ARGUS Product Management Presents: Guide to Understanding Your Data Flows
ARGUS Product Management Presents: Guide to Understanding Your Data Flows
Altus Group Product Manager, James Hutton recently presented at Propmodo’s, Building the Future event, that took place during New York Real Estate Tech Week late last year. The presentation, “Guide to Understanding Your Data Flow,” provided some education and insight on the integration landscape in the CRE industry and what you need to consider before embarking on your own integration project.
Watch James’ full presentation or read the transcript below.
“Guide to Understanding Your Data Flows,” Transcript
Today, what I want to talk about is the topic of integration in commercial real estate. Integration is a key concern when it comes to commercial real estate and the reason for that, is that business processes in commercial real estate involve large numbers of people, and teams, and organizations that need to work together to make things happen.
A really great example of that is the acquisitions process. Think of all the steps that need to happen for an investment manager to acquire a commercial real estate property. It starts with the discovery process, where the buyer will work with a number of brokers to source potential acquisitions. Once properties get to a certain stage in the acquisition pipeline, they’ll undergo an underwriting process where detailed financial modeling of the building will occur. After underwriting, there is legal due diligence, then operational due diligence. If the building needs to be financed there are conversations with lenders. There are presentations to the investment committee and all of these people need to do a large amount of swapping of data as they go through this process of acquisitions.
And if you look at the technology ecosystem that serves all of these people, what you find is that the solutions tend to target individual teams. They’ll help individual teams get their tasks done, but the applications are not speaking to each other. When teams need to swap data between themselves, often they have to revert to phone calls, to emails, just swapping of files. There’s a lot of manual reeking of data that goes on behind all of these solutions. These point solutions.
And so that introduces a lot of cost into the process. It’s time consuming to have to record data manually and makes data quality very, very hard to manage. It creates a lot of chaotic workflows and it impedes transparency in the process. And so, all of this drives a need for integration between all of these point solutions. And what we find is that CTOs, when they’re buying solutions these days they’re not only interested in the functionality that the application can offer their individual teams, they’re interested in how that application can integrate with the rest of the tech stack.
So, what I want to offer you today, is some thoughts on the types of integration that we, at Altus Group, see occurring when customers need to integrate their solutions and the types of integration projects that we see tend to fall into three main categories.
Three Types of Data Integration
The first one is data consolidation and a very, very common type of data consolidation that we see in our world happens with investment managers who outsource their leasing to third party service providers. I’m working right now with a very large investment manager based in London, who has no fewer than 23 service providers who are doing the leasing operations on their building. So, when the fund manager needs to see all of the leases on the entire portfolio so that she can make lease management decisions, that fund manager has to go to 23 different sources to get the list of leases on their property. And so, what we’re doing with our ARGUS Voyanta technology is we’re helping them consolidate those 23 sources of leases into one. So now, the investment manager needs to go to only one place to find all their leases.
The second type is data propagation. And data propagation happens, typically when you have a master source of data within your organization. And then multiple applications need to work on that master source of data.
So again, an example from our world that we often see as an owner operator who uses an ERP system, such as Yardi, JD Edwards or MRI to manage their leases, and their financial data. Then they need to bring that data into our solutions so that they can do modeling of that data.
So, what you have to do is, you have to copy the data from the master source into the application. The problem with data propagation is that it becomes very complicated. If you imagine a situation where someone has say, 10 different applications within their organization and they start to need to propagate data between all of those applications very quickly, you end up with a spaghetti-like structure of data flowing everywhere within the organization. It can become very hard to manage.
And so that leads to the third type of data integration that we’re often involved in, which is data warehousing. Data warehousing is often an alternative to data propagation. Instead of swapping data between individual applications. What you do is you take the data from those applications and then you flow it upwards and surface it in a single data warehouse. Now, while we have investment managers who will typically have debt management systems, lease management systems, ERP systems, and ARGUS modeling systems; what they’ll do is they’ll take the outputs from all of those tools, put in a data warehouse and then they can put a dashboard on top of it. And then everybody in the organization has one place to go to see what’s going on within the organization. It’s a much more efficient way of doing integration than data propagation.
What is Altus Group doing to help Data Integration?
What are we at Altus Group doing to help people with their integrations? I want to offer some thoughts on the different types of technology options that people use when it comes to building these integrations. Most CRE applications are built on top of a database and a lot of integrations start out by reading and writing directly to those underlying databases. And that’s fine. It works. But it tends not to be particularly robust because as these applications upgrade and change, the database schema changes too. And it tends to break the integrations that are built on top of that, the database.
The next level up from direct database integrations is file-based integrations. File-based integrations are more robust because file formats tend to stay the same even as applications change. However, they’re often very manual. They involve exporting a file from one application and putting it into another application. It’s still not the ideal solution.
So, the ultimate is to use APIs. APIs give developers the opportunity to build completely seamless integrations between applications. And I should probably take the time to explain what an API is, I find it’s one of those technical terms that people don’t always understand, or they’re not familiar with it. So API, API is just technological tools that enable development teams to create straight through integrations between two applications. OK, so you can give an API to your development team and then they can use that to build a middle layer, it does a completely automated integration between two applications and I’ve got an example here, which shows how an integration between an ARGUS solution and a property management system would typically work using APIs.
So with that lead-up, you can probably guess what I’m about to announce, the fact that ARGUS Software will soon be releasing an API for its solution. So, this is coming up in December 2019.
The API is designed to support all three of those use cases that I outlined before: data warehouse integration, property management integration. We’ll support them. But most excitingly of all is that for the first time, we’re opening up the ARGUS calculation engine to our end user. So, end users will be able to build their own in-house applications that use the ARGUS calculation engine to do real-time sensitivity analysis on their portfolios. They’ll no longer be limited to doing that through the ARGUS front end.
Thank you very much.