We recently heard from DAT customer Ben Guggenbiller, Senior Director Data & Analytics at ODW Logistics, about his business and how he uses DAT products. Ben gave us his thoughts on data analysis and the tools that help ODW stay sharp, his business goals, and challenges facing brokerages.
ODW Logistics is a national 3PL providing transportation management, contract logistics, and supply chain optimization for a completely integrated logistics solution. The company serves over 250 clients across the United States in industries ranging from retail, food and beverage, health and beauty, and industrial manufacturing.
ODW Logistics is unique because of its breadth and depth of product offerings, including warehousing, distribution, value-added services, all modes of full truckload, less than truckload, parcel, drayage, intermodal, container rescue, freight consolidation, and freight management. ODW’s combination of technology, team, and processes enables a strategic approach to logistics planning, delivering integrated solutions optimized to customer requirements and achieving results that truly “Deliver the Difference.”
When was the brokerage founded, and what prompted you to start?
Guggenbiller: In 2009 the ODW Transportation group was established when the company founder (John Guggenbiller) left his traditional brokerage firm to focus on creating additional service offerings in the middle market. Over time, several experienced folks John had worked with prior joined him at ODW.
What type of brokerage model do you operate?
Guggenbiller: ODW focuses on servicing the customer to generate new sources of value. For example, we put emphasis on on-time delivery, solutions that optimize costs, freight consolidation with the ODW warehouse group, leveraging internal and external technology tools to make better decisions for customers.
Does the brokerage specialize in specific freight types or markets?
Guggenbiller: ODW is headquartered in Ohio, which allows us to be within a day’s drive of the majority of the U.S. population. We also have locations in California, Tennessee, Wisconsin, and Illinois. We’re primarily focused on servicing middle market consumers within retail, industrial, and food market verticals with a wide mix of product types including spot/contract full truckload (van, reefer, flatbed), less than truckload, parcel, drayage, intermodal, container rescue, freight consolidation, and freight management. Our specialty involves delivering and planning solutions that blend multiple modes of transportation, increasing trailer utilization, and reducing supply chain related waste.
The middle market feels like a relatively underserved area in the transportation industry – it is difficult to find many companies that offer a comparable breadth of service and be willing to engage the customer to create value-add solutions. Food and industrial verticals came naturally because we are situated in the Midwest and are near many manufacturers, so we had plenty of opportunity to optimize here. Retail verticals came as our freight consolidation product line has grown. Many freight consolidation opportunities have a retail location as the final destination. As we have grown relationships in the retail space, our size of customer and size of carrier has grown, too.
What products are essential to the day-to-day operations of the brokerage?
Guggenbiller: Over the past 12-18 months, the number of DAT products that we use has grown significantly. Currently we have a DAT API connection linked to a third-party vendor tool. This has helped us automatically set a target rate for every load on our load board and gives our sourcing teams guidance when they seek our carriers. We have been using this connection for about 24 months.
Prior to that, our pricing team would manually look up each load, look up lane rate information, and manually apply a best guess on what the rate should be to give guidance to sourcing teams. This was extremely time consuming, drove lots of variability in the process, resulted in poor consistency/traceability, and left margin on the table in many cases.
We have been able to reduce labor in this process by 90%, freeing that time up to support other areas of the business. We improved our market sourcing by 3-5% and have more consistent data to help benchmark against going forward. We have a process established where we pull lane data down from DAT to support RFP work using DAT’s multi-lane tool.
This process takes rates at different snapshots of time and applies logic to generate approximately a dozen different scenarios with different margins, different risk profiles, and different pricing strategies to help us streamline the RFP process, drive consistency, and remain competitive.
We have a connection to DAT’s Snowflake product and consume different snapshots of the truckload market on a regular basis. This data is extremely valuable, as it helps supplement our knowledge of the market and allows us to easily benchmark our performance against the market.
What did DAT simplify or make easier for your brokerage?
Guggenbiller: Access to large data in a real-time basis. DAT allows users to look up transactional data, but DAT’s API/Snowflake/multi-lane products allows a better “top down” view of the market that can be used to get a better sense of the map quickly. Additionally, because DAT provides dimensions in their data that helps qualify the data quality (such as number of contributors, number of contributions, market area size, time frame, etc.) it is relatively easy to make a self-assessment on which data to trust, and to what degree. Very useful and very flexible to use for whatever business application required – the basic building blocks of data analysis.
What are the greatest challenges facing the freight or brokerage industry?
Guggenbiller: Because of the size and fragmentation of the market, it has historically been very difficult to share information in a consistent manner to drive efficient decision making in a meaningful way. We are approaching an era where data is relatively easy to access due to offerings from technology vendors, and pattern recognition tools such AI and machine learning are pulling information from these vendors in a meaningful way.
As this occurs, the cost floor in the market is likely to decrease over time as players who invested in greater efficiencies benefit. To remain competitive, players in the freight industry will either need to invest to drive better data-based decisions, invest to better streamline their operations, or invest in new methods to generate unique sources of customer value (or likely all three).
What are some short-term or long-term business goals?
Guggenbiller: Short term goals include utilizing MCI/LT Ratio and Ratecast in our decision making and/or benchmarking processes. Intermediate goals include expanding the market views and frequency of data we consume via products like Snowflake.
Learn more about adding market insights and analytics to your operations with DAT iQ.
