June 30, 2017
By Robert Dieli, RDLB, Inc., in-house economist at MacKay & Company
This happens to be one of those situations where the lead time between the writing of a piece and its appearance can actually be helpful to both the person reading the article and the person writing it.
As we put “pen to paper” (actually as we click away on our keyboard) we are looking at an industry environment rife with positive “soft” data. What are “soft” data? The results of surveys about business confidence and spending plans. Since the turn of the year, there has been a surge in business confidence and a rise in spending plans for both people and equipment. What we have not yet seen, for reasons that we shall presently ex-plain, is the associated uptick in the hard data. What are “hard” data? The number of units reported in the last edition of Class 8 truck sales, for one.
And there you have the reason for the question at the top of the piece.
Our expectation is that some of the confidence and optimistic plans will translate into more spending and hiring. The problem is the lead time associated with each of the efforts.
One activity where we think results should show fairly quickly is hiring. The decision to increase payrolls is usually made quickly and the hiring process is straightforward. Of equal importance, the reporting interval is short. The Bureau of Labor Statistics updates the truck transportation employment figures every month.
The data relating to other types of spending takes longer to come to light, both because of the process involved in the spending itself and then the report-ing of same. In the case of a Class 8 truck, the buyer spec’s the truck and places an order. Then the OEM has to slot that truck and build it. Then the OEM reports it to WardsAuto, who then has to compile and publish the numbers. Then the various media outlets have to show you the numbers. All of this can take months. In the case where the spending figures get aggregated into statistics like Gross Domestic Product, or our own metric Truckable Economic Activity (TEA), the reporting interval can be even longer.
The other area where the transition from soft to hard data is both lengthy and hard to forecast is in the budgeting process at both the federal and the state levels. All units of government operate on a fiscal year and a legislative calendar. Both of those are widely known and set the parameters for when certain actions should be taken. Where things get complicated is between the start of the process where the president or the governor proposes a spending plan and the subsequent hearings, bill drafting and lobbying that happens before that agenda is settled and put to a vote. And, let us not forget, while the legislatures are debating how much to spend, they will also be debating how much to tax. All of which adds up to another instance of “soft data” (campaign promises) getting converted into “hard data” (legislation and regulations).
There used to be a commercial that asked the question “is it soup yet?” The employment “soup” should come together quickly. The other “soups,” based on the confidence-driven numbers on spending, will take longer.
The political “soup” follows its own rules. Because of that, the folks who don’t understand how hard data come into being and how long they take to come to light will downplay the progress that is being made. Because it could well be this time next year before we can fully measure how much of the “soft” data has turned into “hard” data, we have to monitor the process as closely as we will be monitoring the results.
Robert F. Dieli is president and founder of RDLB, Inc. an economic research and management consulting firm based in Lombard, Ill. Bob regularly collaborates with MacKay & Company on economic publications as well as industry presentations such as HDAD.