Is there any time of the year more frustrating than budget season? So much depends on it—promises to ownership, commitments to management, and benchmarks for future bonus payouts—it’s a wonder that organizations don’t buckle under the weight of all that pressure. And the worst part of it is that, with all the time spent on budgets, operators end up putting their head facing the CFO and COO and their rear end facing the customer—often in the 3rd and even 4th quarter which can be some of the more challenging times.
Everyone muddles through but often at the expense of a) taking too much time away from customers and b) setting up goals and objectives that only cause more challenges in the future.
While not all of these are applicable to everyone, we have found five key drivers that make rental housing budgeting painful:
There are many generic budgeting tools out there. The challenge with these tools is that they were not built for rental housing and the many unique aspects of rental housing budgeting (e.g. the concept of renewals being based on both expiring and new rents or costs being triggered by the number of move-ins or move-outs.
These tools can be configured for rental housing; however, 1) that typically involves a major project costing hundreds of thousands of dollars (we’ve seen some of these easily top $1 million) and 2) at the end of the day, users are still left with a clunky workflow and limited model.
Simply put, Excel is not an enterprise application! First, it can be very complex with all manual processes to copy and paste data into the spreadsheets and then create the appropriate output. It’s not unusual to see instruction guides for community managers that run 30 steps or more! This complexity introduces another challenge—multiple opportunities for mistakes. While not impossible, it takes a lot of effort and can be a bit cumbersome to lock down Excel the way a purpose-built user interface can; and it’s impossible to drive workflow in Excel the way a well-built interface will. The result is a much higher likelihood for a variety of mistakes.
Lastly, Excel doesn’t provide any underlying database storage. This makes analysis and aggregation at best a complex set of manual steps with references between worksheets (or worse, workbooks) and a variety of sophisticated functions like VLOOKUPs, INDEX matches, etc. In contrast, a budget application built on top of a structured database makes it easy to perform all of the rollups, ad hoc analyses and other investigations users will want.
Many models attempt to simplify the process by having users enter “key assumptions” (e.g. occupancy by month) that seem appropriate but actually make it difficult to analyze why budgets were missed (or exceeded). These happen on both the revenue and the expense side.
Even something as simple as landscaping can become a bit of a challenge if individual line items are not tracked. As an example, a Regional Manager is examining a budget of $500 per month for landscaping and then a sudden $4500 entered in September. She has to call or email the Community Manager to inquire why the big number in the one month. Was that a typo? Eventually, the Community Manager remembers that she entered the higher number in that one month because it is time for the quadrennial tree inspection. If the budget allowed for entering each line item that aggregates to the GL account, then the Regional Manager would have seen this immediately thus saving everyone some time and hassle.
A company is frustrated with its current budget and forecasting model/system. They decide they’re going to fix this by building a new budget model. They form the appropriate committee, assign a project lead, involve everyone who needs to be involved, and embark on building this new system, excited by the opportunity.
Inevitably, time crunches and other resource trade-offs lead to some functionality being deferred as “we’ll get to that in version 2.” Yet, numerous times in our careers, we’ve experienced situations where few, if any, material enhancements are made after version 1. The energy, excitement, and commitment for version 2 simply never match that of v1.
In most situations where a rental housing company has built its own model, there is only one (or at most two) people who “own” the model and really understand it. If/when that person leaves, most of the knowledge leaves with them. This Keyperson risk means executives are at constant risk that just one inopportune resignation will substantially upset the next budget/forecast cycle…often just when they thought they had it all wired tightly!
Donald is CEO of Real Estate Business Analytics (REBA) and principal for D2 Demand Solutions, and industry consulting firm focused on business intelligence, pricing and revenue management, sales performance improvement and other topline processes