How to Use Asset Management Analytics

There’s a lot of data to look over when allocating investment capital, and making sense of that data can take a lot of time if you don’t have the right tools. The AI revolution changed much of that with lightspeed dashboards tailored to the priorities of investors, but mysteries still remain skills for which AI can provide a shortcut to use, but not an understanding. 

When it comes to investment portfolios, those who can use numbers to tell a story are better able to manage one. They are also better suited to spot worthwhile investment opportunities when they arise. 

So how do you read the numbers? Well, you need tools. In this blog, we’re talking about asset management analytics tools designed to give investors and property owners a comprehensive overview of asset performance. We’ll talk about what asset management analytics are, how to use them, and which tools get the most out of them. 

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What is asset management analytics?

To illustrate asset management analytics, let’s pretend you own an orange sales business. In order to be profitable, you need a few pieces in place.

First, oranges need to cost less than you sell them for. You also need to outsell other orange sellers, either by selling better quality oranges for more or charging less for comparable ones. As time goes on, you’ll want to direct more resources to locations that perform better, maybe even by closing down a few weaker spots. 

All these data points use numbers to express a business’s profitability. This is data analytics: using complex equations and algorithms to distill a bunch of numbers into a simple, easy-to-read metric. 

While investment properties are more complicated than a simple orange sales business, they benefit from data analytics all the same. 

You probably already know a few common asset management analytics figures, like:

• ROI (Return on Investment): How much capital an investment requires compared to how much revenue it generates
• Expense Ratio: The percentage of assets that must be deducted in order to cover operating expenses 
• Sharpe Ratio: A property’s rate of return compared the average rate of return for comparable ones
• AUM (Assets Under Management): The total market value of assets in a portfolio
• Beta: An asset’s volatility compared to overall market volatility

There aren’t any secrets to data analytics, but figures like these have earned a reputation for helping investors spend their time wisely when it comes to asset management.

4 types of analytics for asset managers

Different data metrics serve different purposes. In the orange sales example from earlier, knowing how many oranges you sold downtown isn’t very helpful in deciding whether to buy oranges overseas. One tells what already happened while the other needs predictive analysis. This is why there are different kinds of asset management analytics.

The four categories under which most data analytics fall are:

• Descriptive: The most basic of the data conclusions, descriptive analytics are basically your raw data total annual revenue, number of units vacant, total maintenance costs, etc. They tell a relatable story that insiders and outsiders alike can use to understand how a business is performing. They can also be used to build more specialized metrics.
• Diagnostic: Relationships and correlations happen within diagnostic analytics. Perhaps a property comes up for sale that seems like an unbelievably good deal. Diagnostic analytics would encourage a closer look to learn why the seller isn’t charging top dollar, possibly preventing you from making a costly mistake.
• Predictive: Once you have a handle on how and why a portfolio performs the way it does, you can use that data to look ahead elsewhere. Maybe you have good reason to believe a location is about to drop in value, giving you a chance to sell your property and get out while there’s still money to be made. 
• Prescriptive: While these other three areas deal with concrete information, prescriptive analytics is more interested in long-term strategy. Perhaps you want to move away from growth and further into stability. Prescriptive analytics would suggest where to start investing so you can achieve your goals. 

No matter what, you need to collect data before you can analyze it. Cataloguing and taking inventory of assets not only gives you figures to work with, but can also inform what’s actually important to your portfolio. 

Some great sources for acquiring raw data include:

• Financial reports
• Property appraisals
• Economic data from government agencies:
  • Federal Reserve Economic Data (FRED)
  • Bureau of Economic Analysis (BEA)
  • U.S. Census Bureau
• Property heat maps in a given area
• Long-term property performance benchmarks

Make tables, plug in the data, and you’re off to a good start. Unfortunately, this is where things get challenging. Which metrics are the most important? What if you don’t have enough data to calculate them? Why does everybody seem to think this one metric matters?

You don’t know what you don’t know. The internet is your best resource for finding new metrics that interpret your data, but if you haven’t thought of the right question to ask, it won’t be of much help. 

Where do you go next?

Getting started with asset management analytics

The analytics industry is massive, probably because your imagination is the limit when it comes to how you use data. AI tools offer a high level of convenience and customization plug a few numbers in and get answers to questions about what’s going on. Tools like Leni have grown in popularity when it comes to sifting through data and providing useful investment advice. 

Of course, you also have gigantic data firms like Bloomberg and CoStar that charge huge subscription fees for access to their information. These resources are great, but their high price tag can be a little scary. If you want a free option, find a few spreadsheet templates online and analyze the data yourself. 

The more you play with the data and see how it works, the better you will understand the metrics that matter to you specifically. Over time, you will discover your favorites and be able to incorporate more metrics into your investment strategy. 

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