Innovation and Predictable Data

 Brett Settles, Global Director of Customer Success

How to trust your data.

As Revizto delves into providing more functionality to how our industry uses data, the old, tired and yet true phrase of “Garbage in, Garbage out” is still present in my mind, as it has been throughout my career. The industry is making efforts to combat this with ISO 19650, PAS 1192. There are additional efforts to get to some level of standardization with these practices across file formats such as IFC and BCF.

I always think about how standards have actually played out in my career. Let me tell you this, it is not the idea of standards that causes us problems but more our ability to effectively use them and enforce them to create a culture of standardization. It’s true that with any deliverable we create, regardless if it is drawings, asset data, models – the more standardized we become on all practices, the more predictable the outcome is. With a more predictable the outcome, it is easier to both manage and trust the information that is provided—having confidence in the data matters.

New technologies in the AEC industry (including us), are often striving for more automation and automation needs reliable input. Automation drives efficiency and that efficiency allows the team to focus on the bigger and more critical items, and not the verification of tedious items and what should be a known variable.

Time is regularly wasted trying to verify data across teams to avoid costly mistakes and reworks.

That being said, all of the project information needs to be thoroughly vetted. But, this is not something that every team member should be responsible for and have to change every time they have to add two numbers together from a coordinate calculation, when the providing model-based estimation or simply have coordinate two pieces of equipment.The amount of time stacks up and time is money. Standardization can play a massive role in relieving the daily practice of verifying information and in turn, results in minimized stress. More importantly, more efficient practices allow users to focus on their jobs and not tracking down other colleagues to verify if something is correct or not. This applies to everything from questions like “What text style should I be using” or “Is this item located correctly in the project” to “Can we trust this model-based estimation”. All of these questions play large roles in how confident you are in your final deliverable.Can we trust the coordinates displayed for this flow line, and if not how much time does confirming these numbers take?

The Best Tools Won’t Save You From Yourself

I have come across this many times. There are many things in life that make us more efficient. An example would be a Multimeter. If you take this tool and hook it up to an electrical device, it will give you results you can use because the device knows what to expect, an electrical current. It then knows the types of information that will be valuable to you, such as voltage, current and resistance. Now if you take that same device and touch the conductors to a pressurized water line, it would return nothing.This is because the device has no way to retrieve information from the item, and even if it could, it would not be programmed to translate it into useful data. The reason I bring this example up is because data is no different. We have to put the right tools in place to retrieve the correct information, to complete the job we were hired to do. Using data is much the same; the tools we put in place have to be able to retrieve and translate the necessary information into something useful. Standards address this directly within BIM/VDC by creating an environment where the tools know what to expect and can translate that information into something digestible like a search set, report, data visualization, or a task without a human needing to decode the situation manually.

Innovation Based on Automation

One of the easiest ways to reduce labor costs is to take mundane repeatable tasks and leverage innovation to complete these tasks for you. This is why we have things like Dynamo, CNC machines, iRobot vaccums, endless car warranty robocalls, and my personal favorite Pellet Grills. I mean I could put chunks of wood on the thing myself over and over again but I don’t want to. Once again, these things work because the devices know what to expect. By standardizing not only our drawings, data, and our processes, we can begin to link together a chain of events that play off of one another. This is the reason the metadata in Revizto’s Stamp functionality plays a huge role in giving hours back to our clients. The system knows what to expect with a single click and translates that issue into the correct filter, report and dashboard. This functionality knows who the issue is supposed to be delivered to, and enables the end-user to understand when someone has dropped an icon in a model.

Automation not only drives results but the ease of use. Imagine a superintendent drops a stamp on a drawing and instead of all of the above happening, they have to input everything manually. This causes a greater risk of human error, a steeper learning curve for the tool itself and also takes more time from their day – all of which can result in frustration. By creating standards, we are enabling the tools we spend money on to work harder for us. In Revit we can standardize our sheets, families, view templates, schedules and the list goes on. It provides us with great value to know we can fire up the reliable company template to get going.

We standardize our project management systems, our excel spreadsheets, our HR documentation for one simple reason – it saves us time. It also allows us to stay organized, to trust our ears and our eyes, and enables us to know where to go to get what we need. What about the process outside of creating or documenting, though? How do we standardize and automate our communication and accountability when we are not filing something in the right place or creating something from a predetermined set of parts? What about the grey area in the middle where communication happens in the form of emails, phone calls, IM’s, napkin sketches and all of that, as we work through our day to get from point A to point B. We are working every day to encompass this area into something that can be fully standardized, replicated and automated. Our innovation thrives under predictability, as do many of the tools in our ecosystem. But more importantly, so do the users.

In the latest Revizto release, we have begun to connect the dots and while we can incorporate many standards of our own around communication and model data, the standards preceding us can have an enormous impact as well. Predictable data is a big concern in our industry and is also a massive factor in how well these innovative tools work for you. The more predictable the information, the more value you will, in turn, receive from the innovative tools. However, there is no one place to do all of this. It is an interconnected process driven by the users across their tech stack. The further down the line the tool, the more susceptible it is to suffer from an unorganized process in the beginning.

Wrapping it up

This blog is meant to get you to think about how important it is to create straightforward and easy to understand standards across your entire technology stack. Many situations can fail simply because there is not a clear path of information from one process to another. Heck, even we are continually trying to improve our internal information flows. It is the very basis on which these tools, specifically Revizto, work. It’s the reason estimating software fails to pick up modelled-in-place elements. It’s also the reason a point was laid out wrong in the field, the reason a dimension doesn’t look like all the other dimensions on the sheet, and why improperly defined elements are disappearing from your search set. Your organization needs to look at taking full advantage of the investments you are making in innovative technology. I strongly urge you to take a long look and these few points. Where does your process begin and end? Who is involved, and what can be standardized internally and with your business partners to create a culture of predictable data? In the end, this will not only be a massive boost in the ability to trust your information and models but will also really open the floodgates of efficiency via trust.