Technology often helps concrete producers enact small changes that make a big impact. This Tech Talk column examines real-life ROI (return on investment) for reducing on-job waiting time. The data is from real producers using technology to improve performance. To protect financial information, fictional company financials are used.
The waiting game
At WW Ready Mix, drivers play an important role in customer service. Ready-mix delivery professionals are responsible for providing timely and professional service at the jobsite. To help drivers — and overall operations — run more efficiently, WW evaluated how much time they were spending at jobsites.
The producer looked closely at the time between arriving at the job and beginning the pour. With the help of analytical software WW found that, on average, roughly two thirds of multi-load orders requested spacing faster than the customer could unload trucks. This caused trucks to ‘stack up’ at the jobsite and resulted in unnecessary wait time for drivers. While the dispatch center quietly adjusted unrealistic truck spacing requests, a gap remained.
WW calculated an average cost of $1.58 per minute of truck wait time, including the driver’s pay, vehicle lease and variable costs. In 2017, WW’s drivers spent an average of 53.72 minutes, or $84.88, onsite per load. The average pour, wait, and wash times were 28.11, 15.84, and 9.54 minutes respectively. Multiplied across 561,798 loads for the year, job site time cost the producer $47,684,045.
WW also looked at work type versus pouring time and actual mix pricing. The result was that slower pouring jobs were not priced high enough to compensate for added truck time. For example, the sales team treated curbing work as filler, and aggressively discounted it to capture work that turned out to be highly unprofitable.
Recouping lost time
Based on 2017 financial results, saving one minute of time would have increased bottom line profitability by $887,640. In 2018, WW set a corporate goal to reduce waiting and pouring time by a combined average of 1.5 minutes, anticipating a $1,331,461 savings.
First, a mobile app was put in customers’ hands, which included the ability to track trucks and compare ordered versus actual truck spacing. The sales team used the same app to monitor their customers’ truck turnaround times. Then, during face-to-face meetings, salespeople and customers discussed mutual savings opportunities.
WW also began using CRM and quotation software that required managerial override for pricing that fell below a minimum acceptable profit margin. Thus, more labor-intensive work was priced higher. This was a difficult adjustment for the sales team, as WW’s competitors did not increase pricing on slow-pouring jobs, such as curbs. However, due to the current up-market, they were able to reallocate resources to more profitable work. Onsite costs were reduced, and overall profitability improved.
Economic impact
WW reduced drivers’ overall time spent at job sites to just under 52 minutes per load during the first three winter months of 2018 with savings of just over $200,000. These preliminary results suggest WW can indeed reduce the onsite time by 1.5 minutes as planned. Provided this goal is achieved, the producer will save $1,331,461, which represents 2.7% EBITDA growth.
