data flows through all these basic visuals, how to set them up. All these visuals that you're seeing here tell me something about area and departments, but they're all doing it in a slightly different way and a slightly different effect here.

Get to know your formatting options. This is super important. Other people are going to look at this. Get to know how to format colors, units, font sizes, font colors, rounding, decimal places. Clean all that up so that people's attention aren't drawn to those two zeros on top of the area value that we're seeing.

Make this something we want to look at every week, every other day. Make sure your colors are consistent throughout. I'm showing a department on this page here. We want to make sure that between the donut chart, the bar chart, and the tracer that that department is the same color. Sounds simple, but it's something you want to make sure you get this working before you go and share it with other people, and people start using this.

And then conditional formatting, this is very important. This isn't just-- it's not a static report page. When something is going south, or we're getting off of our target, we want some sort of color, or something to bring things to our attention here. And so here, we're coloring the background of this card, whether we're over or under our target.

And then as it gets way, way off target, we're going to get deeper reds, deeper blues, into the purples to tell us how far off we are. Same thing you see in the chart in the table, you see that calculated column is coloring based on how close we are to our target, in that case. So build that in wherever you can. I think the point is to draw attention to these things so that the project team can know where they need to focus their energy to get the project back on track.

And here, we are looking at Revit system families, walls. The project team was interested in seeing these wall types because there were a couple of their wall types that were really impacting the cost of the project. And so they wanted to be able to keep close tabs on these, and note that as the design is changing from day to day, they're sort of realizing how much they're adding or subtracting to this number over time, to keep things in check. So, different reasons for structuring different report pages different ways.

Another use of the Revit data is here, we have furniture families, Revit component families. And we can slice and dice it by level. We have a matrix in the middle there that's giving us our counts. It's giving us a lot of spec information. You can put a nice little image in there, and this is all live, you know. It's getting synced every day. So all these counts are basically getting updated in pretty much near real time.

And then we've got the little planning graphic tracer visual on the right side there that's giving us our general shape of our floor plate, and then placing the locations of all of these pieces of furnitures as dots on the plan.

And then you also want to be tracking any data that you're getting from any Revit add ins. So we, for example, we have an add in our Revit that outputs embodied carbon analysis to show global warming potential based on all of the materials coming from your Revit file. And so here, you see some examples of how we're taking that long CSV file with thousands and thousands of rows, and kind of making sense of it in here, and comparing several projects, in this case.

Build in parameters into your visuals so you can make adjustments on the fly, or use it sort of as a planning tool. A lot of people don't know that you can do this inside of a applications like Power BI. So I think when I first started building these dashboards, that was one of the immediate things like, that's great that I can see this information. Now, how can I manipulate it and change it a little bit?

So you can build these in, and think it's to your advantage to do that so you can plan out several different scenarios. So, don't limit yourself by keeping the data in these native applications. The whole point here is to pull it out, bring it all in here in one place where you can do lots of different stuff with it.

And then, are you meeting your project targets? This is very big with us. We want to make sure we're not just sort of reading what's coming from the Revit file. We want to make sure we get that plan data in there from Excel. So here, you're seeing on the room type level, each row is basically a room type. And we are able to see that nice, round number, the planned area coming from Excel.

And then we've got the area difference that's tracking how far off we are on a room type basis here. We also have the counts of rooms, so we can see how far over or under with the room counts that we are here. So we basically are taking the actual from Revit, the plan from Excel. We're creating a relationship between them. So we can make that comparison.

And then once you feel like you've mastered the basics, experiment with some custom visuals when you feel like you do know enough to jump off into this world. But this is from Chaticulator, is the name of this visual. And you can design lots of different-- there are lots of possibilities with this visual. But here, I'm showing basically, two different plot segments, both tracking areas. The top one is tracking it by the use of the space, and then the bottom is tracking it by buildings.

And you see that it's kind of changing because this is an urban planning project. Our urban designers work in Revit. And it was a heavily phased project with several different phases, so that's why you see different buildings coming on board later on. And all of this, showing you the square footage of how it sort of flows down into these different buildings. So definitely play around with some of these custom visuals when you feel like you're getting to that point.

3D program studies. I've always wanted to view my rooms in 3D. And yeah, think I've been able to do that before with Dyanmo, but it's very nice once you're seeing all these other graphics in Power BI, to be able to see your geometry in 3D.

And this is the tracer visual from proving ground. There's a 3D version of that. It's very nice. When you mouse over stuff, you could add other things. Right now, we're seeing department, but you could be seeing room name, area, target area, things like that. So I would say doing these 3D program studies are very useful here.

And understanding complexities of your data, understand how challenging it is. This work represents an assessment for a school district. The school district had 130 schools, and the assessment for each school was about 70 questions. So we're talking about 10,000 rows of data, a giant Excel file that you probably, you don't want to look at. And so being able to pipe that in here, structure it along with the hierarchy of what's going on here was very helpful.

So understanding any hierarchies in your data, we've looked at departments and room names, sort of parts to a whole. In this case, we have seven regions in a school district, and then each of those regions has clusters, and then each cluster has elementary schools, middle schools, high schools. So we wanted to make sure our colors were consistent when we click on a region. We see those same colors, the orange colors, for example, would be clusters of that region.

And then lastly, we are drawing attention to the lower scores in the middle table there with the darker cells. So we're using some conditional formatting there. And then of course, we have that facility type slicer. We're able to slice and only see elementary schools, only see high schools, in this case.

