Securing the right work at the right price is pivotal to succeeding in the ready-mix concrete business, as price is a producer’s single most impactful way to drive margins. However, determining the right price for the right job is the challenge. Some customers, market segments, and jobs are more profitable while others may be less—or even result in negative profitability.

Gaining the data needed at the speed required to price a job competitively is the main obstacle ready-mix producers face in setting the right price. Simply applying overhead doesn’t fully account for costs related to job volume, material cost, average delivery, and other customer and jobsite variables.

Producers need a way to quickly evaluate the cost of highly variable logistics for each job, as well as to better predict risk management, competitor capability, and the market segment. Often, information is siloed across delivery, batch, quoting, and ERP systems, making gathering information quickly enough to provide accurate cost analysis a daunting task. Information needs to be available instantly to make sure the quote reflects the company’s risk and reward target.

Pricing and bidding correctly is more than just math and data—it’s dynamic and takes human insight. Understanding the market, the people involved and who’s worked with whom is key.

Typically, producers use average costs to bid jobs. However, that often leads to poor outcomes due to a lack of data on the job’s many variables. Gaining a full understanding of the job logistics before placing a bid can make the difference in profitability. When pricing a job, the top factors producers evaluate are materials, production, and delivery costs. Materials and production costs are known variables that can be tracked and understood using historical data. The harder-to-quantify cost is delivery, as well as risk and the competitive landscape.

It’s difficult to compare delivery costs across projects and clients, as the average load size and length of time spent on jobsites are unknown variables. Delivery costs will have an average for an entire year, but that average can vary by a factor of five times from the lowest to the highest rates. For example, producers may know materials will cost $100 per yard and production will cost $10 per yard, but delivery costs may range from $15 to $75 per yard or more. With already-slim profit margins, the delivery estimate must be as accurate as possible to avoid negative profitability.

The solution lies in advanced analytics and dynamic load costing. Dynamic load costing factors the true logistics costs and risk weights for customer behavior, taking into account unknown variables like wait times and unload times—resulting in a much more powerful and accurate way to cost.

Advanced analytics and dynamic load costing can provide more accurate delivery cost estimates by evaluating the load size, distance, and site efficiency. They also harness historical reference data for the market segment and pour type of the project, historical client jobsite efficiency, and even the historical costs of delivering a particular type of mix design. Using these methods, tools like C60 allow producers to see current costs—including delivery costs—across all jobs, products, and market segments serviced.

By understanding strengths and weaknesses in business logistics, companies can better analyze the market and hone in on their niche.

A full understanding of the market segment the company specializes in, including customers and materials, is a key factor in improving profitability.

Access to company information allows producers to use historical information to make informed business decisions related to profitable markets, clients, and products across the entire company history—from yesterday to company inception. This information can guide decisions on improving existing work and pricing future work in the same market segment to maintain profitability. It can help pinpoint which market segments should be a stronger focus for business development as well. A clearer picture of costs per market segment, products and mixes, customers, and location will help determine whether the job is a good fit—and whether the current niche is still effective.

Access to that data can help the producer understand how it services specific jobs, how well it performs when servicing those jobs and whether they can be performed more effectively. When evaluating market segments, it’s key to consider the liability risk associated with each one as well. Some segments, like infrastructure, towers, and other heavily engineered structures, are notoriously higher risk. Failure to appropriately price this risk premium and the management effort required to mitigate it is a common mistake producers make. Other work, like low-rise walls and slabs on grade typically are considered low risk. Understanding the market segment will help guide risk considerations.

When setting pricing strategy with the market segment in mind, producers need analytical tools that can quickly cluster all customers by segment, product, and jobsite to pinpoint those that are more profitable. Data can help evaluate the current client and job portfolio as well, including the products customers are buying and the types of jobs they’re working on. By understanding where the company is losing money, producers can end or renegotiate contracts that may no longer be an asset.

All these considerations can help producers determine whether or not to bid on work or renew contracts with existing clients. But a key component to making those decisions is understanding the dynamic of the competitive landscape.

When bidding a new job, the producer first should consider whether it wants or needs the work. Evaluate whether the job fits in with the portfolio, and whether the materials, equipment, and manpower are available to do the work efficiently. It’s also important to consider the market and determine which competitors have the ability to do the job, how busy those competitors are, how likely they are to bid the work, and how those competitors historically have priced similar jobs.

Analyzing competitor data is extremely difficult without accurate, up-to-date competitor insights. Tools like C60 benchmark market data by plotting them on a map and enable logistics costs comparison. That information can be used to better understand the competition. If a potential client has worked with a competitor for a number of years and opens a bid, producers should do an analysis to determine why the client is no longer working with the competitor. If the producer suspects the change is price related, proceed with caution to avoid driving down the overall industry price.

By integrating data on logistics, the market segment, and the competition—and applying advanced analytics—C60 helps producers move from traditional average costing models to dynamic load costing, which results in prices that drive more profitable outcomes. The next article in this five-part series on solving common business challenges to improve profitability will cover ways to identify and mitigate revenue leakage. Take a look at our first article that covers the top four profitability drivers impacting ready-mix business leaders for a bird’s-eye look at improving the bottom line.