- Membership counts drive MLS budget considerations, including vendor choices, dues levels for agents and brokers, and staffing.
- Forecasting next year's membership count is therefore necessary, but problematic. Predicting the future is hard, but there are some steps MLSs can take to help yield better results.
- Aggressive membership forecasting can land MLS execs in trouble if the actual count falls short.
KANSAS CITY — Budgets often consist of hard facts and figures, but for MLSs, there is at least one figure included that is guaranteed to be wrong: the MLS’s future membership count.
MLSs are businesses. The number of members — customers — an MLS thinks it will have in the next budget period — be it six months, a year or 18 months down the road — helps the MLS gauge its revenue and expenses that period.
That figure could mean the difference between raising dues for brokers and agents or keeping them the same; bringing on a new vendor to help agents be more efficient or getting rid of a vendor; or bringing on new staff to deal with support requests or letting someone go.
But membership forecasting, like most attempts to predict the future, is, well, really hard to do well.
Experts don’t do any better than novices, Elliot Eisenberg told attendees at the first-ever Conference of MLS Financial Executives (CoMFE) in Kansas City on Tuesday. CoMFE was put on by the Council of Multiple Listing Services (CMLS). The annual CMLS conference starts today.
Eisenberg is the chief economist for economic consulting firm GraphsandLaughs LLC.
“Experts are in love with their own ideas. They don’t think outside the box. They come up with stupid ideas,” he said.
“Expertise is important in understanding where we are and where we’ve been; it’s worthless” for forecasting.
And if forecasts are taken as gospel, they can have adverse consequences for their creators, Eisenberg said.
“It’s risky, because you’re going to be wrong. If you give it to your board of directors, prep them,” he said.
Use words like “I think” and “I feel” and remind them that the future is unknowable, he added, pointing to predictions made by “experts” in the past that didn’t pan out in a big way.
Where MLSs can get in trouble is if they make their membership forecast too aggressive, said CoMFE organizer Jay Markell. Markell is also the chief financial officer and chief operating officer of the largest MLS in the Sunshine State, My Florida Regional MLS.
“I would rather go to the board of directors and say we’re meeting our numbers,” than falling short, Markell said.
Central Virginia Regional MLS does its own forecasting and budgets conservatively, setting revenue low and expenses high, said CVR MLS COO Deborah Talley, who attended the conference.
Her MLS leadership has been pleased by the results, she said.
Eisenberg advised against trying to predict too far into the future, especially with a limited data set. Three years of past membership data is not enough to try to predict membership through 2017 with much confidence, for instance.
Forecasts should also be constantly updated, at least on a monthly basis, he added.
This is especially key in markets where membership counts can have wild swings. MFRMLS’s budget cycle lasts 18 months. Eighteen months ago, the MLS had 34,000 members. Now it has 45,000 members due to the booming Florida market, Markell said.
That’s a 32 percent increase.
In June, 3,500 members didn’t renew their memberships, but by August, new members and then some had taken their place, he said.
“I do the budget, and then right after the budget year starts, we re-forecast,” Markell said.
Forecasting is problematic, but membership is nonetheless the key driver of an MLS budget, according to Markell.
“When I first got [to MFRMLS], they wanted to focus on the pencil inventory, the paper inventory. I said, ‘That’s not me,'” he said.
MLSs can use different types of models to come up with their forecast, some subjective and some objective.
Objective models use a specified process that can be replicated. The most common approach is to extrapolate from data on hand, such as past membership data.
An example of a subjective approach is asking the members of an MLS’s board of directors how they think membership will change or polling them on whether they think their local market is improving or not.
In that case, the person asking the questions should not allow discussion but rather should have everyone put their guesses into a hat, Eisenberg said. This is because extroverts tend to dominate meetings and sway others around them to think as they do, he said.
Combining forecasts, even subjective ones, can yield better results than a single forecast, according to Eisenberg.