So that is enough about visuals. We're going to talk about the fourth phase, which involves monitoring the data, or making the data work for you. And think when you first start to look at data in these reports, especially if you're just getting design data from Revit, the first thing you're going to notice is there's stuff missing.

People haven't assigned departments. Here, I see a lot of departments are unassigned. They're blank. And if I click on this row, I can clearly see where they're blank, what levels of the building they're blank on. And I can dig down on the details here, and see actually on those levels what room names don't have departments.

So what I want to do is publish this report, share it with my project team, and get them working on these spaces to classify these into one of these departments that they belong in. So sharing that report, having them fill in the missing details, and on top of that, make sure the team knows-- when it comes to Revit, make sure they're taking care of any room bounding or area bounding issues, and make sure all areas and rooms are calculating an area they're fully enclosed.

And then we also want to avoid duplication of data. This is huge. When you're inside of Revit, when you're looking at a schedule, you're looking at a view, it's not going to duplicate a phase. You're going to choose a phase, and it's only going to show you that phase. You're going to choose a design option that you want to see, and it's not going to show you any other design options in that option set.

So, these are things-- once we take that out of Revit, we may not have that level of control, and we may need to look at these filters in Power BI, and make sure that we're filtering in these three areas in particular, area schemes, design options, and phasing. We want to make sure that things are set. If we have multiple phases, we're filtering to that phase we want to see, and we're not seeing more square footage than we should, in this case. So, a few things here you want to make sure you're keeping an eye on as you're building these reports, and making sure things are filtered correctly.

And then actual versus our targets, we were showing this earlier, but I'm going to highlight the right side here. We've got a simple, overall target here. And down at the bottom, we've got sort of a color coded percentage of how far off we are of that target. We're only at 4%, so it's kind of close to that default green color.

But if this starts creeping below negative 10%, you know, you're going to start see a deeper blue color. And then if it went up, we would eventually start to see a yellow, orange, or red color if we're way off. So definitely build in these targets, even if it's for that one total overall area.

Another example of this is get more granular with it. This is a huge project and a lot of different spaces. And sometimes when you have, let's say, six departments but you may have 600 rooms, if you're off in a certain department and all you can track is your department targets, it may be difficult to find where exactly within that department you're off.

And so getting down to the room type level is where you want to be on the larger projects. That way, you can focus in on which spaces are off, and it's very clear what you need to go in and sort of adjust to get back on target at that point.

OK, so monitoring important metrics on your project, you can do lots of calculations in Power BI. You can create calculations. You can create measures. You can create custom columns. You have so many options. It might be more advanced, but I suggest you take advantage of this. And don't look at Excel as the only place you can do calculations. You can do anything you're doing in Excel in here.

And so, I think it's very valuable to take a look at this and the data that you're working with, maybe you want to create some kind of metrics. Like, we have square foot per seat in here. Counting, just filtered counts. We're filtering all furniture families, but we only want ones of the desk type, in this case. So creating those will go a long way for you.

And when you're creating these, ChatGPT is your friend. When I first started doing this, it took me a long time to figure out how to create the proper syntax for some of these. And once ChatGPT came along, I just-- it's so easy. Any time I'm creating something, I just tell it what I'm trying to do, and it pretty much tells me what I need to plug in here. So take advantage of that, please.

And then tracking changes over time. Throughout the life of the project, projects may go on for years. And we may get to a certain milestone, and the client comes back and says, you know, why are we over budget? We increased scope somewhere. We can actually look at this visual and see exactly when that happened, and what that increase was.

And then maybe go back to my emails around that time and see, oh, yes. The owner was requesting that we added this or this. So I think there's a lot of different applications, and uses, and benefits from being able to track these changes over time in your models.

And then so far, we've been discussing the benefits of using this type of workflow on the current project. But, let's sort of fast forward a year or two. And you've been curating several projects, and making sure that the data is accurate, and you've got several of those of the same project type, several projects done.

Looking forward, we want to start to benchmark or make comparisons between projects so we can effectively plan our future projects. We look at-- when we have a new project coming up, we can look back on the last three or four projects that were a similar size. Look at some of the metrics about that project that effectively could help us plan our next project.

So we see this. We just kind of scratched the surface of this right now. We have several practice areas that are diving into this, now that we've been doing this for some time. But I see this as a natural sort of evolution of things, once you start down this workflow.

And looking to the future, we'll look at things like machine learning and AI, that might help bridge any gaps for spaces or departments that may have been named differently. They had different naming standards. And then I also think later on, we'll be able to use an AI tool like a ChatGPT that's looking at our data. And maybe we want to ask it questions about our data like, show me the last four science and technology projects and the metrics of those. I feel like we're not far off from something like that. So, OK. Yeah.

Just to recap here, we've talked about the connection integration, starting by getting the programming data, BIM data, other data sources. Get them all added to the overall data model, into an app like Power BI to track the key measures and avoid rework.

And she talked about data syncing, getting the latest data, whether the process is automated or on demand, and knowing what types of data to extract from the model. And I talked about visualization, making sense of the data, getting to know the basic visuals and their formatting options. And we showed several examples of how we're doing that.

And then very important, monitoring the data, making sure the data is complete and accurate, making sure we're filtering properly, tracking any actual versus target information, and creating any key measures. So yeah, and the benefits of this process should continue to a benchmarking stage, when there are enough projects to do so.

All right, so that pretty much wraps it up. We hope that this information was valuable for you. And we'd like to thank you for tuning in. If you find this class helpful, feel free to leave us a comment or hit the thumbs up button for this class. Otherwise, we hope you enjoy the rest of your day. Thank you.